Robotic assessment of manual asymmetries in unimanual and bimanual wrist joint position sense

Transcription

1 6th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob) June 26-29, UTown, Singapore Robotic assessment of manual asymmetries in unimanual and bimanual wrist joint position sense Francesca Marini 1, Sara Contu 2, Charmayne M. L. Hughes, Pietro Morasso 1 and Lorenzo Masia 2 Abstract Despite being so similar from a biomechanical perspective, the left and the right arms develop with different dexterity and important functional differences. This asymmetry in motor performance, most commonly known as handedness, has been extensively investigated in numerous research. However, whether such a dominance exists in the proprioceptive system remains unclear. To this end, manual asymmetries in proprioceptive sensitivity were examined in fourteen neurologically healthy right-handed individuals, with a unimanual and bimanual robot-aided wrist joint position matching (JPM) task, whereby they are required to replicate a reference wrist angle in the absence of vision. The results did not provide any evidence of manual asymmetries in proprioceptive acuity but some indication of asymmetry was singled out in motor execution, with smoother movement trajectories when the task was performed by the non dominant hand. In contrast, experimental conditions (unimanual vs. bimanual) appeared to influence proprioceptive acuity as well as movement kinematics: in the unimanual condition proprioceptive acuity was higher and more consistent and, despite the fact that movements were found to be faster in the unimanual task, they resulted smoother if performed with two hands at the same time. In sum, our results indicated that while there was a decrement in performance during bimanual tasks, there was no evidence of proprioceptive hand dominance. I. ITRODUCTIO Asymmetries in upper limb performance are a fundamental aspect of human behaviour. The tendency for humans to prefer the use of one arm versus the other when performing activities of daily living has been cited as one of the most obvious examples of lateralized brain function [1]. This phenomenon, usually known as handedness, commonly favours the use of the right arm [2] and has classically been attributed to a contra lateral left hemisphere specialization for the control of motor output []. This preferred right arm/left hemisphere motor dominance has inspired researchers over the course of the past century garnering interest across a multitude of scientific domains. Despite these observations, the presence of a sensory dominance is still unclear and, in particular the role of proprioceptive information in determining arm performance asymmetries has been largely under appreciated. Indeed, most studies regarding proprioception have focused solely on the preferred right arm of righthanded individuals [][1][15], and the relationship between proprioceptive sensitivity and arm preference is still unclear. 1 F.M. and P.M. authors are with the RBCS Dept., Italian Institute of Technology, Genova, Italy francesca.marini@iit.it C.H. author is with Department of Kinesiology, San Francisco State University, 1600 Holloway Avenue, San Francisco, CA S.C. and L.M. authors are with School of MAE of the anyang Technological University of Singapore Moreover, most studies investigating proprioceptive acuity have focused on unimanual movements (contralateral or ipsilateral task perfomed with one hand at the time) [7][8][9], and at present there is no consensus regarding the mechanisms by which the central nervous system processes proprioceptive information during bimanual movements. There is empirical evidence from both lower and upper limb studies involving both injured and healthy individuals [5][6] that bilateral proprioceptive performance is lowered to the level of the lower performing limb, indicating that when a single limb with higher proprioceptive acuity performs a movement simultaneously with the other limb. The consequence is a decrease in bilateral movement discrimination performance. Conversely, a recent study [10] has suggested the central nervous system is aware of and utilizes information obtained by the limb with the best proprioceptive acuity for bimanual judgments. Further results demonstrated that proprioceptive bias and acuity were best predicted by the model in which bimanual estimates were generated by the use of the limb with the best proprioceptive acuity [5][6]. In order to expand this corpus of work, the present study examined dominant and non-dominant distal upper limb joint position sense of fourteen healthy young adults by means of a robotic bimanual wrist device and investigated whether these asymmetries differ depending on whether the proprioceptive test is performed with one or two hands. Proprioceptive acuity was assessed via an ipsilateral joint position matching task in which participants attempted to replicate a reference wrist angle in the absence of vision [16]. To examine manual asymmetries in wrist proprioceptive sensitivity we asked participants to perform the task with the dominant right hand or the non-dominant left hand, whereas we manipulated the number of hands required during task performance (unimanual, bimanual) in order to examine whether (potential) asymmetry differs depending on whether the motor task is performed with one or two hands. Based on prior work [7][8], it was hypothesized that proprioceptive sensitivity would be greater for the nondominant, compared to the dominant hand. Furthermore, it was expected that wrist proprioceptive acuity would be better during unimanual, compared to bimanual, task performance, in line with previous findings demonstrating that bimanual movements take longer to plan [11] and execute than similar unimanual actions [1][12] /16/$ IEEE 912

2 Fig. 1: A) View of the experimental set-up. B) Human wrist degrees of Freedom (DoFs) tested in the current experiment: Flexion/Extension () and Radial/Ulnar deviation () A. Participants II. MATERIALS AD METHODS Fourteen right-handed participants (mean age 26.9 ±.86 years, 6 females, 8 males) participated in this study. All participants were right-handed (mean score = 8.2, SD = 11.1) as assessed using the Edinburgh Handedness Inventory [17] which ranks handedness on a scale ranging from -100 (completely left-handed) to 100 (completely right-handed). Participants had normal or corrected to normal vision and did not have any known neuromuscular disorders. The experiments were conducted in accordance with local ethical guidelines and conformed to the Declaration of Helsinki. B. The robotic device The experimental apparatus used in this study consists in two degree of freedom (DoF) fully backdrivable robotic devices developed specifically for the study of human motor control and sensorimotor rehabilitation [18]. The range of motion (ROM) of the three DOFs approximates the ROM of the human wrist (human: 65 /70 flexion/extension (), 15 /0 radial/ulnar deviation (), 90 /90 pronation/supination (PS); Wrist robot: 72, 5 /27, 80 PS), Figure 2A. The robots are driven by brushless motors: two motors for which can provide sufficient force to stabilize a human wrist against gravity and one motor for each of the two remaining DoFs; the maximum torque values are: 1.5 m (); 1.6 m (); 2.77 m (PS). Angular rotations on the three axes were measured by means of digital encoders with a resolution of 098 bit/turn. The system is integrated with a virtual environment in order to provide a visual feedback to the user. The PC was equipped with an Analog and Digital I/O PCI card (Quanser QUARC QPIDe), in which the following channels were used: a) Eight Analog channels to command the reference values of the motor currents and b) Eight Encoders to read and receive the repetition signals from the digital encoders. Rotations of each Wrist robot were read through a QUARC block in Simulink and translated to linear movements in the virtual environment. C. Task and procedure The experiment was conducted in the ARIES Lab, School of Mechanical and Aerospace Engineering, anyang Technological University. After reading and filling out the written informed consent and handedness inventory forms, the participant sat in a height adjustable chair in front of the robotic device and a blindfold was used to occlude vision (Figure 2A). Participants performed a JPM test [16] in which wrist and RU deviation proprioceptive acuities (Figure 2B) were examined. At the start of each trial, the wrist was placed in a neutral configuration (0 of and 0 of ), and the robot allowed movement only in the DoF involved in the current trial, while keeping the other DoFs blocked in the neutral position. An auditory cue (highfrequency beep) marked the start of the passive reaching phase, in which the wrist was passively moved by the robotic device to specific target positions, corresponding to the 80% of the functional RoM (: 2 [of 0 ], : 16 [80% of 20 ]). After a hold time of three seconds [19][20], the wrist was passively returned to the initial start position. Thereafter, a low-frequency auditory cue indicated that the participants should move their wrist and try to match the target angle previously experienced (figure2c). During this active matching phase the robot was inactive, and no forces were applied to the wrist joint [21]. The active matching phase was considered complete when the end effector speed was lower than 2 /s for more than two seconds, at which the robot moved the wrist back to the neutral joint angle. Instructions emphasized accuracy, and participants did not receive any information about their execution to eliminate the possibility they recalibrate the responses during testing, based on direct knowledge of performance [21]. There were three separate task conditions: 1) Unimanual right (dominant) hand 2) Unimanual left (non-dominant) hand ) Bimanual. Participants performed 2 trials in each of the task conditions (12 per DoF [, ]), yielding a total of 72 trials. Trials across DoFs and conditions were presented in a pseudo-random fashion. The entire experiment lasted approximately 0 minutes. D. Data analysis Wrist joint rotations were recorded from the robots incremental encoders with microradian resolution. The acquired signals were post-processed with a third-order Savitzky- Golay low-pass filter (10 Hz cut-off frequency) and converted to angular displacement. Wrist proprioceptive acuity was measured using three outcome measures: matching error [22] and variable error [2]. Matching error is the overall deviation from the target and is defined as the absolute difference between the reference and the matched wrist angle in degrees: Matching Error = θ i θ T (1) where θ i is final position of the wrist on the i-trial and θ T is the target position. The total matching error is averaged across (= 12) repetitions of the same target in each of the 91

3 Passive Reaching Phase (ROBOT O) Active Matching Phase (ROBOT OFF) Return Phase (ROBOT O) Hold Time (000 ms) Hold Time (2000 ms) Hold Time (2000 ms) Fig. 2: The temporal sequence of the experimental paradigm. An auditory cue marks the beginning of the trial and the wrist is passively moved by the robotic device from the neutral configuration to the proprioceptive target. After a consistent holding time of 000 ms, the joint is passively returned to the initial starting position. After 2000 ms, an auditory cue indicates participants to start moving and actively reproduce, the joint configuration previously experienced. In this phase the robot is inactive. When the end effector speed is below a 2 /s for more than 2000 ms, the robot moves the wrist back to the neutral position and another trial can start. three tested DoFs and three tested conditions. The Variable error measures the performance consistency (precision), in terms of trial-by-trial repeatability. It is calculated as the standard deviation of the wrist matching position (θ i ) across all the (= 12) repetitions: V ariable Error = var(θ 1: ) (2) Wrist kinematics during the active matching phase were measured through the mean speed and the movement smoothness [2]. Mean speed is defined as Speed = Movement smoothness depends on the number of peaks in the matching movement speed profile: Smoothness = θ i 1 number of peaks( θ i ) Differences in proprioceptive acuity and kinematics were subjected to a 2 (DoF:, ) x 2 (Hand: left, right) x 2 (Task: unimanual, bimanual) Repeated Measures Analysis of Variance (RM AOVA) separately for each outcome measure. Results with p values <0.05 were considered significant. Significant main effects and interactions were compared using the Bonferroni procedure. A. Proprioceptive Acuity III. RESULTS Average matching error values were similar for the left ( X =., SE = 0. ) and right hand ( X =.2, SE = 0.2 ), F> 1.0 (Figure B). There was, however, a main effect of DoF (Figure A), with movements to ( X =.8, SE = 0.2 ) yielding smaller matching error values than movements to ( X =.7, SE = 0.2 ), F(1,216) = 9.007, p = The main () () effect of task was also significant (Figure A) [F(1,216) = , p<0,001], with smaller matching error values during the unimanual ( X =.6, SE = 0.2 ) than the bimanual condition ( X =.9, SE = 0.2 ). Analysis of variable error indicated that movements in the DoF ( X = 2.5, SE = 0.1 ) were more consistent than those made in the DoF ( X =.6, SE = 0.1 ), [F(1,216) =.27, p < (Figure A). In addition, movements were more consistent during the unimanual ( X = 2.9, SE = 0.1 ) compared to the bimanual condition ( X =., SE = 0.2 ), F(1,261) =.501, p<0.001 (Figure C). Variable error values were similar for the left ( X =.0, SE = 0.1 ) and right hand ( X =.1, SE = 0.1 ), F > 1.0 (Figure D). These results are clearly evident from Figure 5 in which is depicted the outcomes of the four performance indicators for the two hands and the two task conditions. The higher is the area, the higher is the value of the relative indicator for that hand/task condition. B. Kinematics Figure illustrates the wrist kinematics during the active matching phase. Average mean speed was significantly higher for unimanual movements ( X = 70.8 /s, SE = 2 /s), compared to bimanual movements ( X = 6.7, SE = /s), F(1,216) = 7,0682, p = (Figure A). There was also a significant main effect of DoF, with lower mean speed values for ( X = 8.5 /s, SE = 1.7 /s) than the DoF ( X = 86.0 /s, SE =.1 /s), F(1,216) = 197,60, p<0.001 (Figure A). Mean speed values were similar for the left ( X = 65.5 /s, SE = 2.1 /s) and right hand ( X = 69.0 /s, SE = 2.5 /s), F > 1.0 (Figure B). Average movement smoothness was significantly larger for unimanual movements ( X = 0.5, SE = 0.05), compared to bimanual movements ( X = 0., SE = 0.05), F(1,216) = 6,1192, p<0,001 (Figure C). In addition, movements were smoother when performed by the left ( X = 0.5, SE = 0.0) compared to the right hand ( X = 0., SE = 0.0), F(1,216)= 2,97, p<0,001 (Figure D). The main effect of DoF (: X = 0., SE = 0.02; : 0. = 0.5, SE = 0.0) was non-significant, 91

4 (# - 1) RH (# - 1) (deg/sec) RH (deg/sec) (deg) RH (deg) (deg) RH (deg) Matching error i-subject 2 mean A DoF B LH (deg) C DoF D.5 Variable error LH (deg) Fig. : Wrist proprioceptive acuity. A) Matching error and C) Variable error as a function of DoF (, ) and task (unimanual, bimanual). Black lines refer to unimanual performance. Orange lines refer to bimanual performance. Individual (black circles) and average (orange circle) asymmetries in B) Matching error and D) Variable error. Data points which fall below the 5 line (equality line) indicate a non-dominant left hand advantage, whereas data points which fall above the equality line indicate a dominant right hand advantage. Data points that fall directly on the equality line indicate that performance of both hands was equal. F > 1.0 (Figure C). IV. DISCUSSIO Upper limb asymmetries in motor behaviour have traditionally been viewed from the standpoint of preferred arm dominance for the generation of motor output. The tendency to use a preferred hand for motor activities is commonly indicated as handedness. It is now well established that approximately nine out of ten individuals prefer to use the right arm to perform selected tasks [2]. However, it is not clearly understood if there is a handedness in proprioceptive perception and if the motor dominance of one hand can be identified also in the sensory system. Furthermore, no evidences are reported related to differences between unimanual and bimanual processing of proprioceptive information. Accordingly, the present study examined manual asymmetries in wrist proprioceptive sensitivity and kinematics, and investigated whether proprioception and motor performance differ depending on whether the motor task is performed with one or two hands. With respect to our first aim, our data did not provide any evidence of manual asymmetries in proprioceptive acuity, as matching error and variable error values were similar for the two hands. This finding is incongruent with recent literature [8][25] demonstrating that the non-dominant limb has superior proprioceptive sensitivity than the dominant limb. In order to understand why we did not observe proprioceptive asymmetries when other researchers did [7], we delved into the literature and discovered that there are a number of older studies that also did not observe asymmetries in proprioceptive function [27][28][26]. At present it is not clear how to explain these divergent results. However, there is some evidence that proprioceptive asymmetry is site-specific [29][]. For example, Han et al. [29] examined active movement proprioception at four pairs of upper and lower limb joints and found that while proprioceptive accuracy A C DoF DoF Speed Smoothness 50 i-subject 0 mean B LH (deg/sec) D LH (# - 1) Fig. : Wrist kinematics. A) Mean speed and C) movement smoothness as a function of DoF (, ) and task (unimanual, black lines and bimanual, orange lines). Individual (black circles) and average (orange circle) asymmetries in B) mean speed and D) movement smoothness. Data points which fall below the 5 line (equality line) indicate a nondominant left hand advantage, whereas data points which fall above the equality line indicate a dominant right hand advantage. Data points on the equality line indicate that performance of both hands was equal. 915

5 scores of the dominant and non-dominant sides at the same joint were strongly positively correlated, scores at different joints were not significantly different from one another. The authors speculated that proprioceptive information sources are identical for the same joint on the two sides of the body (i.e., left and right elbow), but that the sources of proprioceptive information employed may differ at different sites of joints in the body (e.g., elbow and wrist). Indeed, in the present study we examined proprioceptive sensitivity at the wrist joint, whereas the studies reporting manual asymmetries [25][8] have focused on proprioception at the elbow joint. atural directions for future research include elucidating the contribution of specific receptors at different joints, utilizing longitudinal studies to examine proprioceptive changes across the lifespan, and investigating manual asymmetries in proprioceptive acuity in various clinical populations (e.g., stroke, peripheral neuropathy, Parkinson s disease). The second purpose of the current study was to investigate whether proprioceptive performance and movement kinematics differ depending on whether the motor task is performed with one or two hands. In line with our hypotheses, proprioceptive acuity and movement kinematics were influenced by the number of hands required during task performance. Results revealed that proprioceptive acuity was better and more consistent, and movements were faster during the unimanual than the bimanual condition. However, our data do not support recent findings suggesting that the central nervous system utilizes signals from the limb with the best proprioceptive acuity during bimanual movements [10]. Indeed, if that were the case we would have found a significant interaction between hand (left, right) and the task (unimanual, bimanual). Rather, our findings support behavioural motor control research indicating that decreased performance during the execution of bimanual movements arise from callosally mediated mutual inhibition. By this account, bimanual movements result in the transmission of rapid interhemispheric signals from each hemisphere. These signals activate inhibitory networks in the contralateral hemisphere, the end result of which is a slowing of the responses from both hands. The same rapid interhemispheric signals are transmitted during unimanual movements, but only from the responding hemisphere. In contrast to bimanual movements, the inhibitory influence does not affect reaction times as the inhibited hemisphere does not evoke a motor response. The present data suggest that the bimanual cost, often observed during motor execution, can also be found during bimanual proprioception. In addition, we also found that proprioceptive acuity was better and more consistent for the than the DoF. This anisotropy in proprioceptive acuity might be due to the distribution of receptors in the human wrist joint. Specifically, immunohistochemical studies have revealed that the highly innervated dorso-radial ligaments are stressed during human wrist, whereas the lesser innervated ligaments (e.g., volar ligaments) are primarily stressed during [2][]. This finding is also confirmed by empirical studies utilizing Matching error A B,9,6 2,9,2 Variable error,6,9 2,9, C D 69,2 /s 61,8 /s Speed Smoothness 0,59 0, /s 65,7 /s 0,5 0,7 Fig. 5: hand-task comparison for A) Matching Error, B) Variable Error, C) speed and D) smoothness psychophysical methods in which participants experienced two passive wrist movements and had to verbally indicate which action had the larger amplitude [5]. Results of that study demonstrated that the DoF has a lower ROM than the DoF, indicating that the proprioceptive acuity are due to differences in mechanoreceptor density and innervation in the human wrist joint. A number of neurological disorders (e.g. stroke; Parkinson s disease, peripheral neuropathy) result in sensory deficits and abnormal proprioceptive function, that have a negative influence on postural control, motor coordination, motor learning, and motor recovery [0]. Thus, the accurate quantification of joint position sense provides the clinician with important information regarding the patient s post-injury status, the efficacy of the therapeutic approaches. At present there is no established quantitative method for the clinical assessment of proprioception. However, recent advances in haptic interfaces designed for robot-aided sensorimotor rehabilitation may prove useful in the assessment of proprioceptive function [1]. The results of the current study have implications for robotic evaluations of proprioceptive acuity. First, given the evidence of site-specific proprioceptive function, it is critical that proprioceptive acuity be measured at the level of impairment. That is, although wrist and elbow JPS task could be used in individuals with stroke affecting only the upper extremity, individuals with Parkinson s disease should have proprioceptive acuity measured in the lower limbs. Second, given the differences in proprioceptive acuity between different DoFs, robotic evaluations should gather measures in more than one DoF in order to provide a more complete picture of proprioceptive function. Third, given that 916

6 proprioceptive acuity was similar between the two hands, clinicians should collect also data from the unimpaired limb as this would provide a baseline level of proprioceptive and kinematic performance. ACKOWLEDGEMET Authors wish to thank all the colleagues that volunteered to participate the study. The technology and methodology described in this paper is protected by US patent Serial o. 62/16,065 (Systems And Methods For Assessing And Training Wrist Joint Proprioceptive Function). RERECES [1] J. B. Hellige, Hemispheric asymmetry: What s right and what s left, vol. 6, Harvard University Press, 199. [2] M. Annett, Handedness and brain asymmetry: The right shift theory. Psychology Press, [] H. Liepmann, Apraxie. Ergb Gesamte Med., vol. 1, pp , [] S. V. Adamovich, et al, Pointing in D space to remembered targets. I. Kinesthetic versus visual target presentation. J europhys., vol. 79, pp , [5] A. Vucetic, M. Holmes, R. Adams, G. Waddington, Bilateral associations of low level unilateral performance: an unremarked aspect of limb control, J Mot Behav., vol. 0, pp. 79-8, [6] G. Waddington, and R. Adams, Discrimination of active plantar flexion and inversion movements after ankle injury, Aust. J Physiother., vol. 5, pp. 7-1, [7] D.J. Goble, S.H. Brown, Dynamic proprioceptive target matching behavior in the upper limb: effects of speed, task difficulty and arm/hemisphere asymmetries, Behav Brain Res., vol. 200, pp. 7-1, [8] D.J. Goble, and S.H. Brown, Upper limb asymmetries in the perception of proprioceptively determined dynamic position sense, J. Exp. Psychol. Human Percept. Perform., vol. 6, pp , [9] D.J. Goble, B.C. oble, and S.H. Brown, Proprioceptive target matching asymmetries in left-handed individuals, Exp. Brain Res., vol. 197, pp. 0-08, [10] J. D. Wong, E. T. Wilson, D. A. Kistemaker, and P. L. Gribble, Bimanual proprioception: are two hands better than one?, J europhys., vol. 111, pp , 201. [11] S. P. Swinnen, and. Wenderoth, Two hands, one brain: cognitive neuroscience of bimanual skill. Trends Cogn Sci., vol, 8, pp , 200. [12] C. M. L. Hughes, and E.A. Franz, Goal-related planning constraints in bimanual grasping and placing of objects. Exp Brain Res., vol. 188, pp , [1] C. M. L. Hughes, and E.A. Franz, Experience-dependent effects in unimanual and bimanual reaction time tasks in musicians. J Mot Behav., vol. 9, -8, [1] G. Baud-Bovy and P. Viviani, Pointing to kinesthetic targets in space. J eurosci., vol. 18, pp , [15] J. Lonn, et al. Position sense testing: influence of starting position and type of displacement. Arch Phys Med Rehab., vol. 81, pp , [16] D.J. Goble, Proprioceptive acuity assessment via joint position matching: from basic science to general practice. Phys Ther., vol. 90, pp , [17] R. C. Oldfield, The assessment and analysis of handedness: the Edinburgh inventory. europsychologia., vol. 9, 97-11, [18] L. Masia, et al. Eye-hand coordination during dynamic visuomotor rotations. PloS One, vol., pp. e700, [19] D. J. Goble, M. A. Mousigian, and S. H. Brown, Compromised encoding of proprioceptively determined joint angles in older adults: the role of working memory and attentional load., Exp. Brain Res., vol. 216, pp. 5-0, [20] A. Gay, K. Harbst, K. R. Kaufman, D. K. Hansen, E. R. Laskowski, and R. A Berger, ew method of measuring wrist joint position sense avoiding cutaneous and visual inputs., J. euroeng. Rehabil., vol. 7, p. 5, [21] J. Paillard and M. Brouchon, Active and passive movements in the calibration of position sense, europsychol. Spat. Oriented Behav., vol. 11, pp. 7-55, [22] R. Schmidt and T. Lee, Motor Control and Learning. Human kinetics [2] S. S. P. Dukelow, et al., Quantitative Assessment of Limb Position Sense Following Stroke, eurorehabil eural Repair., vol. 2, pp , [2] R. L. Sainburg, Evidence for a dynamic-dominance hypothesis of handedness, Exp Brain Res., vol. 12, pp , [25] D. E. Adamo, and B. J. Martin, Position sense asymmetry, Exp Brain Res., vol. 192, pp , [26] J. E. Bullock-Saxton, W. J. Wong, and. Hogan. The influence of age on weight-bearing joint reposition sense of the knee, Exp Brain Res., vol. 16, pp , [27] R.G. Carson, D. Elliott, D. Goodman, and J. Dickinson, Manual asymmetries in the reproduction of a -dimensional spatial location. europsychologia., vol. 28, pp , [28] C.D. Chapman, M. D. Heath, D. A. Westwood, and E. A. Roy, Memory for kinesthetically defined target location: evidence for manual asymmetries. Brain Cogn., vol. 6, pp , [29] J. Han, et al. Proprioceptive performance of bilateral upper and lower limb joints: side-general and site-specific effects, Exp Brain Res., vol. 226, pp. 1-2, 201. [0] S. M. Schabrun and S. Hillier, Evidence for the retraining of sensation after stroke: a systematic review, Clin. Rehabil., vol. 2, pp. 27-9, [1] J. Han, G. Waddington, R. Adams, J. Anson, and Y. Liu, Assessing proprioception: A critical review of methods, J. Sport Heal. Sci., no. February, pp. 1-11, [2] S. Petrie, J. Collins, M. Solomonow, C. Wink, and R. Chuinard, Mechanoreceptors in the palmar wrist ligaments, J. Bone Joint Surg Br., vol. 79, pp. 9-96, [] E. A. Roy, and C. MacKenzie, Handedness effects in kinesthetic spatial location judgements, Cortex., vol. 1, pp , [] E. Hagert, Proprioception of the wrist joint: a review of current concepts and possible implications on the rehabilitation of the wrist, J Hand Ther., vol. 2, pp. 2-16, [5] L. Cappello,. Elangovan, S. Contu, S. Khosravani, J. Konczak, and L. Masia, Robot-Aided Assessment of Wrist Proprioception, Front Hum eurosci., vol. 9, pp. 1-8,