Wheelchair propulsion technique and mechanical efficiency after 3 weeks of practice. (Med Sci Sports Exerc. 34(5): , 2002)

Transcription

1 CONTENTS Chapter 1 Introduction 2 Chapter 2 Chapter 3 Chapter 4 Chapter 5 Chapter 6 Chapter 7 Wheelchair propulsion technique and mechanical efficiency after 3 weeks of practice. (Med Sci Sports Exerc. 34(5): , 2002) Adaptations in physiology and propulsion techniques during the initial phase of learning manual wheelchair propulsion. (Am J of Phys Med. 82(7): , 2003) Short-term adaptations in co-ordination during the initial phase of learning manual wheelchair propulsion. (J Electromyogr Kinesiol. 13(3): , 2003) Consequence of feedback-based learning of an effective force production on mechanical efficiency. (Clin Biomech. 17(3): , 2002) Effect of stroke pattern on mechanical efficiency and propulsion technique in hand rim wheelchair propulsion. (Med Sci Sports Exerc. Submitted) Influence of task complexity on the mechanical efficiency and propulsion technique during learning hand rim wheelchair propulsion. (Am J of Phys Med. Submitted) Chapter 8 Epilogue 119 References 130 Summary 141 Samenvatting 147 1

2 Chapter 1 Introduction 2

3 Chapter 1 LEARNING HAND RIM WHEELCHAIR PROPULSION Although motor learning is implicitly present in daily life, not much is known about the learning process of gross motor skills. Motor learning has been defined as a set of internal processes associated with practice or experience leading to relatively permanent changes in the capability for skilled behavior (Schmidt et al. 1999). There are several theories regarding motor skill learning, however, most of them focus on the way a new task should be presented to the novice subject i.e. in terms of knowledge of results (information feedback of goal achievement) (Broker et al. 1993; Salmoni et al. 1984; Schmidt et al. 1991), the learner s focus of attention (internal or external) (Wulf et al. 2001), self-control and practice in dyads (McNevin et al. 2000). Furthermore, most motor learning studies have focused on simple motor tasks, like for example single-joint movements such as elbow flexion/extension (Corcos et al. 1993; Flament et al. 1999), or have been associated with the development of motor tasks in children (Ledebt et al. 2000). However, little is known about the biophysical aspects of gross motor skill learning in the adult. For studying the biophysical aspects of learning a gross motor task, an activity should be chosen that is novel for a large group of adults and is relevant to learn. One interesting area of learning different and new modalities of gross motor skills, emerges in those persons who become wheelchair dependent. In the context of rehabilitation, motor skill acquisition is a crucial but often very implicit - ingredient in the restoration of motor function and of recovery of mobility. Therefore, understanding gross motor skill learning is important for an effective and successful rehabilitation process (Gonzalez et al. 2001). Individuals who - due to circumstances - are forced to use a wheelchair have to learn this completely new motor task and many wheelchair-related functional daily activities in adult life. Learning wheelchair propulsion is important because it enables individuals, especially those with a lower limb disability, to be as active as the general population and to maintain employment, to achieve independence in daily life activities and to pursue recreational activities and social life. Because motor programs already exist in the adult patient, the major issues in (re)learning a motor skill include accessing, reorganizing, and utilizing this information. Despite the fact that the movement pattern of wheelchair propulsion is quite different to what persons were used to, every individual seems to be able to pick up this novel task rather quickly. It is quite fascinating how persons are able to do this because wheelchair propulsion is not an easy task since, among other aspects, the hands have to couple to a rotating thin rim whereas the motion of the hands occur predominantly outside the visual field and force production can only 3

4 Chapter 1 effectively take place in 20-50% of the cycle time (Rodgers et al. 2000). Not many learning studies (Amazeen et al. 2001) have been done with respect to wheelchair propulsion. Wheelchair propulsion is a way of locomotion with an overall low gross mechanical efficiency: it rarely exceeds 10%, meaning that 90% of the internally produced energy is lost to other processes than propelling the wheelchair (Astrand et al. 1986). The resultant 10% will be used to overcome, for example, rolling resistance, internal resistance of the wheelchair system, and air resistance. The efficiency of wheelchair propulsion is much lower when compared to cycling (Coyle et al. 1992) but also to other forms of arm exercise such as arm cranking (Martel et al. 1991; Powers et al. 1984). As a consequence of the low efficiency, hand rim wheelchair propulsion is associated with a high physical strain in daily life (Janssen et al. 1994) and leads most likely to a high mechanical load on the upper extremity (Veeger et al. 2002). That the mechanical load is high or that there is too much repetitive loading might be shown by the prevalence of wrist and shoulder pain after long-term wheelchair use, which has been reported to be as high as 73% in individuals with a spinal cord injury, who rely on manual wheelchairs for mobility (Subbarao et al. 1995). LEARNING AND METABOLISM Improvements in performance result from practice and are a frequently used measure of learning. However, not every change that occurs as a result of practice has to imply improvement, therefore, a measure concerning improvement in performance should be defined. A general accepted assumption is that subjects pursue to perform a task with minimal metabolic cost. In the early eighties Sparrow (Sparrow 1983) linked this assumption to learning since he proposed that metabolic cost might be a fundamental principle underlying the learning and control of motor skills. According to his theory organisms select the coordination and control function that cost the least metabolic energy, and with practice the selected control parameters are refined to attain the task goal with even less metabolic energy (Sparrow et al. 1998). Therefore, the present thesis will use gross mechanical efficiency, and its relationship with technique variables, as central indicator for improved performance. To date, there have been very few studies focusing on the relationship between changes in mechanical efficiency and changes in coordination as a consequence of practice. In repetitive gross motor tasks, such as crawling (Sparrow et al. 1987) and ergometer rowing (Sparrow et al. 1999), it was suggested that movements tend to increase in amplitude and decrease in frequency with practice and that these 4

5 Chapter 1 adaptations led to a higher (mechanical) efficiency. However, the results of the crawling and rowing studies were not significant, possibly due to the small group of subjects in these studies. In a more recent study (Lay et al. 2002) the same research group found a significant increase in economy (in Watts. ml -1 ) after ten 16- min. ergometer rowing sessions. According to the authors practice reduced the metabolic energy cost of performance and practice-related refinements (e.g. decrease in stroke rate and less variability of peak forces) were associated with significant reductions in muscle activation (Lay et al. 2002). Almasbakk et al. (2001) studied the learning process of cyclical, slalom-like, ski movements on a ski simulator. They found that the change in the coordination pattern was in congruence with an improvement in gross mechanical efficiency, indicating an effect of improved technique on the mechanical efficiency. Since the term mechanical efficiency is quite important in the present thesis, this term should be clearly defined. Many definitions of mechanical efficiency have been used in the literature. For an overview of the different concepts of efficiency of human movement, the reader is referred to Cavanagh and Kram (1985a; 1985b) or Van Ingen Schenau and Cavanagh (1990). Gross mechanical efficiency (ME) is the ratio of external power output (Po) over metabolic power (Pmet) (i.e. ME. -1. Po Pmet 100% ). The power output can be calculated exactly when using a wheelchair ergometer and knowing the torque applied around the wheel axles and the velocity of the wheels. Metabolic power is derived from food stores, mainly fat and carbohydrates that is converted into another form of chemical energy, which in turn is converted into mechanical energy through muscle contractions. In utilizing food as chemical energy to contract the muscles, oxygen is consumed. The amount of oxygen consumed during submaximal, steady state exercise can be used as an indirect method for calculating metabolic power on basis of the type of foodstuffs being utilized. Similar to machines, the useful power output will always be less than the metabolic power due to energy losses in the process. Usually, the performance of activities that involve large muscles, such as cycling (Coyle et al. 1992), results in a gross mechanical efficiency of 20-25%. The low gross mechanical efficiency of wheelchair propulsion may be explained by the small muscle mass involved compared to leg exercise, the complex functional anatomy of the upper extremity and shoulder, which requires additional muscle effort to stabilize redundant degrees of freedom, and the discontinuous movement which needs (de)coupling of the hands to the rim (Boninger et al. 1997; Woude et al. 2001). Furthermore, gross mechanical efficiency not only includes the metabolic power consumed to generate the amount of external mechanical power output but also the metabolic power 5

6 Chapter 1 needed for other processes such as ventilation and trunk stabilization (Stainbsy et al. 1980). When external mechanical power output increases, e.g. from arm to leg exercise, the relative contribution of the internal metabolic power (Pint) to the total metabolic power (Pint plus power output needed to perform the task (Ptask)) will diminish as it becomes proportionally less, leading to higher gross mechanical. -1. efficiencies with increments in power output ( ME Po (Pint Ptask) 100% ) (Hintzy et al. 2002; Powers et al. 1984). There are, of course, individual differences that are influenced by body size, fitness level, and talent in performing a given task. In theory, the energy cost of hand rim wheelchair propulsion could be influenced in three distinct components of the wheelchair-user combination: 1) By changing the mechanical characteristics of the wheelchair itself, e.g. the weight of the chair (Beekman et al. 1999), since it costs less energy to propel a light wheelchair compared to a standard wheelchair at the same velocity; 2) By changing the geometry and fine-tuning of the wheelchair-user interface, e.g. the seat orientation (Richter 2001; Woude et al. 1989a; Hughes et al. 1992; Masse et al. 1992), camber (Veeger et al. 1989b), hand rim tube diameter (Linden et al. 1996) and hand rim shape (Woude et al. In press), the movement of the upper extremity could be physiologically more optimal e.g. in terms of muscle contractions; 3) And by training the user him/herself since the mechanical efficiency could increase due to physiological adaptations, which take place to satisfy the increased demand of the cardiorespiratory system, and an improvement in propulsion technique. At this stage, it is important to separate the concepts of training and learning. With training both physiological adaptations and changes in the propulsion technique or coordination occur when the intensity, frequency and duration of exercise are equal to or higher than generally accepted training guidelines, such as those that are recommended by the American College of Sports Medicine (ACSM 1990). However, with learning only changes in propulsion technique are meant, without the simultaneous occurrence of physiological adaptations over time. Thus learning is implicit to training but not the other way around. Therefore, to study the effect of learning on the mechanical efficiency only, possible physiological adaptations should be minimized by using an exercise protocol that is well below the ACSM guidelines in terms of intensity, frequency and duration of exercise. PROPULSION TECHNIQUE AND EFFICIENCY Wheelchair propulsion technique is a very general term and can be split into more specific terms. When using the term propulsion technique in the present thesis, the term comprises timing variables (e.g. cycle frequency, push duration and cycle time), force application (e.g. the effectiveness of force direction), and inter-cycle 6

7 Chapter 1 variability (i.e. how similar the subsequent pushes are). Experience seems to influence both energy cost and technique in wheelchair propulsion, as can be derived from cross-sectional wheelchair studies (Knowlton et al. 1981; Brown et al. 1990; Patterson et al. 1997; Tahamont et al. 1986). Several studies investigated the difference in, among other variables, efficiency between non-experienced ablebodied subjects and experienced wheelchair-dependent subjects. Although the results of these studies are inherently limited due to the cross-sectional design and different protocols, results suggest that experienced wheelchair users had a significantly higher efficiency compared to able-bodied subjects (Brown et al. 1990; Knowlton et al. 1981; Patterson et al. 1997; Tahamont et al. 1986). The question, which arose, is whether this difference in mechanical efficiency can be explained by physiological adaptations only or also by an improvement in propulsion technique or motor control. That timing variables have an effect upon the efficiency or economy (the rate of submaximal oxygen uptake for a particular activity and at e.g. a certain speed) has been shown before by Woude et al. (1989b) and Goosey et al. (2000) with respect to the cycle frequency. These studies both found that the freely chosen cycle frequency was most optimal with respect to the mechanical efficiency or economy and that any other higher or lower cycle frequency showed a lower mechanical efficiency or economy. Patterson & Draper (1997) found differences in propulsion time, push angle and work per stroke, with experienced subjects showing higher values compared to novice able-bodied subjects. These results were more clearly expressed at higher velocity levels. Studying the effectiveness of force application during wheelchair propulsion has been a topic for many years (Veeger 1992; Rozendaal et al. 2000; Dallmeijer et al. 1998; Boninger et al. 1997). The non-tangentially directed propulsion force is theoretically far less than optimal, and was first assumed to be at least partially responsible for the low mechanical efficiency (Veeger 1992). However, a model study showed that an effective force application was accompanied by an increase in shoulder muscles activity (Veeger 1999). Furthermore, a recent simulation study concluded that experienced wheelchair users seem to optimize the force pattern by balancing mechanical effect and musculoskeletal cost of the pushing action (Rozendaal et al. 2000). Whether completely inexperienced wheelchair users are able to learn a more effective force application and what the effect on the mechanical efficiency would be, are yet unclear. Brown et al. (1990) found a difference in mechanical efficiency between inexperienced and experienced wheelchair users. Furthermore, wheelchairdependent subjects had significantly greater shoulder extension at the point of 7

8 Chapter 1 initial wheel contact as measured by the shoulder angle, while the able-bodied subjects had significantly greater shoulder range of motion at all work rates in comparison to wheelchair-dependent subjects. Veeger et al. (1992a) studied the difference between trained and untrained subjects during a sprint test and only found differences in kinematics parameters: the able-bodied group extended their push further, leaned significantly more forward, and started the push with their arms in a more retroflexed position. The inter-cycle variability has not been often used in previous wheelchair-related research. However, it is a common variable in the motor learning research area. The typical finding is that movement variability reduces as function of practice (Vereijken et al. 1997). It might be expected that a stable, smooth movement pattern will lead to less energy expenditure, since fewer corrections are needed, and thus to a higher mechanical efficiency. Again, all the above-mentioned studies were cross-sectional. Therefore, it is not known whether the differences in mechanical efficiency between the groups are due to physiological adaptations, which could have taken place over time in the wheelchair-dependent group, or due to differences in propulsion technique between the experienced and inexperienced groups. Some training studies have been performed in the past, in which mechanical efficiency and propulsion technique were evaluated after a period of training (Dallmeijer et al. 1999b; Rodgers et al. 2001; Woude et al. 1999). A 6-wks training intervention (including stretching, strengthening, aerobic exercise) of wheelchair users led to decreased stroke frequency, increased maximum elbow extension angle, increased trunk and shoulder range of motion, and increased wrist extension moment (Rodgers et al. 2001). Oxygen uptake values were similar before and after training although power output increased significantly after training (Rodgers et al. 2001). A 7 wks wheelchair training (30 min, 3. wk -1 ) had favorable effects on maximal physical work capacity in able-bodied subjects (Woude et al. 1999). At submaximal exercise (Dallmeijer et al. 1999b), an increase in stroke angle, push time and cycle time after 7 weeks of training was found. However, efficiency and effective force direction did not change in comparison with a control group. Much to the authors surprise the control group showed a slight improvement in efficiency and effective force direction as well. Although the low number of observations for the efficiency may explain the lack of concomitant improvement, the authors (Dallmeijer et al. 1999b) hypothesized that efficiency and force application were short-term adaptations. It has been found that the maximal power output of people with a spinal cord injury during wheelchair propulsion increased significantly between the start of the rehabilitation process and 3 months later 8

9 Chapter 1 (Dallmeijer et al. 2003). Kemenade et al. (1999), in their study on wheelchair propulsion under submaximal conditions between the initial stage of rehabilitation and one year after discharge, found no differences in effective force direction, mechanical efficiency, and timing variables. However, lack of results could be due to the very heterogeneous subject group regarding lesion level (ranging from C6 to L3/4). So far, no study has been performed that examined changes in efficiency due to wheelchair skill acquisition only. Since the topic of this thesis is about learning hand rim wheelchair propulsion, only completely novice wheelchair users could be included in the different studies. However, this is virtually impossible with novice wheelchair-dependent subjects. The problem with including novice wheelchairdependent subjects is that there are not many subjects at that stage of rehabilitation who are willing to participate. As a consequence, a subject group will be very heterogeneous, and it will be virtually impossible to create test conditions that will be comparable for all subjects. Therefore, it was decided to study able-bodied subjects without any experience in wheelchair propulsion. This implies that results hold for individuals with an intact (upper) body and may not be fully transferable to (novice) wheelchair-dependent individuals since e.g. loss of neuromuscular functions is likely to influence the learning process of wheelchair propulsion. AIM OF THIS THESIS The understanding of motor learning in the context of rehabilitation is still limited but clearly of theoretical as well as clinical importance. The learning process of wheelchair propulsion is a good opportunity to study motor learning of a relevant and novel gross motor task. Furthermore, knowledge about motor skill learning is important for an effective and successful rehabilitation process (Gonzalez et al. 2001). Since not many studies are yet available on biophysical aspects of learning gross motor tasks, the first step in this thesis is to investigate what adaptations take place over time due to systematic practicing a motor task without receiving any extrinsic (feedback) information. Therefore, the first aim of the present thesis is to study possible changes in wheelchair propulsion technique/coordination, in association with gross mechanical efficiency, over time due to a learning process. The second aim is to define optimal conditions for the learning process such as instructing them to direct the force mechanically more effectively, to use different stroke patterns, and performing under different forms of task complexity/ diversity. 9

10 Chapter 1 THESIS OUTLINE In chapters 2 to 4 the adaptations that take place over a shorter and longer term are described. In chapter 2 the effect of a 3-week practice period (3 times a week), with a low intensity and short duration, on propulsion technique (force direction, timing, inter-cycle variability) and mechanical efficiency was studied. The hypothesis of this study was that improvements in gross mechanical efficiency and propulsion technique occur by practicing hand rim wheelchair propulsion over 3 weeks. Chapter 3 focused on changes in propulsion technique and mechanical efficiency during the initial seconds/minutes of the learning process of completely novice subjects. It was expected that certain propulsion technique variables, e.g. the effective force direction, already change during the first seconds/minutes of practice. This short-term study was extended with electromyography and kinematics measurements to get an indication of changes in muscle activity patterns and co-contraction and the movement pattern during the learning process, which is described in chapter 4. Given the large number of muscles around the shoulder, movements can be conducted with different sets of active muscles. Early in the learning process, muscles could be linked into a muscle synergy via muscle coactivity (Bernstein 1967). The purpose of the experiment of chapter 4 was to analyze adaptations in kinematics and muscle activity/co-contraction during the initial phase of learning. The hypothesis was that muscle coactivity is initially high and will decrease with skill learning when limb stiffness is reduced. A possible decrease in muscle co-contraction could explain an increase in mechanical efficiency. Chapters 5 to 7 concentrate on the optimization of the learning process and thus on the understanding of effects of some of the boundary conditions. In chapter 5 this is done by letting the subjects learn to direct the force more tangentially with help of visual feedback on a computer screen. The effect of this more effective force direction on the mechanical efficiency of wheelchair propulsion was studied. In the experiment described in chapter 6 subjects learned to propel the wheelchair with three kinds of stroke patterns, i.e. pumping, semi-circular or single looping over propulsion. The purpose of the study was to investigate whether one stroke pattern is more efficient than another in terms of energy expenditure. It was hypothesized that the semi-circular stroke pattern, in which the hand follows a path below the hand rim in the recovery phase, was the most efficient pattern as was suggested in several previous papers. Finally, chapter 7 focused on the effect of task complexity (i.e. practicing on a stationary wheelchair ergometer, a motordriven treadmill or on a wheelchair track) on mechanical efficiency and propulsion technique during the learning process of wheelchair propulsion. The assumption 10

11 Chapter 1 was that inexperienced able-bodied wheelchair users would achieve a larger improvement in gross mechanical efficiency and propulsion technique when realworld conditions are simulated more closely, i.e. when the task is more diverse and complex. 11

12 Chapter 2 Wheelchair propulsion technique and mechanical efficiency after 3-weeks of practice 12

13 Chapter 2 ABSTRACT Differences in gross mechanical efficiency between experienced and inexperienced wheelchair users may be brought about by differences in propulsion technique. The purpose of this experiment was to study changes in propulsion technique (defined by force application, left-right symmetry, inter-cycle variability and timing) and gross mechanical efficiency during a 3-week wheelchair practice period in a group of novice able-bodied non-wheelchair users. Subjects were randomly divided over an experimental group (N = 10) and a control group (N = 10). The experimental group received a 3-week wheelchair practice period (3. wk -1, i.e. 9 practice trials) on a computer-controlled wheelchair ergometer while the control group only participated in trial 1 and 9. During all 9 practice trials propulsion technique variables and mechanical efficiency were measured. No significant differences between the groups were found for force application, left-right symmetry and inter-cycle variability. The cycle frequency and negative power deflection at the start of the push phase diminished significantly in the experimental group in contrast to the control group (p < 0.05). Work per cycle, push time, cycle time and mechanical efficiency increased. The practice period had a favorable effect on some technique variables and mechanical efficiency, which may indicate a positive effect of improved technique on mechanical efficiency. Although muscle activation and kinematic segment characteristics were not measured in the present study, they may also impact mechanical efficiency. No changes occurred over time in most force application parameters, left-right symmetry and inter-cycle variability during the 3-week practice period, however, these variables may change on another time scale. 13

14 Chapter 2 INTRODUCTION Many lower-limb disabled subjects depend upon a wheelchair for their mobility. Therefore, training and learning of hand rim wheelchair propulsion are essential in the process of rehabilitation. Novice (recently injured) wheelchair users have to learn a completely new motor task for the purpose of ambulation. According to Sparrow (1983) the motor performance of novices is relatively inefficient even though they may perform at a rate optimal to their stage of learning. With practice, the movement pattern will be refined to approximate more closely that which is mechanically and physiologically optimal within the constraints of the task (Sparrow 1983). Tuller et al. (1982) have shown that a beginner learns a skill by freezing out some of the free variation of the body. As skill increases, the beginner will release the ban on the degrees of freedom. It can be expected that wheelchair-dependent subjects (WCD), being more experienced in manual wheelchair propulsion, have a higher gross mechanical efficiency (i.e. a higher ratio between power output and energy expenditure) compared to novice able-bodied subjects (ABS). They will probably also differ in propulsion technique. Studies in this realm are, however, scarce and cross-sectional in nature. Results on a 30 s hand rim wheelchair sprint test did not indicate superior results for WCD over ABS concerning power output and force application, although some differences in kinematics seemed to exist (Veeger et al. 1992a). More important in the light of the present study are studies comparing WCD with ABS during submaximal tests (Knowlton et al. 1981; Tahamont et al. 1986). They found that WCD had a significantly higher net mechanical efficiency than ABS. The biomechanical differences between WCD and ABS, like stroke length, were suggested to be possible influencing factors on mechanical efficiency (Knowlton et al. 1981). Although the subjects in the above-mentioned studies were able bodied, they are generally not fully inexperienced. The inclusion criterion for subjects in the current study was that they had not been using a wheelchair in any prior instance. Above that, cross-sectional studies do have clear limitations. However, results may indicate that increasing expertise can lead to shifts in technique and possibly to a gradual increase of overall mechanical efficiency. Both physiological adaptations and improved propulsion technique are assumed to underlie shifts in mechanical efficiency during practice. Identifying the technique aspects of wheelchair propulsion related to mechanical efficiency is important both theoretically and practically. Learning of hand rim wheelchair propulsion seems to provide a valid and interesting model to study motor learning phenomena in adult individuals (Amazeen et al. 1999). Currently there is little research pertaining to propulsion technique factors associated with the learning of wheelchair propulsion. 14

15 Chapter 2 Ultimately, if changes in technique variables improve the mechanical efficiency of wheelchair propulsion, these findings would enable novice wheelchair-dependent subjects to optimize wheelchair performance much more effectively from the start of the rehabilitation (i.e. learning) process onwards. This is particularly important because hand rim wheelchair propulsion is a way of locomotion with a low gross mechanical efficiency. Gross mechanical efficiency of wheelchair propulsion rarely exceeds 11% and is much lower than in arm cranking (16%) (Martel et al. 1991; Powers et al. 1984) or cycling (18-23%) (Coyle et al. 1992). As a consequence, hand rim wheelchair propulsion is associated with a high physical strain in daily life (Janssen et al. 1994) and leads most likely to a high mechanical load on the upper extremity. The latter may lead to a high prevalence of overuse injuries in shoulder and wrist (Boninger et al. 1997). It is important to note the difference between training and learning. As mentioned before, shifts in mechanical efficiency can take place due to physiological adaptations or as a consequence of improved propulsion technique. Generally, in training both physiological adaptations and learning responses (i.e. an improved propulsion technique) will take place. If one wants to isolate changes in propulsion technique and ME, physiological adaptations as a consequence of training have to be excluded. Therefore, the learning protocol has to be at a very low intensity and duration, and with a limited frequency. Clearly, intensity should be less than the general training guidelines that are suggested by the ACSM (ACSM 1990). The process of adaptation during wheelchair training or learning has not been described in detail. Woude et al. (1999) and Dallmeijer et al. (1999b) performed a 7-week wheelchair training process in 10 ABS on a motor-driven treadmill. They found substantial effects on performance capacity and timing parameters, but no changes in characteristics of force application and mechanical efficiency in comparison to a control group. Kemenade et al. (1999) studied the effects of the rehabilitation process on mechanical efficiency and technique. They found a tendency for a larger mechanical efficiency and a smaller outwardly directed force after approximately one and a half years of rehabilitation. Lack of significant results for mechanical efficiency in these studies could be due to a too small group size (Dallmeijer et al. 1999b; Kemenade et al. 1999; Woude et al. 1999) and/or great range of lesion levels of the subjects (Kemenade et al. 1999). Wheelchair propulsion is a bilateral, cyclical activity and little is known about the nature and extent of variability that exists among the movement pattern of a continuous sequence of push cycles in general (Rao et al. 1996). Variability, or lack thereof, in a given movement parameter is often used as an index of skilled performance (Newell et al. 1993). The typical finding is that movement variability 15

16 Chapter 2 reduces as function of practice and increments of skill (Darling et al. 1987; Vereijken et al. 1997). Variability in the motor system can be examined at several levels. The variations may be related to force production, which in turn will be influenced by variations in the muscle activation and timing, excitability of motor neurons, and command signals from higher nervous centers (Carlton et al. 1993). Since regulation of force is a critical function of the motor system, possible changes in force application parameters due to skill acquisition will be used in the present study. The (a)symmetry of the bilateral force production in time and space determines the direction of coasting. Every small correction that has to be made to keep the wheelchair in a straight path leads to extra energy loss. It can be hypothesized that novice individuals produce a less stable coasting line and thus require more corrections, which is suggested to lead to asymmetric technique parameters. Bilateral symmetry of the elbow movement pattern was found in WCD by Goosey and Campbell (1998a) and Jones et al. (1999). However, it is unknown whether novice subjects display similar stable patterns of bilateral symmetry during steady state submaximal wheelchair propulsion along a straight line. In the current study, the following hypothesis was tested: an improvement in propulsion technique (i.e. a more effective force application and timing, more bilateral symmetry and less inter-cycle variability) and improved mechanical efficiency occur as a function of practicing hand rim wheelchair propulsion over a 3-week practice period. METHODS Subjects After having given written informed consent, 20 able-bodied male subjects participated in the study. Criteria for inclusion were: male, no prior experience in wheelchair propulsion, absence of any medical contra-indications. Subject characteristics are listed in Table 1. The protocol of the study was approved by the Medical Ethical Committee. Protocol Subjects were randomly divided over an experimental group (N = 10) and a control group (N = 10). The experimental group received a 3-week wheelchair practice period (3. wk -1, 9 practice trials) on a computer-controlled wheelchair ergometer. Every trial comprised two four-minute exercise blocks at two different levels of external power output (block 1: 0.15 W. kg -1 and block 2: 0.25 W. kg -1 ) at a velocity of 1.11 m. s -1. Two minutes of rest preceded each exercise block. Visual 16

17 Chapter 2 feedback, on a 15-inch computer screen in front of the subject, was used to give the subjects feedback on the actual velocity of the left and right side as well as on the required velocity (1.11 m. s -1 ). The velocity was made visible by a line which had to be kept - on average - at certain points indicating a velocity of 1.11 m. s -1 on the left and right side and had to be kept horizontal (i.e. symmetric for the left and right side). Force application, timing parameters, bilateral symmetry, inter-cycle variability and mechanical efficiency were measured every trial during the 3-week period. Measuring variables every trial, instead of only during a pre- and post-test, is necessary to develop a description of the learning curve and to determine at which time variables stabilize i.e. do not improve anymore. The control group participated in the first and last trial only. Although the experimental group and the control group were asked not to change the normal daily routine during the 3-week interval, it was not possible to control this aspect completely. Wheelchair ergometer All trials were performed on a custom-built wheelchair ergometer. This ergometer is a stationary, computer-controlled wheelchair simulator that allows for direct measurement of propulsive torque around the wheel axle, propulsive force applied on the hand rims and resultant velocity of the wheels (Niesing et al. 1990). Wheelchair ergometer dimensions were individually adjusted such that when sitting upright with the hands on the rim top the subject s shoulder was directly above the wheel axle and the elbow angle was approximately 110 with 180 being full extension. Wheel camber was set at 4º. Seat angle and backrest were set at 5º to the horizontal and 15º to the vertical axis, respectively. Ergometer data were collected each exercise block, during the last minute, with a sample frequency of 100 Hz. Torque, forces and velocity were low-pass filtered (cut off frequency of 10 Hz, recursive second order Butterworth filter). Because of resonance in the system the medio-lateral force component was filtered at a lower cut-off frequency (5 Hz, fourth order Butterworth). Propulsion technique Variables were calculated as mean over the whole last minute or as mean and peak values over each of the pushes of the last minute. The push phase was defined as the period the hand exerted a positive torque on the hand rim (Figure 1). From the measured torque (M), wheel velocity (V w ) and wheel radius (r w ), the power output was calculated: 17

18 Chapter 2 Power output = M. V w. r w -1 (W) (1) Mean total power output was the sum of the power output for the left and right wheel and was calculated over one minute. The negative deflections or dips at the start of the push phase and at the end of the push phase were determined from the power output curve. The negative deflections or dips at the start of the push phase and at the end of the push phase were the most negative power output values respectively at the start and the end of the push (Figure 2). From the mean power output and the cycle frequency (in Hz) the work per push cycle was calculated: Work per cycle = Mean power output. frequency 1 (J) (2) Force application Force parameters were calculated as mean and peak values over each of the pushes over the last minute of an exercise block. The positive forces applied with the hand on the rim were defined as follows: Fx: horizontally forward, Fy: horizontally outward, and Fz: vertically downward (Figure 3). From force components Fx, Fy and Fz, total force applied on the hand rim (Ftot) was calculated according to: Ftot = (Fx 2 + Fy 2 + Fz 2 ) (N) (3) The effective force (Fm) was calculated from torque (M) and hand rim radius (r r ), according to: Fm = M. r r -1 (N) (4) The fraction of effective force on the hand rims (FEF) was calculated from equations 3 and 4 for each workload and expressed as a percentage: FEF = Fm. Ftot (%) (5) Because of technical problems with one of the force transducers on the left-hand side, it was not possible to determine reliable values of Fy on that side. To examine whether the FEF characteristics of the left-hand side are comparable with the right hand side over the trials an alternative FEF was calculated for both sides for only five subjects per group, namely: FEFalt = (M. r r -1 ). ( (Fx 2 + Fz 2 )) (%) (6) 18

19 Chapter 2 Finally, the slope of the line between the start of the push and the peak torque in the push was determined (slope) (Figure 1). Timing The cycle frequency was determined from the torque signal and defined as the number of complete pushes per minute. The timing parameters cycle time and push time were also determined from the torque signal of the ergometer (Figure 1). The push time was defined as the amount of time that the hand exerted a positive torque on the hand rim. The cycle time was defined as the period of time from the onset of one push phase to the onset of the next. The push time was also expressed as a percentage of the cycle time (%push time). Bilateral symmetry The difference between the dominant and non-dominant hand for the maximal value of FEFalt, mean torque, power output, timing variables (frequency, push time, cycle time and %push time) and the slope was determined as measures of bilateral symmetry during wheelchair propulsion. The symmetry between the timing of the right and left hand was also defined from the torque signal as the right-left difference between the start time of the push (Right-Left push) and as the right-left difference in time of the peak (Right-Left peak) (Figure 1). Inter-cycle variability The inter-cycle variability was determined for each subject for all consecutive push cycles during the 60-s measurement period for the push time, cycle time, %push time, power output, FEF, torque, the negative power output dips at the start and end of the push and the velocity. The mean and standard deviation (SD) of the variables were calculated over all push cycles in the measurement period. From the mean and SD the coefficient of variation (CV) was calculated by the formula: CV = SD. mean (%) (7) Gross mechanical efficiency Oxygen uptake ( V O2 [l. min -1 ]) was continuously measured during the whole test with an Oxycon Champion (Jaeger, Germany). Calibration was performed before each test with reference gas mixtures. Averaged values of 10 s were sampled. To obtain an indication of the gross mechanical efficiency (ME) of wheelchair propulsion, the ratio power output/ energy expenditure was calculated according to: 19

20 Chapter 2 ME = Mean power output. Energy expenditure (%) (8) where the energy expenditure is calculated from the oxygen uptake and the respiratory exchange ratio according to Garby and Astrup (1987). The mean power output was calculated over the last minute of each exercise block. Energy expenditure was calculated over the last two minutes of each exercise block in order to minimize errors inherent in the measurement system. Statistics To examine possible differences in starting levels between the two subject groups an Independent t-test was performed. An ANOVA for repeated measurements, with power output (0.15 and 0.25 W. kg -1 ) and trial (1 and 9) as main factors and group (experimental and control) as between subject factor, was applied to detect significant differences for selected parameters. The interaction Trial*Group was considered to be the most important effect since it indicates the differences between the groups over the practice period (trials). Significance level was set at p < 0.05 for all statistical procedures. RESULTS Subjects All subjects completed all trials. Mean age, body mass and height did not differ among the groups (Table 1). No significant differences were found in the starting levels between the experimental group and the control group except in the difference between the dominant and non-dominant hand for the mean torque at the external power output of 0.25 W. kg -1 (p=0.046). Propulsion technique Figure 4 lists the values of the mean power output and the negative power output dips at the start and end of the push. The negative power output dip at the start of the push diminished in both groups over time (for the experimental group from ± 3.52 W at trial 1 to ± 1.75 W at trial 9; for the control group from ± 1.08 W at trial 1 to ± 1.21 W at trial 9; both at 0.25 W. kg -1 ) but with a significantly larger decrease in the experimental group (p = for interaction Trial * Group). The experimental group significantly increased the work per cycle (0.38 ± 0.06 J at trial 1 to 0.54 ± 0.19 J at trial 9, both at 0.25 W. kg -1 ) during the practice period in contrast to the control group (0.39 ± 0.12 J at trial 1 to 0.41 ± 0.14 J at trial 9, both at 0.25 W. kg -1 ) (p = for interaction Trial * Group) (Table 2). The negative power output dips and the work per cycle were significantly larger at the higher levels of external power output. 20

21 Chapter 2 Force application No effect of practice was found on FEF, FEFalt and slope between the groups over the trials (Table 2). The slope was significantly increased at a higher power output. Timing Values of push time and cycle time during the 3-week practice period are visualized in Figure 5. The cycle frequency decreased significantly in the experimental group (62 ± 12 pushes/minute at trial 1 to 46 ± 12 pushes/minute at trial 9, both at 0.25 W. kg -1 ) in contrast to the control group (63 ± 17 pushes/minute at trial 1 to 60 ± 17 pushes/minute at trial 9, both at 0.25 W. kg -1 ) at both external power output levels (p = for interaction Trial * Group)(Table 2). The push time (p = for interaction Trial * Group) and cycle time (p = for interaction Trial * Group) increased significantly in the experimental group compared to the control group. No significant differences were shown for %push time (Table 2). Cycle frequency, push time and %push time were all significantly larger at the external power output of 0.25 W. kg -1 compared to 0.15 W. kg -1. Bilateral symmetry No effect of practice was found for Right-Left push and Right-Left peak. The difference of the timing of the start of the push or peak was at the most 0.01 s. The difference between the dominant and non-dominant hand for the variable push time showed a significant alteration over the practice period between the groups (p=0.040 for interaction Trial * Group). The difference in push time between the dominant and non-dominant hand increased in the experimental group over the trials, although the largest difference was only 6 ms. Inter-cycle variability The variability (SD and CV) of the propulsion technique parameters did not change significantly over time between the groups. Low coefficients of variation were found for the velocity, FEF and cycle time (2-11%); moderately low CV s were found for the mean power output, push time and %push time (12-20%); and high inter-cycle variability was found for the negative power output dips at the start (33-50%) and end (47-75%) of the push. Figure 6 shows the CV s of push time, cycle time, FEFmax and mean power output for both groups over the trials. The push-variability of the torque signal at the right hand side of a subject from the experimental group at trial 1 and trial 9 is visualized in figure 7. This figure demonstrates that the variability did not diminish over the trials and also clearly shows the increase in push time over practice. 21

22 Chapter 2 Gross mechanical efficiency Gross mechanical efficiency over time for both groups is plotted in Figure 8. A significant increase in mechanical efficiency was found for the experimental group (7.45 ± 0.87% at trial 1 to 8.11 ± 0.56% at trial 9, both at 0.25 W. kg -1 ) in contrast to the control group (7.37 ± 0.75% at trial 1 to 7.23 ± 0.90% at trial 9, both at 0.25 W. kg -1 )(p = for interaction Trial * Group). Mechanical efficiency was significantly higher at a higher external power output. Visualization of the results showed that the mechanical efficiency seems to deteriorate in the control group. This deterioration could lead to significant differences between the control group and the experimental group and to the conclusion that the variable improved in the experimental group, while it actually did not. An analysis on the two power outputs and on all nine trials for the experimental group only, showed no other results than those mentioned above. Again a significant improvement of mechanical efficiency over the trials for the experimental group (p = 0.001) was found, suggesting that the significant difference found between the experimental group and the control group was due to an improvement of mechanical efficiency in the experimental group instead of a deterioration in the control group. DISCUSSION During the rehabilitation period persons with (acute) lower-limb disabilities have to learn a novel gross motor task for mobility, i.e. hand rim wheelchair propulsion. A few researchers investigated physiological and/or biomechanical changes during a practice period of a novel gross motor task, such as rowing (Sparrow et al. 1999), crawling (Sparrow et al. 1987) and skiing (Brinker et al. 1982). However, nothing is known of the learning process of manual wheelchair propulsion in biophysical terms. The purpose of this experiment was, therefore, to study the effect of a 3- week wheelchair-practice program on propulsion technique (defined by force application, timing, bilateral symmetry and inter-cycle variability) and mechanical efficiency. The significant increase in mechanical efficiency in the experimental group during the learning program in contrast to the control group, was not in accordance with the results of a 7-week wheelchair training study (Dallmeijer et al. 1999b; Woude et al. 1999). In a (too) small sample of subjects, the training study was unable to support a possible effect of training on mechanical efficiency in the experimental group, despite significant changes in peak oxygen uptake and power output. Kemenade et al. (1999) found a tendency for a larger mechanical efficiency after approximately one and a half years of rehabilitation in persons with spinal cord 22

23 Chapter 2 injury. Besides a training and/or learning effect, this increase in mechanical efficiency could be due to recovery of functions during the rehabilitation process. The small but significant increase in gross mechanical efficiency in the present study (5.54 ± 0.61% at trial 1 to 5.87 ± 0.52% trial 9, both at 0.15 W. kg -1 ; and 7.45 ± 0.87% at trial 1 to 8.11 ± 0.56% at trial 9, both at 0.25 W. kg -1 ) could theoretically not be due to an effect of training because the two exercise blocks were at a low intensity and of a short duration to avoid such an effect (ACSM 1990). The hypothesis, that the practice period probably led to an improvement in propulsion technique and subsequently the activity became less strenuous for the subjects, was thus supported. Therefore, the effect of practice on several propulsion technique variables has to be observed in more detail. An effect of the practice period was found in the negative dip in the power output at the beginning of the push phase. Less negative power was produced over time in the experimental group compared to the control group at the beginning of the push phase. Negative power production will reduce overall performance, since it implies the braking of the wheels. The negative dip is most likely the result of non-optimal coupling technique in which the hands of the subjects had not attained the required tangential velocity of the wheels at the moment of first contact (Veeger et al. 1991a). The motion of the hands at the start of the push occurs outside the visual field, what makes it more difficult to grasp the rims with the same hand velocity compared to the actual wheel velocity. The results showed that, at a low velocity of 1.11 m. s -1, one learns to diminish the braking torque at the start of the push. Less negative power was produced over time at the end of the push phase for both groups, indicating a short-term adaptation. Like in most tasks, it is necessary to maximize concurrently both the forces generated and the effectiveness with which these forces are applied in manual wheelchair propulsion. The effectiveness of the total force vector in association with the effective force component, indicated by FEFmax and FEFmean, increased only with a non-significant few percent and in both the experimental group (80 ± 12% at trial 1 to 84 ± 10% at trial 9) and the control group (81 ± 8% at trial 1 to 83 ± 11% at trial 9). This was in accordance with a 7-week wheelchair training study (Dallmeijer et al. 1999b). No differences in FEF were visible between WCD and ABS in the cross-sectional study on performance and technique during a 30-s sprint test (Veeger et al. 1992a). These findings suggest that the force application during hand rim wheelchair propulsion might change on a short-term, occurring already in the first seconds or minutes of practice. The cycle frequency of hand rim wheelchair propulsion can be varied to a certain extent without affecting the mean velocity. This is in contrast to cycling and arm- 23

24 Chapter 2 cranking, which are more constrained cyclical motions (Woude et al. 1989b). This can be seen in the results of the present study. Three weeks of practice on the wheelchair ergometer led to a significant decrease in cycle frequency while the mean velocity remained the same. Also, significant changes over the trials were seen between the groups for the push time, cycle time and work per cycle. The increments in push time and in the work per cycle are well visualized in figure 7 by respectively the broader peak and the larger surface under the curve. All these variables increased over time in the experimental group in contrast to the control group. This indicates a possible adaptation in segment excursions and velocities and subsequently in muscle contraction characteristics. The 7-week wheelchair training study showed similar results (Dallmeijer et al. 1999b). That study found, using video recordings, also a larger stroke angle, which is the angle between the line from the hand through the wheel axle, relative to the vertical, at the start and the end of the push phase. Since no kinematics were taken into account in the present study a larger stroke angle could not be demonstrated. The changes in stroke angle, cycle frequency and work per cycle appear to be linked (Dallmeijer et al. 1999b). The increase in work per cycle was confirmed with cross-sectional results of Veeger et al. (1992a) on the 30 s wheelchair sprint test. No significant bilateral differences between the groups over time were found except for the variable push time. The difference in push time between the dominant and non-dominant hand decreased in the control group, while it increased in the experimental group. However, our expectations were just the other way around, more bilateral symmetry after practice. On the other hand, steering is not a crucial task element on a stationary wheelchair ergometer in contrast to wheelchair use in real life or on a motor driven treadmill, i.e. bilateral symmetry is not a must on a wheelchair ergometer. Despite that, no essential differences were seen between the dominant and non-dominant side. The apparent symmetry was underlined by a submaximal wheelchair study (Veeger et al. 1992b), in which identical mean values of the power output were found and comparable time series of both power curves. Woude et al. (1998) compared the power production on the right and left hand during a sprint test on a wheelchair ergometer. They found some variance but overall good agreement between the left and right hand side. Goosey and Campbell (1998a) established whether bilateral symmetry exists during wheelchair propulsion in the elbow movement pattern of trained wheelchair racers. The main finding from their study was that as a group (N = 7) there were no significant differences between the left and right arm movement patterns. Jones et al. (1999) did not find any significant bilateral differences in kinetic parameters in a group of 11 subjects with paraplegia. Therefore, it can be concluded that - 24

25 Chapter 2 especially at submaximal exercise levels bilateral symmetry occurs even at the start of a learning process. Small differences between left and right may be explained by hand dominance and the lack of accurate directional information (Woude et al. 1998). As was the case for bilateral asymmetry, the expectation was that the variability would reduce as a function of practice. A high level of push-to-push consistency, i.e. a low variability, is necessary in the execution of effective movement patterns, such as in rowing (Smith et al. 1995). However, after three weeks of wheelchair practice the variability between the pushes was not significantly diminished (figure 6 and 7). The coefficient of variation of different variables varied a lot during the three weeks. The lack of support for the hypothesis might be due to the fact that subjects had to propel in a stationary wheelchair ergometer. Subjects did not have to pay much attention to steering, which normally needs constant attention. Therefore, the subjects could be distracted more easily and consequently more variability occurred. The inter-cycle variability of the power output and the velocity was quite low. This can be partly explained by the fact that the velocity had to be regulated at a mean constant level on the basis of feedback. The large inter-cycle variability of some variables may imply the difficulty to improve these variables and keep them constant during a learning period. One may conclude that bilateral symmetry is dominantly coordinated from the start on, whereas temporal consistency in technique shows strong fluctuations over time and no consistent decrease with practice. Several studies found low inter-cycle variability for kinematic variables in (racing) wheelchair propulsion, suggesting that the upper extremity motion pattern was consistent and repeatable for a single subject (Goosey et al. 1998a; Rao et al. 1996; Sanderson et al. 1985). However, low inter-cycle variability can be expected in these studies with WCD subjects or even wheelchair racers because they are extremely experienced compared to the novice able-bodied subjects in the present study. In a study on the effect of practice on rowing performance no significant change in stroke-to-stroke variation was found, although the authors suggested that there was a trend towards reduced variability in the rowing cycle (Sparrow et al. 1999). Another study showed that biomechanical and performance variables, such as stroke-to-stroke consistency, stroke smoothness and propulsive work consistency, can be used to discriminate accurately between rowers of different skill levels (Smith et al. 1995). Lack of significant differences in force application, bilateral symmetry and intercycle variability between the experimental group and the control group after a 3- week practice period could be due to a too low intensity of the protocol. Under 25

26 Chapter 2 submaximal conditions, technique may be considered less critical to performance. This suggests that differences may be (more) expressed at higher intensities. Effectiveness of force application and gross mechanical efficiency do indeed show some increase with a higher load (Dallmeijer et al. 1998). However, practicing at higher intensities will lead to a training effect, which had to be excluded here. While the gross mechanical efficiency increased in the experimental group compared to the control group, only significant changes in wheelchair propulsion technique were visible for the cycle frequency, push time, cycle time, work per cycle and the negative power dip at the start of the push. Mechanical efficiency can be influenced by the cycle frequency as was stressed by Woude et al. (1989b) and Goosey et al. (2000). Goosey et al. (1998b) stated that lower push rates have been associated with greater pushing economy (defined as oxygen uptake at a given propulsion speed). A high push rate means that the athlete is experiencing many shifts in the deceleration and acceleration and inertial moments of the limb segments, thus influencing muscle activity and co-ordination and subsequently energy cost and efficiency. A previous study (Goosey et al. 1998b) stated the hypothesis that a slower push rate may mean that the athlete is able to apply more force effectively on the hand rim to produce the desired power output with less muscular effort. The present study found a decrease in cycle frequency over the trials for the experimental group. But in contrast to an expected increase in work per cycle and a less negative power dip at the start of the push, this was not accompanied by an increase in FEF, i.e. a more effective force direction. However, changes in FEF due to a practice period may be not that self-evident as expected. Changes in timing parameters, for example cycle frequency, due to learning of a motor skill are typical in literature. The major practice-related adaptation in walking on hands and feet was to use longer and slower strides (Sparrow et al. 1987) while in rowing it was a decreased mean stroke rate over days (Sparrow et al. 1999). It was assumed that participants in both studies learned to produce a more economical rate of muscle contraction. The results of the present study are in agreement with the statement of Sparrow (1999) that the learning of many repetitive gross-motor tasks might be characterized by a longer-slower control mode, i.e. a larger stroke angle/longer push time and cycle time and a decreased cycle frequency. Changes in movement patterns and in muscle activity/timing patterns may lead to alterations in gross mechanical efficiency during a learning process of manual wheelchair propulsion. Since the shoulder-muscle complex offers a wide range of movements, this might result in a great variability in repetitive movements of the upper extremity. In the beginning of skill learning, for example manual wheelchair 26

27 Chapter 2 propulsion, there will be freezing out of some of the free variation of the body, so that it is not allowed into the activity (Tuller et al. 1982). According to this theory, muscles will not be controlled individually but are functionally linked with other muscles via muscle co-activity. Acquiring a skill is essentially trying to find ways of controlling the degrees of freedom and of exploiting the forces made available by the context (Turvey et al. 1982). Later in learning, the restrictions could be relaxed, allowing reductions in co-activity in favor of more specific multi-muscle sequencing. One hypothesis that emerges from this idea is the following: muscle co-activity should decrease with skill learning as degrees of freedom are freed up and limb stiffness is reduced (Spencer et al. 1999). Subsequently this may lead to an improvement in gross ME. The possible reduction in muscle co-activity during the learning process could be easily measured by EMG. Therefore, EMG and kinematics measurements will be useful in future learning studies. CONCLUSION In this study with novice able-bodied subjects a 3-week practice program on a wheelchair ergometer resulted in a significant improvement in gross mechanical efficiency in an experimental group compared to a control group. Timing variables (push time, cycle time and cycle frequency), work per cycle and the negative deflection in the power output curve at the start of the push phase changed also significantly with learning in the experimental group in contrast to a control group. The wheelchair-practice program had a favorable effect on the timing parameters and on the mechanical efficiency. This may indicate a positive effect of the timing parameters on mechanical efficiency. No changes were seen over the trials in the inter-cycle variability, bilateral symmetry and force application variables like the direction of the effective force. It is possible that these variables change in a shorter time span - already in the first seconds or minutes - or on a longer term than the three weeks used in the present study. ACKNOWLEDGEMENT The experimental assistance of Cécile Boot and Stephanie Valk is greatly acknowledged. 27

28 Chapter 2 TABLES Table 1. Mean and SD of the subject characteristics for the control (C) and experimental (EXP) group. P- value: results of independent t-test between group means. C (N = 10) EXP (N = 10) p-value Mean SD Mean SD Age (years) Body mass (kg) Height (cm) Dominant arm - Right: N = 9 N = 10 Table 2. Mean and SD for the technique variables at external power outputs 0.15 and 0.25 W. kg -1, at the beginning (1) and the end (9) of the 3-week practice period for both the experimental (EXP) and control (C) group. Number of subject is 10 for all variables. See text and figures 1-3 for definition of variables. *: p < 0.05, indicates the difference between the groups over the practice period. Trial x Group EXP (0.15 W. kg -1 ) C (0.15 W. kg -1 ) EXP (0.25 W. kg -1 ) C (0.25 W. kg -1 ) Mean SD Mean SD Mean SD Mean SD Work per cycle (J) 1 * FEFmax (%) FEFmean (%) Slope (Nm/s) Frequency (pushes/min.) 1 * Push time (s) 1 * Cycle time (s) 1 * %Push time (%)

29 Power output (W) Torque (Nm) Chapter 2 FIGURES Torque signal right (-) and left (.-). Ri-Le peak Slope 0-5 Push time Ri-Le push Cycle time Sample Figure 1. Definition of the variables push time, cycle time, slope and the right-left difference of the timing of the peak (Ri-Le peak) and push (Ri-Le push). 50 Power output signal PnegS PnegE Sample Figure 2. Illustration of the definition of the dips of negative power output at the start (PnegS) and the end (PnegE) of the push. 29

30 Power output (W) Chapter 2 Fx M Fz Ftot Fm Figure 3. Illustration of the torque and force components exerted on the hand rim * 0 POmean (0.15 W/kg) POmean (0.25 W/kg) PnegS (0.15 W/kg) PnegS (0.25 W/kg) PnegE (0.15 W/kg) PnegE (0.25 W/kg) EXP 9 - EXP 1 - C 9 - C Figure 4. Mean and standard deviation of the power output (POmean) and the dips of negative power output at the start (PnegS) and end (PnegE) of the push, at trial 1 and 9 for external power output 0.15 W. kg -1 and 0.25 W. kg -1 for the experimental (EXP) and control (C) group. * = significant Trial * Group effect at p <

31 CV (%) Time (s) Chapter 2 Cycle time and push time * * C - Cycle time 0.15 W/kg EXP - Cycle time 0.15 W/kg C - Cycle time 0.25 W/kg EXP - Cycle time 0.25 W/kg C - Push time 0.15 W/kg EXP - Push time 0.15 W/kg C - Push time 0.25 W/kg EXP - Push time 0.25 W/kg C C Trial Figure 5. Mean and + or standard deviations of the push time (PT) and cycle time (CT) for the experimental (EXP) compared to the control (C) group at external power outputs 0.15 and 0.25 W. kg -1. * = p < 0.05 for interaction effect Trial * Group. Coefficient of variation (%) Cycle time (C) Cycle time (EXP) Push time (C) Push time (EXP) FEFmax (C) FEFmax (EXP) Mean Power Output (C) Mean Power Output (EXP) 2.0 1C C Trial Figure 6. Impression of the fluctuating mean coefficient of variation (%) for the variables push time, cycle time, effective force production (FEFmax) and mean power output during three weeks of practice (9 trials) for the experimental (EXP) group compared to a control (C) group at an external power output of 0.25 W. kg

32 Gross mechanical efficiency (%) Torque (Nm) Torque (Nm) Chapter 2 Sample Sample Figure 7. Example of the push-variability during the first 15 s of trial 1 (left picture) and the last 15 s of trial 9 (right picture) i.e. after 3 weeks of practice, both at an external power output of 0.25 W. kg -1. Gross mechanical efficiency (%) * C (0.15 W/kg) EXP (0.15 W/kg) C (0.25 W/kg) EXP (0.25 W/kg) C C Trial Figure 8. Significant increase in gross mechanical efficiency (mean and standard deviation) over the trials for the experimental (EXP) group compared to a control (C) group at external power output levels 0.15 and 0.25 W. kg -1. p < 0.05 for interaction effect Trial * Group. 32

33 Chapter 3 Adaptations in physiology and propulsion techniques during the initial phase of learning manual wheelchair propulsion 33

34 Chapter 3 ABSTRACT The purpose of this study was to analyze adaptations in gross mechanical efficiency and wheelchair propulsion technique in novice able-bodied subjects during the initial phase of learning hand rim wheelchair propulsion. Nine able-bodied subjects performed three 4-minute practice blocks on a wheelchair ergometer. The external power output and velocity of all blocks was respectively 0.25 W. kg -1 and 1.11 m. s -1. Gross mechanical efficiency, force application, timing, and inter-cycle variability were measured. No change in gross mechanical efficiency was found. However, a decrease in cycle frequency was seen, which was accompanied by an increase in work per cycle and a decrease in percentage push time. The increase in work per cycle was associated with a higher peak torque. No changes in inter-cycle variability were visible over time. The timing variables changed already during the initial phase of learning manual wheelchair propulsion. However, for other variables, such as force production, gross mechanical efficiency and inter-cycle variability, a longer practice period, i.e. even months/years, might be necessary to induce a change. The effective force direction seemed to be optimized from the start of the learning process onwards. 34

35 Chapter 3 INTRODUCTION Training and learning are essential in the process of rehabilitation. Novice (recently injured) wheelchair users in the process of rehabilitation have to learn a complete set of new motor patterns of the upper extremities and trunk for the purpose of propulsion and activities of daily living. Due to the way the task of wheelchair propulsion has to be executed - in terms of segmental rotations, coupling of the hand to the rotating rims et cetera - hand rim wheelchair propulsion has a low gross mechanical efficiency. It has been suggested that a learner has to discover an appropriate movement pattern and has to find the optimal pattern in terms of reproducibility and/or efficiency of energy expenditure when confronted for the first time with such a novel motor task (Almasbakk et al. 2001; Sparrow 1983). This raised the overall question, which learning processes and adaptations take place over time as a consequence of practicing a completely novice cyclic gross motor task like manual wheelchair propulsion? A previous study with able-bodied subjects showed that a 3-week wheelchairpractice program (two 4-min. exercise blocks at a low intensity, 3 times a week) had a favorable effect on timing parameters (cycle frequency, push time and cycle time) and gross mechanical efficiency (Groot et al. 2002), Chapter 2). However, no changes in force application and inter-cycle variability occurred during the 3-week learning program. Dallmeijer et al. (1999b) found similar results in a 7-week wheelchair-training study (30 min. exercise at 50-70% heart rate reserve, 3 times a week), changes in timing parameters but no alterations in force application. Because regulation of force is a critical function of the motor system, possible changes in force application due to skill acquisition could occur. Based on the findings of the 3- (Groot et al. 2002), Chapter 2) and 7-week (Dallmeijer et al. 1999b) studies and on cross-sectional wheelchair literature (Veeger et al. 1992a), possible learning-based changes in force application and inter-cycle variability can be either long-term adaptations, i.e. the 3-week learning program and even the 7- week training period were too short for improving these variables, or could be short-term adaptations, occurring already during the first seconds or minutes of practice. Therefore, it was suggested in Groot et al. (2002b, Chapter 2) that force application does adapt partly at a short-term basis as well as in a much more gradual pattern over the long term. The present study will focus on the suggested short-term changes to understand which changes in physiology and propulsion technique take place during the first seconds / minutes of the wheelchair-learning process. Therefore, the inclusion criterion for subjects in the current study was that they had not been using a wheelchair in any prior instance. Since nothing is known about the initial motor learning processes of wheelchair propulsion, it was chosen 35

36 Chapter 3 to start simple and well controlled with a homogeneous subject group who are able to propel the wheelchair at a standardized power output and velocity. Therefore, able-bodied subjects were included since these standardizations and homogeneity would not be possible with wheelchair-dependent subjects at the early stages of rehabilitation. Although the results might not be completely transferable to people with limited functions, especially when these concern the upper trunk and arms, it will give insight in adaptations in propulsion technique and mechanical efficiency that take place due to a natural practice period in general. In order to understand the processes underlying the initial learning of hand rim wheelchair propulsion the purpose of the present study was to study the short-term adaptations in wheelchair-propulsion technique (defined by force application, timing and intercycle variability) and gross mechanical efficiency in completely novice able-bodied subjects in the initial 12 minutes of the learning process on a computer-controlled wheelchair ergometer. It was expected that 1) the mechanical efficiency would increase during the practice period; 2) an increase in the effective force direction would occur already in the first seconds/minutes of practice (Groot et al. 2002b, Chapter 2); A possible increase in mechanical efficiency could be due to 3) an improvement in the timing variables, as was found for the 3-week learning study (Groot et al. 2002b, Chapter 2), or 4) a decrease in inter-cycle variability since the typical finding is that movement variability reduces as a function of improvement of skill (Darling et al. 1987; Vereijken et al. 1997). METHODS Subjects After having given written informed consent, 9 able-bodied male subjects participated in the study. Criteria for inclusion were: male, no prior experience in wheelchair propulsion, absence of any medical contra-indications. The mean age was 24.0 years (SD = 4.8), mean body mass was 76.4 kg (SD = 8.0) and mean height was 1.82 m (SD = 10.2). The dominant hand for all subjects was the right hand. The protocol of the study was approved by the Medical Ethical Committee. Design Without prior familiarization, subjects performed three 4-min. submaximal practice blocks on a computer-controlled wheelchair ergometer. The external power output of all blocks was 0.25 W. kg -1 and the velocity was 1.11 m. s -1. These submaximal levels of power output and velocity were chosen to be able to compare the results of this study with previous studies (Groot et al. 2002, Chapter 2; Groot et al. 36

37 Chapter a, Chapter 5; Veeger et al. 1992c) and to exclude an effect of training or fatigue. Two minutes of rest preceded each exercise block. Visual feedback on the actual velocity, presented on a computer screen in front of the subject, was used by the subject to keep the velocity of the wheels at a constant level of 1.11 m. s -1 on average in a natural manner (Groot et al. 2002b, Chapter 2). The consequence of practice on force application, timing and inter-cycle variability were determined for the right side only. Wheelchair ergometer The practice blocks were performed on a custom-built wheelchair ergometer. This ergometer is a stationary, computer-controlled wheelchair simulator that allows for direct measurement of propulsive torque around the wheel axle, the 3-D vector of the propulsive force applied on the hand rims and resultant velocity of the wheels (Niesing et al. 1990). Wheelchair ergometer dimensions were individually adjusted according to a standardized protocol described elsewhere (Groot et al. 2002b, Chapter 2). Ergometer data were collected with a sample frequency of 100 Hz during the first practice block from (T1) and from minutes (T2). In the second and third practice block a 15 s data set was collected from minutes (respectively T3 and T4). Torque, forces and velocity were low-pass filtered (cut off frequency of 10 Hz, recursive second order Butterworth filter). Because of resonance in the system the medio-lateral force component was filtered at a lower frequency (5 Hz, fourth order). Gross mechanical efficiency Oxygen uptake ( V O2 [l. min -1 ]) was continuously measured during the whole test with an Oxycon Champion (Jaeger, Germany). Calibration was performed before each test with reference gas mixtures. Averaged values of 10 s were sampled. The gross mechanical efficiency (ME) of wheelchair propulsion was calculated according to: ME = Mean power output. Energy expenditure (%) (1) where the energy expenditure is calculated from the oxygen uptake and the respiratory exchange ratio according to Garby and Astrup (1987). The mean power output was calculated over the last 30 s of each exercise block. Energy expenditure was calculated over the last two minutes of each exercise block. 37

38 Chapter 3 Force application Variables were calculated as the averaged mean and / or peak values over the number of completed pushes of each 15 s period. The push is defined as the period that the hand exerted a positive torque on the hand rim (Figure 1). From the measured torque and wheel velocity, the power output was calculated: Power output = M. V w. r w -1 (W) (2) Where: M = torque on the hand rim, V w = velocity of the wheel, r w = wheel radius. Mean total power output was the sum of the power output for the left and right wheel and was calculated over all completed pushes in the 15 s periods. The positive forces applied with the hand on the rim were defined as follows: Fx: horizontally forward, Fy: horizontally outward, and Fz: vertically downward. From force components Fx, Fy and Fz, total force applied on the hand rim (Ftot) was calculated according to: Ftot = (Fx 2 + Fy 2 + Fz 2 ) (N) (3) The effective force (Fm) was calculated from torque (M) and hand rim radius (r r ), according to: Fm = M. r r -1 (N) (4) The fraction of effective force on the hand rims (FEF), by definition the ratio between the magnitude of the total force applied and the effective or tangential component, was calculated from equations 3 and 4 and expressed as a percentage: FEF = Fm. Ftot (%) (5) FEF was expressed as an average (FEFmean) and maximal (FEFmax) value during the push phase. A low FEF generally indicates a more downward direction of the total force vector, i.e. a deviation from the effective force (Fm) (Veeger et al. 1992c). Negative deflections or dips were calculated from the power output curve. The negative dips were the most negative power output values respectively before and after the push phase (Figure 1). From the mean power output and the cycle frequency (in Hz) the work per push cycle was calculated: Work per cycle = power output. frequency 1 (J) (6) 38

39 Chapter 3 Finally, the slope of the line between the start of the push and the peak torque was determined (Figure 1) to give an indication of how the peak torque is built up over time. Timing The cycle frequency was determined from the 15 s data set of the torque signal and expressed as the number of complete pushes per minute. The timing parameters cycle time and push time were also determined from the torque signal of the ergometer (Figure 1). The push time was defined as the amount of time that the hand exerted a positive torque on the hand rim. The cycle time was defined as the period of time from the onset of one push phase to the onset of the next. The push time was also expressed as a percentage of the cycle time (%push time). Inter-cycle variability To determine the variability of the force application and timing parameters the coefficient of variation was calculated. The mean and standard deviation (SD) were calculated over all cycles in the measurement period. From the mean and SD the coefficient of variation (CV) was calculated by the formula: CV = SD. mean (%) (7) The CV was determined for each subject for all consecutive push cycles during the 15 s measurement periods for the force application variables: negative power output dips before and after the push phase, FEFmax, FEFmean, slope, push time, cycle time, percentage push time. Statistics To evaluate a possible learning effect over the 12 minutes practice period, the changes over the four measurement times, namely T1 ( minutes of the first block) and T2, T3 and T4 (respectively minutes of exercise block one, two and three), were analyzed, with the exception of the gross mechanical efficiency. The latter was analyzed for T2, T3 and T4 only. An ANOVA for repeated measurements, with measurement time (T1, T2, T3 and T4) as main factor, was applied to detect significant differences over time for selected parameters. A post-hoc Tukey was applied to determine which time blocks differed significantly from each other. Significance level was set at p < 0.05 for all statistical procedures. 39

40 40 Chapter 3 RESULTS All subjects performed the three submaximal exercise blocks without any problem. Due to the complete inexperience with this arm task, some subjects felt some weak muscle fatigue. Gross mechanical efficiency The 12 minutes of practice did not lead to a change in the gross mechanical efficiency over time (p = 0.82) (Table 1). Force application No significant differences over time were found for the force application variables, except for the peak torque signal. The peak torque increased significantly over time (p=0.02)(table 1), although the mean torque did not (p=0.07). A significant difference in the peak torque was found between T1 and T4, indicating a slight change over time. The mean power output and the negative deflections in the power output curve before and after the push did not show any significant change over the 12 minutes period (Table 1). The fraction effective force (FEF) was calculated for 8 subjects due to problems with Fy of one of the subjects. Since the FEF did not change over time (Table 1), the FEF values during the first 15 s of practice (before T1) were visualized push by push as group means. Although, the first pushes were not yet at the right velocity and, therefore, external power output, it seems that novice subjects immediately reach a FEF of 70-80% (Figure 2). No learning effect was found for the variable slope (Table 1). The work per cycle increased significantly over time, with the largest increase between T2 and T3 (Table 1). Timing By definition the cycle frequency lowers, given the shift in work per cycle and the constant power output over time (T1: 61 ± 12 pushes/minute T2: 57 ± 12 pushes/minute T3: 53 ± 15 pushes/minute T4: 51 ± 13 pushes/minute)(p = 0.00). The push time did not change significantly over time (Figure 3), while the cycle time (Figure 3) and the percentage push time did (T1: 36 ± 7 %push time T2: 34 ± 8 % push time T3: 33 ± 8 % push time T4: 32 ± 8 % push time)(p = 0.05). Inter-cycle variability FEFmax, FEFmean, cycle time, push time and percentage push time showed a relatively low coefficient of variation (<10%). Slope showed a moderate inter-cycle variability (ranged between 15-21%). A high inter-cycle variability was found for

41 Chapter 3 the negative power output dips before and after the push phase (respectively 26-45% and 45-59%). A significant increase in inter-cycle variability over the practice period was found for the push time (T1: 5.92 ± 2.10 % T2: 6.50 ± 1.94 % T3: 5.79 ± 1.56 % T4: 8.63 ± 4.82 %)(p = 0.03) and the negative power output dip before the push phase (T1: ± 7.53 % T2: ± % T3: ± % T4: ± %)(p = 0.00). DISCUSSION Although the results of the present study with able-bodied subjects are not completely transferable to novice wheelchair-dependent subjects with disabilities of trunk and/or upper extremity, this well controlled study gives a good indication about which adaptations do take place during the first seconds/minutes of the learning process of manual wheelchair propulsion. The few complaints of muscle fatigue at the end of testing could probably not be avoided due to the complete inexperience of the subjects regarding wheelchair propulsion and cyclic arm exercise in general. Mechanical efficiency The most important change in learning a cyclic gross motor skill is an improvement in gross mechanical efficiency, i.e. a reduction of energy cost, since the mechanical efficiency is generally suggested to be an indicator for a more refined and optimized movement pattern (Sparrow 1983). Previous studies demonstrated a higher mechanical efficiency for experienced wheelchair-dependent subjects compared to less experienced able-bodied subjects (Knowlton et al. 1981; Tahamont et al. 1986). In contrast to what was hypothesized, in the present study no improvement of the gross mechanical efficiency was found over time. A practice period of 12 minutes seems to be too short to show an effect of practice on the mechanical efficiency. At the end of the practice period the task was still fairly new for the novice wheelchair users and they were probably still exploring this new way of ambulation, trying different strategies. The increase in the intercycle variability during the practice period, for the push time and the negative dip before the push, could be an indication for this exploration phase. The mechanical efficiency is dependent upon physiological and technique factors. The lack of change in the mechanical efficiency was expected from a physiological viewpoint. On the other hand, although no difference was found in the mechanical efficiency over time, adaptations in force application, timing and/or variability in the execution of the task could still have taken place during the 12 minutes of practice. 41

42 Chapter 3 Force application The fraction effective force did not change during either a 3-week learning study (Groot et al. 2002), Chapter 2) or a 7-week training study (Dallmeijer et al. 1999b). Since there were also no significant differences in FEF between experienced and less experienced subjects during wheelchair sprinting (Veeger et al. 1992a), it could be expected that the fraction effective force initially changes on a short-term, within seconds or minutes. The results of the present study showed that subjects apply the force in a consistent way from the start of the novel task onwards and that the fraction effective force did not change during the 12 minutes of practice. Previous studies stated that force direction is based on optimization of cost and effect (Groot et al. 2002a, Chapter 5; Rozendaal et al. 2000; Veeger 1992). It seems that novice wheelchair users were able to find this optimum right from the start of this novel gross motor task. Since a feedback-based learned fraction effective force of around 100% does not improve the mechanical efficiency (Groot et al. 2002a, Chapter 5), this might not be the most important variable to pay attention to during the learning process. The negative dips in the power output curve before and after the push phase did not diminish during the practice period. Negative power production will reduce overall performance, since it implies braking. The dip before the push is possibly the result of coupling of the hands of the subject to the rim, in which the hands had not attained the required tangential velocity of the wheels at the moment of first contact (Veeger et al. 1992c). Novice able-bodied subjects do not seem to be able to incorporate this new movement in their motor system within 12 minutes. A longer practice period appeared to lead to significant reduction of negative work in the dip before the push as was shown by the results of the 3-week practice study (Groot et al. 2002b, Chapter 2). An even longer practice period, i.e. more than three weeks, might be necessary to induce a significant improvement in the negative dip after the push. Timing variables The timing variables changed remarkably during the short practice period. The cycle frequency decreased significantly with 10 pushes/minute during the 12 minutes of practice. When the practice period is longer, the effect on the cycle frequency is even larger. This was shown in previous studies with decrements in cycle frequency of and 22 pushes/minutes after respectively three weeks of practice and seven weeks of training (Groot et al. 2002b, Chapter 2; Dallmeijer et al. 1999b). An even longer period of practice may not lead to much further 42

43 Chapter 3 reduction of the cycle frequency since it will basically be dictated by the mechanical constraints of the task and the physical characteristics of the musculoskeletal system. A cycle frequency of pushes/minute was found after three and seven weeks of practice which compared well with a cycle frequency of 40 and 55 pushes/minute of experienced wheelchair-dependent subjects, although the latter group was wheeling on a treadmill at a different velocity or power output of respectively 0.55 and 1.11 m. s -1 and 20.4 and 39.8 W (Woude et al. 1989b). Although the cycle frequency decreased, and subsequently the cycle time increased, the push time remained constant. This means that the duration of the recovery phase increased over the practice period. An increase in the recovery time would enable the subjects to choose a different (e.g. longer) hand trajectory. Several recovery styles have been described in the past (Boninger et al. 2002; Sanderson et al. 1985; Shimada et al. 1998). It has been suggested that the recovery style could influence the mechanical efficiency, which is surely not the case in this short-term learning study. By definition, with the constant power output and reduction in cycle frequency, the work per cycle had to increase over time (23.9 to 29.6 J). This result was similar to the 3-week learning study, which showed even a larger increase (22.6 to 32.7 J), when the pre- and post-tests were compared. This increase in work was most probably generated through an increase in peak torque since the push time did not change. It could be suggested that a lower cycle frequency, and therefore a reduction of the number of de/accelerations of the upper extremity per time unit as well as a reduction of the overall negative power in the dips, relates to the mechanical efficiency. However, the present results do not support this hypothesis since the cycle frequency diminished significantly without a subsequent increase in the mechanical efficiency. Inter-cycle variability A typical finding is that movement variability reduces as a function of improvement of skill (Darling et al. 1987; Vereijken et al. 1997). For example, in rowing a high level of stroke-to-stroke consistency is necessary in the execution of an effective movement pattern, there being a high degree of dependence between successive movements (Smith et al. 1995). More variability in the movement pattern could lead to the necessity for more corrections to maintain, for example, the desired velocity and a good left-right symmetry. However, the need for corrections would subsequently lead to more energy loss. The inter-cycle variability gives an indication of how stable the movement pattern was. The inter-cycle variability of the force application variables was comparable with which was found in the 3-week learning study (Groot et al. 2002b, Chapter 2) except that the inter- 43

44 Chapter 3 cycle variability values of the push time and percentage push time were lower in the present study. Although a decrease in movement variability was expected as a function of practice and increments of skill (Darling et al. 1987; Vereijken et al. 1997), no decrease in inter-cycle variability was found during the first minutes or over three weeks of wheelchair practice (Groot et al. 2002b, Chapter 2). On the other hand, Bernstein (1967) proposed that, early in learning, redundancy might be constrained by freezing out degrees of freedom via muscle coactivity. Later in learning, these restrictions could be relaxed, which could lead to more variability in the movement pattern. The inter-cycle variability of the push time and the negative dip before the push increased in the present study, which might be an indication of unfreezing. One hypothesis that emerges from this idea is the following: muscle coactivity is initially high and will decrease with skill learning as degrees of freedom are freed up and limb stiffness is reduced. Subsequently, this may lead to an improvement in gross mechanical efficiency. Since muscle activity and kinematics could be easily measured, this will be useful in future learning studies. CONCLUSION Twelve minutes of manual wheelchair practice in novice able-bodied subjects induced already a significant decrease in the cycle frequency, which was accompanied by an increase in work per cycle and cycle time and a decrease in percentage push time. Since the push time remained the same, the increase in work per cycle was found to be due to an increase in the peak torque. For changes in other variables a longer practice period might be necessary, for example for the gross mechanical efficiency and to find a decrease in inter-cycle variability. On the other hand, the results of the present study combined with those from previous studies indicate that some variables are optimized from the start onwards. An example is the fraction effective force, since no difference was found after 3 (Groot et al. 2002b, Chapter 2) or 7 (Dallmeijer et al. 1999b) weeks of practice or compared to experienced subjects (Veeger et al. 1992a). ACKNOWLEDGEMENT The experimental assistance of Stefan van Drongelen is greatly acknowledged. 44

45 Chapter 3 TABLES Table 1. Mean values and SD of experimental variables over time and statistical results. For definition of variables, see text. * Results of a post-hoc test Tukey revealed that: the peak torque differed significantly between T1 & T4 and Work per cycle differed significantly between T1 & T3 and T1 & T4. T1 = Block min. T2 = Block min. T3 = Block min. T4 = Block min. Time Effect N Mean SD Mean SD Mean SD Mean SD P Mean power output (W) Negative dip before push (W) Negative dip after push (W) Peak torque (Nm) * Mean torque (Nm) Slope (Nm. s -1 ) Work per cycle (J) * FEFmax (%) FEFmean (%) Mechanical efficiency (%)

46 FEF (%) Torque (Nm) Chapter 3 FIGURES Torque signal right = Work per cycle Slope 0-5 Power loss Push time Cycle time Sample Figure 1. Illustration of the definition of push time, cycle time, slope, work per cycle and power loss before and after the push time. First FEF values FEFmax FEFmean Push Figure 2. Group mean and standard deviations (N = 8) of FEFmax and FEFmean for the first 10 pushes of the practice period. 46

47 Time (s) Chapter 3 Push time and Cycle time * Push time Cycle time T1 T2 T3 T4 Figure 3. Change in cycle and push time over the practice period. T1 = min. of block 1; T2-T3-T4: min. of respectively block 1, 2 and 3. * = significant main effect for cycle time. 47

48 Chapter 4 Short-term adaptations in co-ordination during the initial phase of learning manual wheelchair propulsion 48

49 Chapter 4 ABSTRACT The purpose of this study was to analyze adaptations in kinematics and muscle activity/co-contraction in novice able-bodied subjects during the initial phase of learning hand rim wheelchair propulsion. Nine able-bodied subjects performed three 4-minute practice blocks on a wheelchair ergometer. The external power output and velocity were constant for all blocks, respectively 0.25 W. kg -1 and 1.11 m. s -1. Electromyography of 16 arm, shoulder, back and chest muscles and kinematics were measured. Some small changes in the segmental movement pattern were seen during the practice period. Moreover, an increase in muscle activity and co-contraction of several muscles was found over time. The hypothesis that subjects instinctively search for an optimum frequency, in which the recovery phase is related to the eigenfrequency of the arms and, therefore, the least muscle activity, could not be supported. Since co-contraction of antagonist pairs remained the same or even increased, the hypothesis that there would be a decrease in muscle co-contraction as a result of practice, was not confirmed. This study was probably too short for the novice subjects to explore this new task of wheelchair propulsion completely and reach an optimum in terms of cycle frequency and muscle activity / co-contraction. 49

50 Chapter 4 INTRODUCTION Energy efficiency is one of the characteristics attributed to skilled movements. Sparrow et al. (1998) stated that adaptive movement patterns emerge as a function of the subject s innate tendency to minimize metabolic energy expenditure with respect to task and environment. In manual wheelchair propulsion a significant increase in gross mechanical efficiency was found after 3-weeks of practice (Groot et al. 2002b, Chapter 2) in a novice wheelchair-user group. Simultaneously, a decrease in cycle frequency was seen, which was accompanied by an increase in work per cycle (Groot et al. 2002b, Chapter 2). It was suggested that the improvement in timing variables had a positive effect on the mechanical efficiency. However, in a study focusing on the short-term adaptations in physiology and propulsion technique (Groot et al. 2003a, Chapter 3), it was found that the timing variables already changed within the initial 12 min. of practice while the mechanical efficiency remained the same in a group of completely novice able-bodied wheelchair users. A decrease in cycle frequency and an increase in work per cycle were found during the initial 12 min. of practice. The latter seemed to be due to an increase in peak torque over the practice period since no change in push time was found. Woude et al. (1989b) stated that shifts in timing will affect the kinematics of motion and thus influencing muscle activity and coordination. A wheelchair user can maintain the same external power output by varying the cycle frequency in combination with the work per cycle. If the cycle frequency decreases, the work per cycle has to increase to maintain the external power output and, therefore, the force application has to be enhanced or has to occur during a longer trajectory. The latter will demand increased segment excursions and an increased stroke angle. An increase in muscle activity during the push phase, and subsequently during the whole cycle, could be expected to accomplish this enhanced force application. Since the mean external power output remains the same, the averaged level of muscle activity over a certain time period could be expected to remain the same too, regardless of the cycle frequency - work per cycle combination. The work per cycle is accomplished during the push phase while the recovery phase has been called a passive period (Veeger et al. 1992c). However, it is suggested that ac/decelerating the arms during the recovery phase costs some amount of energy although this does not contribute directly to propelling the wheelchair. If the recovery phase indeed costs energy, then a high cycle frequency leads to more ac/decelerations of the arms and subsequently a higher energy loss. Previous studies found that the physiologically most efficient cycle frequency is the freely chosen frequency in comparison to paced frequencies below and above, both in experienced and less experienced wheelchair users (Goosey et al. 2000; Woude et 50

51 Chapter 4 al. 1989b). The relationship between cycle frequency and energy cost in hand rim wheelchair propulsion appeared to be hyperbolic where the freely chosen frequency is close to minimum energy cost. This is in contrast to cycling, where the freely chosen pedal rate is unrelated to gross mechanical efficiency and where the mechanical efficiency is highest at the lowest pre-set pedal rate (Hansen et al. 2002). In walking, Holt et al. (1991) found that preferred stride frequency produces a minimal metabolic cost as a result of the leg oscillating at resonance. Preferred behaviors seem to follow laws generated by the relationship between body-scaled (e.g. segment length) and environmental (gravity) parameters, i.e. in the study of walking (Holt et al. 1991). The idea of the leg swinging at resonant frequency is supported by electromyography (EMG) studies that have reported very little muscle activity during walking at a self-selected walking speed in the swing leg muscles of healthy subjects (Selles et al. 1999). These studies lead to the hypotheses that novice wheelchair users instinctively search for a cycle frequency with a recovery phase closest to the resonance frequency of their arms, and when they find this optimum frequency it will correspond to the least EMG activity. Several studies have been conducted to examine muscle activity patterns during wheelchair propulsion (Harburn et al. 1986; Mulroy et al. 1996; Rodgers et al. 1994; Schantz et al. 1999; Veeger et al. 1991a) but, as far as is known, alterations in muscle activity patterns over time due to natural training or learning in hand rim wheelchair propulsion have not been studied before. Given the large number of muscles around the shoulder, movements can be conducted with different sets of active muscles. One way to constrain this redundancy is to link muscles together into a muscle synergy. Bernstein (1967; Newell et al. 2001) proposed that, early in learning, redundancy might be constrained by reducing ( freezing out ) the number of degrees of freedom via muscle coactivity. Later in learning, these restrictions could be relaxed. If this is true, a corollary would be the following: muscle coactivity is initially high and will decrease with skill learning as degrees of freedom are freed up and limb stiffness is reduced. The push phase of wheelchair propulsion is a guided movement, with not many degrees of freedom, in contrast to the recovery phase, in which the hand can choose many paths to return to the initial push position. Therefore, it is expected that possible changes in cocontraction are particularly, if not only, visible during the recovery phase, especially at the end of the recovery phase when the moving hands have to be coupled to the rotating rim outside the visual field. Furthermore, a possible decrease in muscle cocontraction could explain the change in mechanical efficiency as was seen in the 3- week practice study (Groot et al. 2002b, Chapter 2). 51

52 Chapter 4 In order to test the hypotheses mentioned above, the present study focused on the short-term adaptations in kinematics and muscle activation patterns in completely novice able-bodied subjects in the initial 12 min. of the learning process on a computer-controlled wheelchair ergometer. METHODS Subjects After having given written informed consent, 9 able-bodied male subjects participated in the study. Criteria for inclusion were: male, no prior experience in wheelchair propulsion, absence of any medical contra-indications. The mean age was 24.0 years (SD = 4.8), mean body mass was 76.4 kg (SD = 8.0) and mean height was 1.82 m (SD = 10.2). All subjects were right-handed. The study was approved by the Medical Ethical Committee. Design Without prior familiarization, subjects performed three 4-min. submaximal practice blocks. The practice blocks were performed on a stationary, computer-controlled wheelchair ergometer (Niesing et al. 1990). The external power output of all blocks was 0.25 W. kg -1 and the velocity was 1.11 m. s -1. Two minutes of rest preceded each exercise block. The protocol was described in detail in Groot et al. (2003a, Chapter 3). Wheelchair ergometer Wheelchair ergometer dimensions were individually adjusted according to a standardized protocol described elsewhere (Groot et al. 2002b, Chapter 2). The ergometer allows for a direct measurement of propulsive torque around the wheel axle and the resultant velocity of the wheels (Niesing et al. 1990). From the torque signal the push and recovery phases were determined (Groot et al. 2003), Chapter 3). Kinematics Movement analysis was performed with a three-camera Optotrak system. The three-dimensional positions of markers were recorded at 100 Hz during the first practice block from (T1) and from minutes (T2). In the second and third practice block a data set was collected from minutes (respectively T3 and T4). The Optotrak computer was synchronized with the ergometer computer. Markers were positioned on the right side, on the hand (fifth metacarpal), wrist (caput ulna), elbow (epicondylus lateralis), and shoulder (angulus 52

53 Chapter 4 acromialis). From measurements with Optotrak the following parameters were determined: begin angle ( ), end angle ( ) and stroke angle ( ) (Figure 1). Begin and end angle were defined as the angle between the line from the hand marker (on fifth metacarpal) through the wheel axle, relative to the vertical, at the start and the end of the push phase. Stroke angle was defined as the sum of the begin and end angle. For every cycle the relative 3-D locations (in m, anterior/posterior, medial/lateral, cranial/caudal) of adjacent upper extremity points (shoulder elbow, elbow wrist, wrist hand) at time of the start and end of the push phase were determined according to Chow et al. (2000). To determine whether the position of the trunk in the chair changed over time, the position of the acromion with regard to the wheel axle was analyzed in the three directions at the time of the start and end of the push phase. The mean and peak velocity and ac/deceleration of the hand in the anterior/posterior (x) direction were calculated for the push and recovery time separately. Muscle activity The electromyography (EMG) of muscles of the forearm, upper arm, shoulder, back and chest were measured to obtain an indication of the level of activity and the tendency for co-contractions between certain sets of muscles over time. The following 16 muscles were determined: m. extensor carpi ulnaris, m. extensor carpi radialis, m. brachioradialis, m. biceps brachii, m. triceps brachii caput lateral and longum, m. pectoralis major pars sternocostalis and clavicularis, m. trapezius pars descendens, transversa and ascendens, m. deltoideus pars anterior, medialis and posterior, m. serratus anterior and m. latissimus dorsi. The bipolar EMG data were captured by Ag/AgCl, circular electrodes (Medicotest, Blue Sensor, type N-00-S) of about 11 mm diameter. Prior to the experiment, after shaving, gentle abrasion, and cleaning by alcohol of the skin, surface EMGelectrodes were positioned at the approximate geometrical center of each muscle on the right side (Hermens et al. 1999). The center-to-center electrode distance was 2 cm. The EMG signals were amplified, band-pass filtered ( Hz) and stored on a disk at a sample frequency of 1000 Hz. The EMG was synchronized with the Optotrak computer by means of a pulse. For each muscle, a static maximal voluntary contraction (MVC) was recorded and used for reference. For the MVC measurements subjects were asked to push as hard as they could against the tester s resistance in several positions of the upper extremity and trunk (Hermens et al. 1999) when sitting in the wheelchair ergometer. This was performed once for each muscle tested to exclude fatigue effects prior to the actual exercise blocks. Linear envelopes were constructed by re-sampling EMG signals with a frequency of

54 Chapter 4 Hz, preceded by rectifying and low-pass filtering (8th order Butterworth filter, Fc = 6 Hz (Winter 1979)) of the signal. Thereafter the EMG values were normalized to the highest muscle activity obtained in the MVC test. An electromechanical delay of 100 msec was used (from results of unpublished data) for synchronization of EMG and ergometer and kinematic data. The EMG data were normalized to percentage cycle time and ensemble-averaged for all complete cycles during the measurement period for each subject, leading to one average cycle (in percentage cycle time) for each subject. To get an indication of possible changes in the level of muscle activity the ensemble-averaged cycle for each subject was integrated over 1% steps. The level of muscle activity for each muscle, as well as the co-contraction, was determined for respectively the push, recovery and cycle time, all calculated from the ensemble-averaged cycle. Also, the level of muscle activity and co-contraction during all complete cycles, i.e. from the start of the first push until the start of the last push in the 15 s period, were determined by integrating the rectified, filtered, and normalized (to MVC) EMG signal over 1 s steps. It was expected that the possible effect of a lower cycle frequency, and thus less ac/decelerations of the arms, on the muscle activity was better visible in this 15 s analysis than in the ensemble-averaged cycle. By overlaying the linear envelopes of an agonist antagonist pair and calculating the area of overlap the amount of co-contraction was assessed (Figure 2). This created a co-contraction index for each pair at T1, T2, T3 and T4. The level of cocontraction was established for the following muscle combinations: m. extensor carpi radialis - m. extensor carpi ulnaris, m. biceps brachii - m. triceps brachii caput longum, m. biceps brachii - m. triceps brachii caput lateral, m. trapezius transversa - m. serratus anterior, and m. deltoideus anterior - m. deltoideus posterior. As said before, all complete cycles were used to compute within-subject ensemble averages. These ensemble averages were in turn averaged across all subjects to yield a grand ensemble normalized average for each of the four measurement periods. Inter-cycle variability The coefficient of variability (CV) was determined for every muscle of each subject from the mean and SD values of the integrated EMG signals of all pushes, recoveries and cycles in the measurement period according to: CV = SD. mean (%) (1) 54

55 Chapter 4 Statistics To evaluate a possible learning effect over the 12 minutes practice period, the changes over the four measurement times, namely T1 ( minutes of the first block) and T2, T3 and T4 (respectively minutes of exercise block one, two and three), were analyzed. An ANOVA for repeated measurements, with measurement time (T1, T2, T3 and T4) as main factor, was applied to detect significant differences over time for selected parameters. Significance level was set at p < 0.05 for all statistical procedures. RESULTS Kinematics Descriptive statistics for stroke angle, hand velocity and de/acceleration are presented in Table 1, and relative joint locations at time of hand contact and release for each testing time appear in Table 2. No difference in velocity was visible regarding the four measurement times, i.e. subjects were already at the desired velocity (and power output) at T1. Despite a significant reduction in cycle frequency over the 12 min. period (T1: 61 ± 12 pushes/minute T2: 57 ± 12 pushes/minute T3: 53 ± 15 pushes/minute T4: 51 ± 13 pushes/minute) (Groot et al. 2003a, Chapter 3), stroke angle, begin angle and end angle did not change significantly over time (Table 1). The position of the trunk in the chair as derived from the shoulder-wheel axis distance - at the start and end of the push phase did not alter during the practice period. In contrast, the medio-lateral distance, at both the start and end of the push phase, between the shoulder and the elbow diminished significantly over time, while the medio-lateral distance between the elbow and wrist increased significantly over time (Table 2). Since the position of the trunk did not change over time and the hand is fixed in the medio-lateral direction onto the rim, this indicates an inward movement of the elbow (adduction of the upper arm). The medio-lateral distance between the wrist and hand increased significantly and the cranial-caudal distance between the wrist and hand decreased significantly at the end of the push phase (Table 2). This indicates more palmar flexion and possibly ulnar deviation of the hand. In the anterior-posterior direction, the mean velocity and mean and peak acceleration of the hand during the push phase and the peak acceleration of the hand during the recovery phase changed significantly over time (Table 1). 55

56 Chapter 4 Muscle activity The activity pattern of each muscle at T1, T2, T3 and T4 is visualized in Figure 3. Muscle activity during push time: M. pectoralis major pars sternocostalis (p=0.04, T1 vs. T3) and m. deltoideus posterior (p=0.02, T1 vs. T2) showed an increase in muscle activity during the push phase over time. No change in co-contraction was found during the push time (Figure 4). Muscle activity during recovery time: M. trapezius descendens (p=0.00, T1 vs. T2, T3 and T4) and ascendens (p=0.00, T1 vs. T3 and T4), m. deltoideus posterior (p=0.02, T1 vs. T2 and T4), m. serratus anterior (p=0.03, T1 vs. T4) and m. lattisimus dorsi (p=0.05) showed an increase in muscle activity during the recovery phase over time. Significantly more co-contraction was found over the practice period for m. biceps brachii and m. triceps brachii caput longum (p=0.02, T1 vs. T2) and for m. trapezius transversa and m. serratus anterior (p=0.00, T1 vs. T4) during the recovery phase (Figure 4). Muscle activity during cycle time: A significant increase in muscle activity over the practice period during the (normalized) cycle time was visible for m. trapezius descendens (p=0.00) and ascendens (p=0.00), and m. deltoideus posterior (p=0.02). All three muscles showed most of the change already between T1 and T2, i.e. within four minutes of practice. A significant increase in co-contraction of m. trapezius transversa and m. serratus anterior (p=0.02) was found during the cycle time (Figure 4). When the integrated EMG of all complete cycles in the 15 s measurement period was calculated, i.e. not normalized to percentage cycle time and ensemble averaged, a significant increase in muscle activity was shown in m. biceps brachii (p=0.03), m. trapezius descendens (p=0.00) and ascendens (p=0.00), m. deltoideus medialis (p=0.02) and posterior (p=0.00) and m. serratus anterior (p=0.05), with most of the change between T1 and T2. The level of co-contraction of all complete cycles during the 15 s measurement period increased significantly between T1 and T2 for the antagonists m. biceps brachii m. triceps brachii caput lateral (p=0.02), and m. biceps brachii m. triceps brachii caput longum (p=0.01). Inter-cycle variability An increase in inter-cycle variability over time was found during the cycle time for all muscles except for m. triceps brachii caput longum, m. trapezius descendens and ascendens. The coefficient of variation of the activity of the muscles varied between 27-51% during the push phase and 23-62% during the recovery phase (with a high variation for m. serratus anterior of 75-97%). No change in inter-cycle variability was found during the push phase while a decrease was found for m. serratus anterior (p=0.04) during the recovery phase. 56

57 Chapter 4 DISCUSSION Learning of a motor task is associated with a number of changes in limb kinematics and muscle activity that produces the movement (Flament et al. 1999). Previous research (Groot et al. 2003a, Chapter 3) on short-term adaptations in propulsion technique found changes in timing parameters, indicating changes in kinematics and muscle activity. Although it is often suggested that changes in timing relate to changes in the mechanical efficiency (Groot et al. 2002b, Chapter 2; Woude et al. 1989b) this was not supported by a previous report by the authors that focused on the short-term changes in propulsion technique (Groot et al. 2003a, Chapter 3). However, changes in the movement pattern and muscle activity still could have occurred in association with changes in timing. The decrease in cycle frequency and subsequently increase in work per cycle during the first 12 min. of wheelchair practice (Groot et al. 2003a, Chapter 3) was clearly associated with an increase in peak torque while the push time remained the same. The increase in peak torque was obviously accomplished by the increase in acceleration of the hand during the push phase, which was found in the present study. Even though the push time remained the same, there could be an increase in the stroke angle due to the increased acceleration of the hands. The stroke angle in the current study showed a non-significant tendency to increase over time. It has been shown before that a longer training period (7-weeks) induces a significantly higher end and stroke angle in non-wheelchair users (Dallmeijer et al. 1999b). Some small changes in the relative joint locations were found in the current study, which could relate to the small but non-significant changes in begin and end angle. When more work per cycle occurs, the muscles, which have to produce this extra work, have to be more active during the push phase. So, the first question is, How do the muscle activity patterns of the present study relate to the increase in work per cycle? Secondly, Are the results of these novice wheelchair users regarding muscle activity patterns similar to the results of experienced wheelchair users of other studies? Of the muscles, which could be anticipated to propel the wheelchair forward and from which an increase in activity was expected as a consequence of the increase in work per cycle, i.e. m. biceps brachii, m. triceps brachii, m. deltoideus anterior, m. pectoralis major pars clavicularis and sternocostalis, only an increase of m. pectoralis major pars sternocostalis was found during the push phase. The increase in activity of m. deltoideus posterior over time, which was found in the present study during the push phase, would not be useful for increasing the work per cycle. Schantz et al. (1999) also found high activity of m. deltoideus posterior during the push phase in their study with paraplegic and tetraplegic subjects. They hypothesized that the possible function of 57

58 Chapter 4 m. deltoideus posterior activity during the push phase is stabilization of the shoulders. With an increase in work per cycle due to an increase in muscle activity of m. pectoralis major there probably should also be a corresponding increase in m. deltoideus posterior to keep the shoulder stabilized. The increase in muscle activity over time during the recovery phase (m. deltoideus posterior, m. trapezius ascendens and descendens, m. serratus anterior and m. latissimus dorsi), indicated by the integrated EMG, might be due to the increase in recovery time in absolute terms. Furthermore, the longer recovery time seems to lead to more variability in the movement pattern, which might lead to more muscle activity. The biceps brachii and the brachioradialis were hardly active during the whole cycle. This result was not similar to that reported by other investigators (Masse et al. 1992; Rodgers et al. 1994; Veeger et al. 1989a). They found m. biceps brachii activity during the initial part of the push phase and during the latter part of the recovery phase. Thus m. biceps brachii served as a forearm flexor to pull during the initial phase and again at the end of recovery as the arm returned to starting position (Rodgers et al. 1994). Since the begin angle was very small in this novice able-bodied subject group, the pull phase was probably very short too and, therefore, not much m. biceps brachii activity was required during the push phase in the present study. To flex the elbow during the recovery phase does not seem to cost a lot of biceps or brachioradialis activity, when expressed with reference to their MVCs. That these results are not similar to previous studies (Rodgers et al. 1994; Masse et al. 1992; Veeger et al. 1989a) might be due to the subjects use of a pumping recovery style (Sanderson et al. 1985; Schantz et al. 1999; Veeger et al. 1989a) in which the hands are brought back over the top of the wheel which could be in contrast to styles used by more experienced wheelchair users. M. trapezius transversa, a scapular retractor, functioned antagonistically to m. serratus anterior as has been shown before (Mulroy et al. 1996). M. lattisimus dorsi did not show a consistent pattern of activity during the propulsion cycle and was low in intensity, as was also shown by Mulroy et al. (1996). Changes in the amount of muscle activity were expected to result from changes in the cycle frequency, and these were expected to be most clearly visible in the analysis of all complete cycles in the 15 s period. The effects of arm ac/decelerations in the recovery phase is less clear when looking at one averaged and normalized cycle in contrast to analyzing a certain time block with more/less cycles involved dependent upon the cycle frequency. Previous research suggested that a lower cycle frequency leads to fewer de/accelerations of the arms and subsequently less muscle activity (Woude et al. 1989b). However, the present results do not support that theory, i.e. muscle activity did not decrease (and even 58

59 Chapter 4 increased in a number of muscles) with a lower number of pushes. It has also been reported before that the most efficient cycle frequency is the freely chosen frequency in experienced as well as less experienced wheelchair users (Goosey et al. 2000; Woude et al. 1989b), which is not the lowest frequency possible. The first hypothesis of the present study was that novice wheelchair users instinctively search for an optimum cycle frequency and when they find this optimum frequency the least EMG activity will be found. It was suggested that this optimum cycle frequency could relate to the eigenfrequency of the arms during the recovery phase as was previously found regarding the legs in walking (Holt et al. 1991). Novice wheelchair users do not seem to find this optimum cycle frequency within 12 min. of practice because the cycle frequency of the novice subjects was still higher than that found in previous studies after 3 (Groot et al. 2002b, Chapter 2) or 7 (Dallmeijer et al. 1999b) weeks of practice, and, furthermore no change in the mechanical efficiency in novice subjects has been reported (Groot et al. 2003a, Chapter 3). Moreover, an increase instead of a decrease in activity was found for several muscles. The theory of a segment oscillating at resonance during the recovery phase might not completely be applicable to novice wheelchair users since the arms do not really swing passively during a good deal of the recovery phase as the leg does, especially when using the pumping propulsion pattern (Sanderson et al. 1985; Schantz et al. 1999; Veeger et al. 1989a). The theory would be more applicable when the (semi-)circular propulsion pattern (Boninger et al. 2002; Sanderson et al. 1985; Schantz et al. 1999; Shimada et al. 1998; Veeger et al. 1989a) is used by the subjects. In this pattern, the hands show more swing motion from the end to the start point of the push phase below propulsion. Also, one needs to realize that walking is a fully automatic movement pattern in the adult, while hand rim wheelchair propulsion in the current study was a completely novel task. Since the task was completely new for the novice able-bodied subjects, Bernstein s theory suggests that they might begin by reducing ( freezing ) the number of degrees of freedom by muscle co-contractions (Bernstein 1967), then as they become more used to the task, they might start to unfreeze, resulting in less cocontraction and thus lower energy costs. However, in this study, no change in cocontraction was visible during the push phase. The lack of change was expected since the push phase is a guided movement with not many degrees of freedom. However, an unexpected increase in co-contraction was found for m. biceps brachii m. triceps brachii longum and m. trapezius transversa m. serratus anterior during the recovery phase. The high co-contraction of the anterior and posterior part of m. deltoideus might be necessary for stabilization of the shoulder. This result was also found in experienced subjects by Schantz et al. (1999), but this 59

60 Chapter 4 finding was in contrast with results of Mulroy et al. (1996) and Rodgers et al. (1994). Although it was suggested that more co-contraction would lead to a lower mechanical efficiency, this was not supported since the latter remained the same over the practice period (Groot et al. 2003a, Chapter 3). Moreover the time scale of practice (and learning) in the current study may not fully fit the freezing/unfreezing theory and needs to be studied on a larger time scale in the future. The inter-cycle variability gives an indication about the stability of the movement pattern. Typically movement variability reduces as function of practice and increments of skill (Darling et al. 1987; Vereijken et al. 1997). In previous studies, no decrease in inter-cycle variability of force application has been found during the first minutes of practice (Groot et al. 2003a, Chapter 3) or over three weeks of wheelchair practice (Groot et al. 2002b, Chapter 2). More variability in the movement pattern could lead to the necessity for more corrections to maintain e.g. the desired velocity and a good left-right symmetry, leading to more energy loss. Remarkable was that the variability of the movement pattern during the recovery phase increased over the practice period. Figure 5 shows the movement pattern that was visible for most subjects (pattern of subject B) in contrast to the less variable movement pattern of subject A. This increase in variability over time could be due to the increase of the recovery time. Therefore, the subjects had more time to get back to the initial push position. Another explanation for this increase in variability could be that the subjects were less concentrated at the end of the test. In the beginning, the task is completely new and they have to focus on what they are doing while at the end, the task will be performed more automatically and less concentration is needed to complete the task. Furthermore, the wheelchair task in the present study was fairly easy and submaximal, giving the subjects the opportunity to explore the task, using different propulsion styles, leading to more variability. Or, as found by Tuller et al. (1982), a beginner learns a skill by reducing some of the free variation of the body. As skill increases, the beginner will release the ban on the degrees of freedom and subsequently this will lead to more variability. The latter was not supported by the co-contraction findings, i.e. there was an increase in co-contraction of some muscle pairs instead of a decrease. Harburn and Spaulding (1986) found a high inter-subject variability but a low intrasubject variability (i.e. less than 10% as stated by them) from cycle to cycle. The low intra-subject variability of muscle recruitment patterns suggests that their subjects, in both wheelchair-dependent and able-bodied group, had a stable movement pattern and that the wheelchair task seemed to be a learned skill. Indeed, the able-bodied subjects in the study of Harburn and Spaulding (1986) 60

61 Chapter 4 were familiar with wheelchair mobility before the start of the test, i.e. not completely novice as the able-bodied subjects in the present study. The inter-cycle variability in the novice subjects was almost always higher than 10%, up to 51% and 62% for respectively the push and recovery phase. The shoulder muscle complex offers a wide range of movements, which could subsequently lead to a high variability between push cycles, especially in inexperienced subjects. As was the case with the negative power output dip at the start of the push phase, the push time (Groot et al. 2003a, Chapter 3) and the movement pattern, the inter-cycle variability of some muscles increased during the practice period. CONCLUSION Some small changes in the segmental movement pattern and an increase in muscle activity and co-contraction of several muscles were found during the 12 min. of practice in association with the changes in timing parameters. However, the subjects had probably not found their optimum cycle frequency yet because the cycle frequency of the novice subjects was still higher than found in previous studies after 3 (Groot et al. 2002b, Chapter 2) or 7 (Dallmeijer et al. 1999b) weeks of practice. Since the subjects did not reach their optimum cycle frequency within 12 min., the hypothesis that the optimum cycle frequency relates to the eigenfrequency of the arms and will lead to a higher mechanical efficiency and lower level of muscle activity, could not be supported. Furthermore, the suggested releasing or unfreezing of degrees of freedom by a decrease in muscle cocontraction as a result of practice, was not confirmed since co-contraction of antagonist pairs remained the same or even increased. This study was probably too short for the novice subjects to explore this new task of wheelchair propulsion completely and reach an optimum in terms of cycle frequency and mechanical efficiency. ACKNOWLEDGEMENT The experimental assistance of Stefan van Drongelen is greatly acknowledged. 61

62 Chapter 4 TABLES Table 1. Changes in mean and peak velocity and de/acceleration of the hand during the push and recovery phase over time in the sagital plane, and stroke angles (degrees). T1 = Block min. T2 = Block min. T3 = Block min. T4 = Block min. Time Effect N Mean SD Mean SD Mean SD Mean SD (p) Begin angle ( ) End angle ( ) Stroke angle ( ) PUSH Mean velocity Peak velocity Mean de/acceleration Peak de/acceleration RECOVERY Mean velocity Peak velocity Mean de/acceleration Peak de/acceleration Table 2. Relative locations (m) of shoulder, elbow, wrist and hand at the time of hand contact and hand release. X +: First joint in front of second joint; Y +: First joint medial of second joint; Z +: First joint above second joint. T1 = Block min. T2 = Block min. T3 = Block min. T4 = Block min. Time Effect N Mean SD Mean SD Mean SD Mean SD (p) HAND CONTACT Shoulder Elbow X Shoulder Elbow Y Shoulder Elbow Z Elbow Wrist X Elbow Wrist Y Elbow Wrist Z Wrist Hand X Wrist Hand Y Wrist Hand Z HAND RELEASE Shoulder Elbow X Shoulder Elbow Y Shoulder Elbow Z Elbow Wrist X Elbow Wrist Y Elbow Wrist Z Wrist Hand X Wrist Hand Y Wrist Hand Z

63 Chapter 4 FIGURES Start push phase TDC SA BA EA End push phase Wheel axle Wheeling direction Figure 1. Definition of the variables begin angle (BA), end angle (EA), stroke angle (SA) and top dead center (TDC). Cocontraction Co-contraction of m. trapezius transversa ( - ) and m. serratus anterior (.) %MVC % M VC Sample Figure 2. Definition of co-contraction. The area of overlap (gray) is the amount of co-contraction. 63

64 Chapter 4 Figure 3. Mean muscle activity patterns for T1 ( min. of the first block) and T2, T3 and T4 ( min. of the each block), normalized by MVC and cycle time. The vertical lines indicate the end of the push phase. (T1 =, T2 = - -, T3 =, T4 = _. _ ). 64

65 Integrated EMG Chapter Co-contraction Recovery time Push time * * # ECU-ECR T1 ECU-ECR T2 ECU-ECR T3 ECU-ECR T4 BB-TBLA T1 BB-TBLA T2 BB-TBLA T3 BB-TBLA T4 BB-TBLO T1 BB-TBLO T2 BB-TBLO T3 BB-TBLO T4 DA-DP T1 DA-DP T2 DA-DP T3 DA-DP T4 TT-SA T1 TT-SA T2 TT-SA T3 TT-SA T4 Figure 4. Change in co-contraction during the push, recovery and cycle time over the practice period. T1 = min. of block 1; T2-T3-T4: min. of respectively block 1, 2 and 3. ECU-ECR: m. extensor carpi ulnaris and radialis; BB-TBLA/TBLO: m. biceps brachii and m. triceps caput lateral / longum; DA- DP: m. deltoideus anterior and posterior; TT-SA: m. trapezius transversa and m. serratus anterior. # = significant for cycle time. * = significant for recovery time -50 T1 Subject A -50 T4 Subject A T1 Subject B -80 T4 Subject B Figure 5. Two typical examples (subjects A and B) of different changes in hand movement patterns in the sagital plane over time (T1: min. of the first block and T4: min. of the last block). 65

66 Chapter 5 Consequence of feedback-based learning of an effective hand rim wheelchair force production on mechanical efficiency 66

67 Chapter 5 ABSTRACT The purpose of this study was to investigate the effect of visual feedback on effective hand rim wheelchair force production and the subsequent effect on gross mechanical efficiency. In mechanical terms, the low gross mechanical efficiency of hand rim wheelchair propulsion may be the result of ineffective force production. Ten subjects in an experimental group and ten subjects in a control group practiced three weeks (3. wk -1, i.e. a pre-test and 8 trials) on a computer-controlled wheelchair ergometer. Every trial consisted of two blocks of 4 minutes at 0.15 and 0.25 W. kg -1 and 1.11 m. s -1. On three trials an additional block at 0.40 W. kg -1 was performed. The experimental group practiced with and the control group practiced without visual feedback on the effectiveness of force production. During all trials oxygen uptake, power output, forces and torque on the hand rims were measured. In comparison with the control group, the experimental group at trial 8 had a significantly more effective force production compared to the control group (respectively 90-97% vs %), but showed a significantly lower mechanical efficiency (respectively % vs %). Findings indicate that the most effective force production from a mechanical point of view is not necessarily the most efficient way - in terms of energy cost - from a biological point of view and that force direction is based on an optimization of cost and effect. 67

68 Chapter 5 INTRODUCTION Hand rim wheelchair propulsion is a way of locomotion with a low gross mechanical efficiency (ME). Gross ME of wheelchair propulsion rarely exceeds 11% and is much lower than in arm cranking (16%) (Martel et al. 1991; Powers et al. 1984) or cycling (18-23%) (Coyle et al. 1992). As a consequence, hand rim wheelchair propulsion is associated with a high physical strain in daily life (Janssen et al. 1994) and leads most likely to a high mechanical load on the upper extremity. The latter may lead to a high prevalence of overuse injuries in shoulder and wrist (Boninger et al. 1997). It was suggested that propulsion technique plays a role in the low ME (Veeger et al. 1992c). Therefore, it is important to study which aspects of propulsion technique are associated with ME and how hand rim wheelchair propulsion technique can be improved in terms of efficiency and mechanical strain. What is known about the gross ME of hand rim wheelchair propulsion is that, at least partially, it is the result of non-optimal tuning of the wheelchair to the physical characteristics of the user (Woude et al. 1989c). The low ME can also be due to the occurrence of, so called, ineffective propulsion technique characteristics, such as braking torques at the start and end of the push phase (Veeger et al. 1991a; Veeger et al. 1992c), and/or a propulsion force whose direction is at least from a mechanical viewpoint - not fully optimal, as it would be when tangential to the hand rims (Veeger et al. 1992c). From a purely mechanical standpoint, the greater the portion of force directed tangentially to the hand rim and the more positive the torque around the hand, the greater the moment developed around the wheel hub. Individuals who apply large non-tangential forces will require larger total forces to produce the same effective torque (Boninger et al. 1997). Veeger and colleagues (Dallmeijer et al. 1994; Veeger et al. 1991a; Veeger et al. 1992b; Veeger et al. 1992c) have described the tangential versus total force produced and developed the fraction of effective force (FEF). This measure is defined as the ratio of effective (tangential) force and total force, expressed as a percentage, and was used to describe how effective an individual was in applying forces to the hand rim. The FEF is dependent on the direction of the propulsion force that is applied and on the direction and magnitude of torque around the hand (Veeger et al. 1992a). The FEF was found to be low (between 57 and 81%) in able-bodied and low-level spinal cord injured subjects (Dallmeijer et al. 1994; Dallmeijer et al. 1998; Veeger et al. 1992a; Veeger et al. 1992b; Veeger et al. 1992c; Veeger et al. 1991b), as well as in wheelchair athletes (Woude et al. 1998). A low FEF generally indicates a more downward direction of the total force vector. Boninger et al. (1997) using a comparable but not identical measure 68

69 Chapter 5 (squared tangential force / squared resultant force of the force components in three directions, expressed as a percentage) found equally low values (52-54%) in experienced wheelchair users on a wheelchair dynamometer. Since able-bodied as well as experienced wheelchair-dependent subjects appear to direct the force always more downward, this may indicate that the force is directed to the best of abilities - regarding joint mechanics and muscle coordination - when directed nontangentially (Roeleveld et al. 1994). Besides a simulation experiment of force direction (Rozendaal et al. 2000), which suggested that experienced users optimize the force pattern by balancing the mechanical effect as well as the musculoskeletal cost, no literature is yet available concerning the consequences of a high FEF on gross ME in hand rim wheelchair propulsion. Therefore, a visual feedback computer program on FEF was developed. This was implemented in a practice period to obtain a group, who could apply a high FEF, for studying the effect on ME. Although feedback on force application was found to be effective in changing pedal force patterns in cycling (Broker et al. 1993; Sanderson et al. 1990), it was not certain whether subjects could indeed improve FEF with help of visual feedback. Therefore, the first purpose of the study was to investigate the effect of visual feedback on FEF. The second and main purpose of the present study was to investigate the consequences of a learned high FEF on gross ME, compared to a freely chosen FEF in two otherwise comparable novice, able-bodied subject groups. Novice able-bodied wheelchair users were included in this study since experienced wheelchair users already found a balance between mechanical effect and musculoskeletal cost. METHODS Subjects Twenty able-bodied male subjects participated in this study. Criteria for inclusion were: male, no prior experience in wheelchair propulsion, absence of any medical contra-indications like, among others, complaints of the musculoskeletal system. Subject characteristics are listed in Table 1. All subjects completed a medical history questionnaire and were informed of the nature and possible risks involved in the study before giving their informed consent to participate. Subjects were not informed about the precise purpose of the study. They only were told that they participated in a wheelchair training study. The protocol of the study was approved by the Medical Ethical Committee. 69

70 Chapter 5 Design Subjects were randomly divided into an experimental group (EXP; N=10) and a control group (C; N=10). Both groups practiced for three weeks, three times per week, on a computer-controlled wheelchair ergometer. All subjects performed a pre-test at the beginning of the three weeks, followed by eight practice trials. The pre-test and the eight practice trials comprised two four-minute exercise blocks at two different levels of external power output (first block: 0.15 W. kg -1 and second block: 0.25 W. kg -1 ) at a velocity of 1.11 m. s -1. The intensity of 0.25 W. kg -1 and the velocity (1.11 m. s -1 ) were chosen for comparison with previous studies (Linden et al. 1996; Veeger et al. 1992c). Since it was expected from results of a previous study (Dallmeijer et al. 1998) that the experimental effects would be more markedly present at higher levels of power output, an extra practice block was added on trial one, four, and eight with an external power output of 0.40 W. kg -1 and a velocity of 1.11 m. s -1. To exclude an effect of training on gross ME, the groups received this extra block on three trials only. The second trial was chosen to perform this extra block for the first time, so the subjects first could familiarize with the wheelchair ergometer before propelling at this relatively high intensity. Each exercise block was preceded by two minutes of rest. Subjects were asked to propel the wheelchair as naturally as possible. All subjects were given visual feedback on the velocity, and were able to keep the mean velocity at a constant level (1.11 m. s -1 ). Feedback on velocity was presented on a screen in front of the subjects (Figure 1). In order for EXP to reach a more effective propulsion technique, subjects were asked to propel on the basis of visual feedback of a graphical representation of FEF. The feedback of the velocity and FEF were both nearly instantaneous. The successfulness of such a feedback on force application was shown before in cycling (Sanderson et al. 1990). The FEF feedback, given on the same screen as the feedback on the velocity (Figure 1), was a graphic that showed a single vertical line, ranging from %, representing the actual FEF for the right side only. The presented FEF was low-pass filtered (cut off frequency of 1.5 Hz) in order to show a gradually increasing/decreasing FEF line per push. EXP were instructed to try to increase the computer-generated representation of FEF as high as possible. Subjects were not aware that the line represented the magnitude of the FEF and was meant to assist them in directing the force tangentially and/or to increase the torque around the hand. C were propelling with a freely chosen natural technique i.e. without visual feedback on FEF on any of the trials. 70

71 Chapter 5 Wheelchair ergometer The practice trials were all performed on a custom-built wheelchair ergometer. This ergometer was a stationary, computer-controlled wheelchair simulator that allows for direct measurement of propulsive torque around the wheel axle, propulsive force applied on the hand rims, and resultant velocity of the wheels (Niesing et al. 1990). Wheelchair ergometer dimensions were individually adjusted such that when sitting upright with the hands on the rim top the subject s shoulder was directly above the wheel axle and the elbow angle was approximately 110 with 180 being full extension. Camber of the wheels was set at 4º. Seat angle and backrest were set at 5º to the horizontal and 15º to the vertical axis, respectively. Ergometer data were collected within each exercise block, during the last minute, with a sample frequency of 100 Hz. Torque, forces and velocity were low-pass filtered (cut off frequency of 10 Hz, recursive second order Butterworth filter). Because of resonance in the system the medio-lateral force component was filtered at a lower frequency (5 Hz, fourth order). Force effectiveness Variables were calculated as mean over the whole last minute of each exercise block or as mean values for each of the pushes of this last minute. The push is defined as the amount of time that the hand exerted a positive torque on the hand rim (Figure 2). From the measured torque and wheel velocity, the power output (PO) on each wheel was calculated as: PO = M. V w. r w -1 (W) (1) Where: M = torque around the axle, V w = velocity of the wheel, r w = wheel radius. Mean total power output (POmean) was the sum of the power output for the left and right wheel and was calculated as an average value over one minute. The global coordinate system in which forces were analyzed, was defined as follows: Fx: horizontally forward, Fy: horizontally outward, and Fz: vertically downward. From force components Fx, Fy and Fz, total force applied on the hand rim (Ftot) was calculated, according to: Ftot = (Fx 2 + Fy 2 + Fz 2 ) (N) (2) 71

72 Chapter 5 The force component tangential to the hand rims, called here effective force (Fm) was calculated from torque (M) and hand rim radius (r r ) according to: Fm = M. r r -1 (N) (3) The fraction effective force on the hand rims (FEF) was calculated from equations 2 and 3 for each workload and expressed as a percentage: FEF = Fm. Ftot (%) (4) Gross mechanical efficiency Oxygen uptake ( V O2 [l. min -1 ]) was continuously measured during the whole test with an Oxycon Champion (Jaeger, Germany). Calibration was performed before each test with reference gas mixtures. The gross ME of wheelchair propulsion was calculated, according to: ME = POmean. En (%) (5) The mean power output (POmean) was calculated from the ergometer data over the last minute of each exercise block. The energy expenditure (En) was calculated from the oxygen uptake and the respiratory exchange ratio according to Garby and Astrup (1987). En was calculated over the last two minutes of each exercise block in order to minimize errors inherent in the measurement system. Statistics An independent t-test was applied on the subject characteristics to detect significant differences between the groups. An ANOVA for repeated measurements was applied, with external power output (0.15 and 0.25 W. kg -1 ) as within-subject factor and group (EXP and C) as between-subject factor, on the pre-test values of FEF and gross ME to test for possible differences between the two groups. Since the objective is to evaluate the consequence of learned differences in FEF, EXP and C were studied at the end of the practicing period (trial 8) only for the three levels of power output combined. An ANOVA for repeated measurements, with external power output (0.15, 0.25 and 0.40 W. kg -1 ) as within-subject factor and group (EXP and C) as between-subject factor, was applied to test the hypothesis, i.e. to detect significant differences for the force variables and gross ME between the groups on trial eight. 72

73 Chapter 5 To investigate the possible relationship between FEFmean and gross ME on trial eight, Pearson s correlation coefficients were calculated for each of the external power output levels and for 20 subjects. Significance level was set at p < 0.05 for all statistical procedures. RESULTS Subjects All subjects completed all the trials. Mean age, body mass and height did not differ significantly between the groups (Table 1). No significant differences were found in pre-test levels of FEF and gross ME between the two groups (Table 1). Force effectiveness Mean forces and FEFmean, averaged over the push phase, at trial eight are listed in Table 2. FEFmean at trial eight (Figure 4) differed significantly between groups. A larger FEFmean was observed for EXP at all external power outputs (respectively 90%, 97% and 97%) in comparison with C (respectively 79%, 83% and 83%). The pattern of change in FEFmean across PO levels was about the same for both groups. This was indicated by the absence of a significant interaction effect PO * group. Fx showed no significant difference between the two groups, whereas Fy and Fz did. Fy was directed inwards in EXP and outwards in C at trial eight. Fz was significantly lower for EXP in contrast to C at the last trial. Although FEFmean differed significantly between the groups, Fm and Ftot did not show any significant difference. Gross mechanical efficiency Gross ME at trial eight (Figure 5) differed significantly between the groups (Table 2) with EXP showing a systematically lower gross ME (respectively 5.5%, 7.0% and 8.5%) compared to C (respectively 5.9%, 8.1% and 9.9%). Gross ME increased significantly with a higher load in both groups. The difference in gross ME between EXP and C increased also with a higher power output level, as is seen in Figure 5. No significant correlation was found between FEFmean and gross ME on trial eight at any of the levels of power output (r = 0.14 at 0.15 W. kg -1, r = at 0.25 W. kg -1, and r = at 0.40 W. kg -1 (N=20 for all calculations)). 73

74 74 Chapter 5 DISCUSSION Previous research suggested that an ineffective force production, that is a low FEF, may at least in part be responsible for a low gross mechanical efficiency (Veeger et al. 1992a; Linden et al. 1996). The present study was designed to investigate the effect of a learned high FEF on gross mechanical efficiency in hand rim wheelchair propulsion. Although feedback on force application was found to be effective in changing pedal force patterns in cycling (Broker et al. 1993; Sanderson et al. 1990), it was unknown whether it was possible for the subjects to attain a more effective propulsion technique in manual wheelchair propulsion with help of visual feedback. The results of the FEF values even more than 100% in some of the EXP subjects - showed that a mechanically effective propulsion technique is possible through feedback-based learning. The high values of FEF reflected the strength of the visual feedback, which was in accordance with previous studies using visual feedback on a biomechanical variable to acquire new skills (Gauthier 1985) or to modify skills (Broker et al. 1993; Sanderson et al. 1990) in cyclical motions such as rowing and cycling. Values of FEF and ME and the differences in these variables between EXP and C increased with a higher load, as was also shown in a previous study (Dallmeijer et al. 1998). This stresses the influences of more strenuous boundary conditions of the task on technique related parameters. Under low submaximal conditions, technique may be considered less critical to performance and, therefore, differences may be (more) expressed at higher intensities. The FEF is a complex phenomenon and, by definition, dependent on the direction of the propulsion force that is applied and on the direction and magnitude of the torque around the hand (Veeger et al. 1992a). Equation 3 shows that in our experimental set-up (Niesing et al. 1990) the effective force on the hand rim (Fm) is directly calculated from the torque around the axle (M), which is again dependent on the torque around the hand (Mh) and the tangential (i.e. effective) part (Feff) of the total force applied (equations 6 & 7; Figure 3). M = Mh + Feff. r r (Nm) (6) Equations 3. and 6. lead to: Fm = (Mh + Feff. r r ). r r -1 (N) (7) The absence of a torque around the hand would lead to a FEF value of 100% when simultaneously Ftot is directed perfectly tangential (Roeleveld et al. 1994;

75 Chapter 5 Veeger et al. 1992a). In some subjects FEF exceeded 100% which means that a positive torque around the hand was present. Since kinematics was not included in the measurements, it was not possible to calculate Feff and to subsequently obtain Mh. Previous work (Linden et al. 1996) showed that the direction of the torque around the hand was opposite to the propulsion torque for most of the push phase. This is possibly due to the need to keep sufficient contact with the rims in order to be able to apply force on those rims. However, that a positive Mh is possible was previously shown by a study of Veeger et al. (1992a), in which a top basketball player had a FEF of 94% and was the only subject who produced a positive Mh. There were no significant differences in Fm and Ftot between the groups, possibly due to the high standard deviation of these variables in EXP. Since both Fm and Ftot showed a tendency to be respectively higher and lower in EXP, this probably contributed to the significantly higher FEF in EXP compared to C. A tendency to a decrease in Ftot in EXP is associated with significant changes in the force components, Fy and Fz. Since a higher fraction effective force could be attained, this raised the question why the naturally learning subjects in the control group and (experienced) subjects in previous research (Dallmeijer et al. 1994; Dallmeijer et al. 1998; Veeger et al. 1992a; Veeger et al. 1992b; Veeger et al. 1992c; Veeger et al. 1991b; Woude et al. 1998) did not acquire in mechanical terms a high FEF. Possibly, the relatively low effectiveness of force production, which was shown in C, may be the direct result of the fact that wheelchair propulsion is a guided movement. Since during the push phase the hands have to hold the rims in order to be able to apply force, the wheelchair user has the option not to apply a mechanically effective force. In fact, any direction of force will be possible as long as this force will have a certain tangential component. The choice made by subjects for a less effectively directed force, might thus be based on the innate capacity of biological systems to adapt to movement tasks in a biologically optimal way, thus preventing other biologically detrimental effects under the given boundary conditions (Roeleveld et al. 1994; Veeger 1993). Indeed, EXP showed a higher FEF but a lower gross ME compared to C, which was in contrast to what was expected from a mechanical viewpoint. There are several theories that could explain the present findings. First, the lack of improvement in gross ME in EXP can be due to the previously described conflict around the elbow that arises with the application of a tangential force direction (Roeleveld et al. 1994; Veeger et al. 1992c). This conflict between the torque production requirements and the movement-related requirement of the active 75

76 Chapter 5 muscles (Roeleveld et al. 1994; Veeger et al. 1992c) is illustrated by Figure 6. When Ftot is directed tangentially the elbow joint is extending in order to follow the hand rim, while at the same time a flexing moment ought to be generated for directing the force tangentially (Veeger et al. 1994). This situation would lead to the production of negative power, and hence, be ineffective regarding co-ordination and physiology (Linden et al. 1996). Also, it is not possible to maximize elbow extension torque (i.e. triceps contribution) when the force has to be directed tangentially. Since the present study was partly an explorative one, no EMG measurements were done in the present study and no answer can be given to the question whether and how EXP, who achieved a high FEF, resolved the possible arising conflict in the elbow in terms of muscle activity and timing. According to a second theory, the dissipation of energy, that can occur when the force is directed tangential to the hand rim, could be easily remedied by incorporating bi-articular muscles (Gielen et al. 1990). The required flexion torque in the elbow joint for directing the force can be obtained by activation of m. biceps, which is preferential above lengthening of mono-articular muscles resulting in negative work done. On the other hand, lengthening of biceps, which would arise due to the elbow extension necessary to follow the hand on the rim, is compensated for by anteflexion of the shoulder. This theory states that it is possible to direct the force tangentially without dissipating mechanical energy. However, an isometric contraction of the biceps also costs energy and a significant difference in gross ME was found in the present study between EXP and C, indicating a relative loss in efficiency in EXP compared to C. A third theory states that when applying a tangential propulsion force, there will be an increased power production around the shoulder (Veeger et al. 1992c) due to an increased moment arm of the propulsion force. This implies that the shoulder muscles have to be used more heavily and the compression force in the glenohumeral joint is subsequently expected to increase (Veeger 1999). Modelling results showed that the use of the effective force direction indeed led to higher muscle forces and a higher compressive load on the glenohumeral joint (Veeger 1999; Veeger et al. 1999). One of the main reasons for this high compression force in the shoulder was the additional muscle force that was needed to stabilize the glenohumeral joint to obtain the desired force direction. Since this extra muscle activity would not all contribute to propulsion, this might induce a lower mechanical efficiency. A simulation experiment was performed by Rozendaal and Veeger (2000) to evaluate the relationship between mechanical effect and musculoskeletal cost (i.e. costs at the joint level) in wheelchair propulsion. The results of the simulation 76

77 Chapter 5 study indicate that the actual direction of force generation is a compromise between the mechanically most effective direction and the force direction that can be sustained by the arm at minimum metabolic cost. Previous cross-sectional work (Dallmeijer et al. 1998) showed that persons with tetraplegia (TP) had a considerably lower effectiveness of propulsion technique and gross ME compared with persons with paraplegia (PP) (FEFmax for TP was 55-60% vs % for PP). However, as a consequence of loss of arm muscle function in TP in particular lack of hand grip function and elbow extensor function - TP found probably also the most effective force direction within the constraints of their biological system, similar to PP and C of the present study. Therefore, it will not be useful for PP and TP to learn a more effective propulsion technique with help of visual feedback on FEF. Based on the current comparison between EXP and C, it may be concluded that a high FEF does not lead to an improved performance in terms of gross ME and that push performance is based on a minimization of energy losses criterion. The experimental results in the current study do not imply that FEF is of a fixed magnitude and may not react to long-term practice and training or as a consequence of functionality (Dallmeijer et al. 1998; Woude et al. 1998). Apart from the probable effect of talent and level of disability, cross-sectional results of Woude et al. (1998) suggest that small increments in FEF may be reached as a consequence of training. Other technique related parameters are probably responsible for the increase in gross ME as a consequence of natural learning in C. Future research should focus on whether the high FEF is achieved by changes in Mh or Feff and should investigate the muscle activity patterns, especially in the framework of improved ME with learning/practice. Also important is that researchers should look at the whole wheelchair and user system from a combined mechanical and biological perspective instead of drawing conclusions without taking all perspectives into account. CONCLUSION Visual feedback on the force effectiveness appeared to be a useful learning tool in hand rim wheelchair propulsion. The experimental group showed a higher effective force production than the natural learning control group. Conversely, however, the experimental group showed a lower gross mechanical efficiency compared to a control group. This indicates that the most effective propulsion technique from a mechanical point of view is not necessarily the most efficient way of propulsion from a biological point of view. Other technique parameters than an 77

78 Chapter 5 improved effective force direction are responsible for the improvement in gross mechanical efficiency in the control group as a consequence of natural learning and training. ACKNOWLEDGEMENT The experimental assistance of Cécile Boot and Stephanie Valk is greatly acknowledged. 78

79 Chapter 5 TABLES Table 1. Mean and SD of the subject characteristics and pre-test levels of FEFmean and gross mechanical efficiency (ME) for the experimental (EXP) and control (C) groups and results of the statistical tests for determining differences between the groups. External PO EXP (N=10) C (N=10) P-value (W. kg -1 ) Mean SD Mean SD Age (years) Body mass (kg) Height (cm) FEFmean Gross ME Table 2. Mean and SD of the force variables and gross mechanical efficiency (ME) at trial 8 for the two groups and results of the ANOVA for repeated measurements. External PO EXP C PO Group PO * (W. kg -1 ) Mean SD Mean SD Group POmean (W) V (m. s -1 ) Fm (N) Fx (N) Fy (N) Fz (N) Ftot (N) FEF (%) ME (%)

80 Torque around wheel axle (Nm) Chapter 5 FIGURES 1.11 m. s -1 on the right side Fluctuating velocity line 1.11 m. s -1 on the left side 0 m. s % FEF Gradually fluctuating FEF line 50% FEF Figure 1. Screen showing the velocity (left) and FEF (right) feedback given to the subjects. Torque on the right side Push Samples Figure 2. Illustration of the definition of the push. 80

81 FEFmean (%) Chapter 5 Mh Fz M Fx Fm Ftot Figure 3. Illustration of the torques and forces applied to the hand rim. Mh = torque around the hand; Fx = force direction horizontally forward; Fz = force direction vertically downward; Fm = effective force on the hand rim; Ftot = total propulsion force applied; M = torque around the wheel axle EXP C External power output (W. kg -1 ) Figure 4. FEFmean (mean and SD) at trial eight for EXP and C at external power output levels 0.15, 0.25 and 0.40 W. kg