Analysis of EMG and Biomechanical Features of Sports Aerobics Movements

Analysis of EMG and Biomechanical Features of Sports Aerobics Movements Jingjing Wang* WuHan Sport University, Wuhan, Hubei, 430070, China *itrazyl@163.com Abstract To analyze electromyography (EMG) and biomechanical features of sports aerobics movements. The 20 athletes and 20 healthy college students are chosen as the observation group and the control group. The EMG and biomechanical features of flexors and extensors are examined when the two groups of samples finish movements such as jumping. Samples of the observation group and the control group are compared in terms of their flexor and extensor peak torque, overall power, average power and degree of movement fatigue. The data differences show statistical significance (P<0.05). Compared with the ordinary people, sports aerobics athletes have a stronger muscular contraction; a higher flexor and extensor peak torque, overall power and average power; and a lower degree of movement fatigue. All this suggests a stronger athletic ability of sports aerobics athletes. Key words: Sports Aerobics, Hip Movement; Electromyography (Emg), Biomechanical Features 0. INTRODUCTION Sports aerobics is a kind of competitive sports integrating music and dancing(kim,2002). While performing sports aerobics, the athletes usually show a wide range of movements, of which the hip movements and jumping are common to see(maia, Rodrigues-De-Paula and Magalhães,2013). Research points out that electromyography (EMG) and biomechanical features of sports aerobics athletes, while accomplishing different movements, are different(pinto, Cadore and Alberton,2011). Concerning the difference, this paper selects 20 athletes and 20 healthy students, and divide them into the observation group and the control group, respectively(verikas, Parker and Bacauskiene,2017). A series of movements, such as jumping, is examined to further analyze EMG and biomechanical features of sports aerobic movements. Below is the research report. 1. MATERIALS AND METHODS 1.1 General materials As mentioned above, 20 athletes and 20 healthy college students are chosen, and divided them into the observation group and control group, respectively. The basic data of samples in the two groups are presented in Table 1: Table 1. Basic data of chosen samples Gender ratio (males Groups Age (Years old) Weight (kg) Health status to females) Observation group 1:1 21.2±2.0 65.9±1.5 Healthy Control group 1:1 21.3±2.1 66.0±1.4 Healthy p >0.05 >0.05 >0.05 >0.05 As one notices the observation group in Table 1, the ratio of males to females is 1:1; the age of samples averages at (21.2±2.0) years old; their weight averages at (65.9±1.5) kg; and all of them are healthy. The basic data of the samples chosen from the two groups are not statistically significant (P>0.05). This provides the basis for their comparability. 1.2 Inclusion and elimination criteria 1.2.1 Inclusion criteria (1) All samples selected shall have no historical disease records and all shall be healthy; (2) The samples selected shall be aged no older than 25 years old; (3) All samples selected shall finish corresponding movements as required by the researcher. 1.2.2 Elimination criteria (1) Samples with records of major diseases or poor in health are eliminated; (2) Samples aged above 25 years old are eliminated; 473

(3) Samples unable to finish the required movements are eliminated. 1.3 Methods 1.3.1 Infrared monitoring The same infrared monitoring method is adopted to the two groups of samples: (1) Prepare six sets of 3D cameras to capture infrared rays irradiated by samples during their movements from different angles; (2) Use the high-speed infrared long-range movement capture to capture movement situations of samples; (3) Require all the 40 samples to stand up, set the six cameras in the front, back, left front, left back, right front and right back of the responders. Put every set of camera at an equal distance away from the responders, and keep the responders at the center of a circle; (4) Require responders to make corresponding movements three times according to the requirement of the researcher; (5) Collect muscular movement situations of responders, including flexor and extensor indexes, and analyze EMG and biomechanical features of sports aerobics movements. 1.3.2 Constant speed muscular test method The onsite measurement method is adopted to observe biomechanical features of flexors and extensors of the two groups of samples. The constant speed muscle strength test system features BIODEXYSTEM 3. Below are specific steps of the constant speed muscular test method: (1) Require samples of the two groups to take adequate sleep, and get prepared by warm-up; (2) Fix the responders according to requirements of responders; (3) Fix joints of responders on the test instrument, and keep the movement axial of responders hip joint and the test rotator to be on the same straight line; (4) Require all responders to hold the test chair by two hands, and test flexors and extensors of responders in the two groups; (5) Keep the movement speed of responders in the two groups at an average speed of 30 /s and test five times in total, and ask the responders to take a good rest after the test. 1.3.3 EMG test method The EMG test method for the two groups is the same. The electrode should be connected with the muscles in both groups. The amplification system is adopted to amplify biological current features at different states. The biological features are then displayed in the form of oscillography. Then, EMG of the responders is judged. The motor neurons and the muscle fibers at the disposal of the motor neurons both belong to the same movement unit. When the movement unit is under a relaxing state, the potential remains the same. At the moment, the graph on the oscilloscope is mostly demonstrated in the form of straight lines. When the human body is at a moving status, the muscle will be at a contraction status. At the moment, the biological current of the muscles will be changed to some extent, which will lead to changes of EMG. The more movement units participate in the activity, the more serious the overlapping of potential is, and the more difficult it is to tell them apart from each other. The potential of various movement units influences each other, which can disturb accuracy of judgment. This paper just monitors the hip joint movements when responders are jumping. This can effectively avoid the occurrence of the above problem. 1.4 Observational indexes (1) Compare the peak torque of flexors and extensors of samples hip joint in the two groups; (2) Compare the total work of flexors and extensors of samples in the two groups; (3) Compare the average power of samples hip joint in the two groups; (4) Compare the degree of work fatigue of samples in the two groups; (5) Observe the EMG fluctuations of athletes. 1.5 Statistical method The statistical software, SPSS 20.0, is employed for data processing. The count is represented by percentage (%), while the measurement is represented by (average±standard deviation). When p<0.05, it is thought that the data difference has statistical difference. 2 RESULTS 2.1 Comparison of peak torque of samples hip joint flexors in two groups 474

Table 2. Comparison of peak torque of hip joint flexors and extensors of the control group and the observation group Hip joint Observation group (PT, Nm) Control group (PT, Nm) p Flexors Left 266.0±10.0 178.9±20.6 <0.05 Right 285.4±11.0 200.8±12.5 <0.05 Extensors Left 152.9±29.6 122.3±30.0 <0.05 Right 168.5±20.9 140.6±33.4 <0.05 Results suggest that data difference of peak torque of hip joint flexors and extensors between the two groups show statistical significance (P<0.05). Compared with the control group, the observation group shows a higher peak torque in terms of the left and right flexors and extensors. This means outperformance of the observation group in terms of the athletic ability. 2.2 Comparison of total work of flexors and extensors in two groups Table 3. Comparison of total work of flexors and extensors of the control group and the observation group Hip joint Observation group (MW, J) Control group (MW, J) p Flexors Left 880.9±15.6 685.0±20.8 <0.05 Right 986.7±13.5 730.5±14.0 <0.05 Extensors Left 740.4±30.4 569.3±20.5 <0.05 Right 810.6±21.7 660.6±30.0 <0.05 As one notices the data of the observation group in Table 3, the left flexor total work is (880.9±15.6) J; the right flexor total work is (9,876±13.5) J; the left extensor total work is (740.4±30.4) J; and the right extensor total work is (810±21.7) J. The data difference between the control group and the observation group in terms of the above indexes has statistical significance (P<0.05). The flexor and extensor total work of the observation group is higher than that of the control group. 2.3 Comparison of average power of flexors and extensors in two groups Table 4. Comparison of average power of flexors and extensors of the control group and the observation group Hip joint Observation group (AP, W) Control group (AP, W) p Flexors Left 145.8±20.9 74.0±11.6 <0.05 Right 158.4±12.6 90.4±13.5 <0.05 Extensors Left 140.3±22.8 63.2±15.5 <0.05 Right 150.6±30.4 90.0±10.0 <0.05 Table 4 presents average power of left and right flexors and extensors of the observation group and the control group, respectively. In terms of the observation group, the left flexor average power is (145.8±20.9) W; and the right flexor average power is (158.4±12.6) W. In terms of the control group, the left extensor average power is (140.3±22.8) W and the right extensor average power is (150.6±30.4) W. By comparing the two groups in terms of their flexor and extensor average power the data difference shows statistical significance (P<0.05). The flexor and extensor average power of the observation group is obviously higher. 2.4 Comparison of the degree of movement fatigue of flexors and extensors in two groups Table 5. Comparison of the degree of movement fatigue of flexors and extensors of the control group and the observation group Observation group (WF, %) Control group (WF, %) p Flexors 41.6±5.8 60.9±4.5 <0.05 40.0±6.0 56.9±10.2 <0.05 Extensors 52.4±4.3 67.9±3.9 <0.05 50.3±4.1 63.4±3.8 <0.05 Table 5 shows that the differences of the degree of movement fatigue of flexors and extensors of the control group and the observation group. In terms of the observation group, the left flexor movement fatigue is (41.6±5.8) % and the right flexor movement fatigue is (40.0±6.0) %. In terms of the control group, the left extensor movement fatigue is (52.4±4.3) W, and the right extensor movement fatigue is (50.3±4.1) W. The data difference between the two groups is statistically significant (P<0.05). The flexor and extensor movement 475

fatigue of the observation group is lower. This means that accomplishment of the same movement causes less influence on the body of samples in the observation group. 2.5 Athletes hip joint EMG The surface EMG of athletes is shown in Table 1: User HCI system Data mining and training strategy determination Data warehouse managing system Model library managing system Knowledge base managing system Data warehouse Model base Knowledge base (a) tall Height short middle strength Flexibility speed strong weak good common bad fast slow Y Flexibility Y N N Y N good common bad Y N N (b) Figure 1. Surface EMG of Athletes Model By observing Fig. 1, huge fluctuations can be observed in the surface EMG of athletes, meaning that athletes have stronger muscular contraction. This cannot be separated from athletes long-term training. Conversely, the EMG fluctuations of college students in the control group are not so dramatic. This indicates the muscular contraction of college students is inferior to that of athletes. 3 DISCUSSIONS 3.1 Jumping movements in sports aerobics Sports aerobics has requirements about athletes accomplishment of different movements. Only when these movements are made up to standards can sports aerobics deliver a sense of aesthetics and achieve the effect of body-building. This paper adopts jumping movements as a case study (Alberton, Pinto and Cadore,2014). In general, the horizontal speed of the athlete s gravity center during the jumping process gradually decreases, while the vertical speed is on an increase trend. The actually-measured increase rate stays at around 2.11 m/s. 476

Angle control of the knee joint at the maximum buffer moment can promote improvement of jumping movements. The actual measurement and analysis results suggest that it is desirable to control the angle at 141.98 ±4.51 (Barton, Balachandar and Lack,2014). Research has shown that the buffer duration has a close bearing on the overall time taken by the jumping movement. Compared with high jump and long jump, jumping in sports aerobics takes a longer time. This can exert certain degree of influence on athletes movement expansion. The movements can be adjusted through shortening of the jumping duration. When the body of the athlete stays in the air, the athlete s shoulders and hip can reach a peak value. In order to guarantee harmony of the jumping movements, the athlete can swing the legs and control their movement range and strength. In this way, the power generation of the whole body can be more proportional to achieve overall harmony of jumping and jumping movement expansion. When an athlete is jumping, his leg swinging is shown in Fig. 2. (a) (b) Figure 2. Leg swinging of the athlete during jumping 3.2 EMG Electromyography (EMG) is a method which takes down the electrical activity of muscles when the muscles are static or contracting using the electronic instruments, and also a method to test neural and muscular excitement and transmission using electrical stimulation. 477

Muscle cells are highly exciting. The characteristic makes muscle cells similar to neural cells. Both cells fall under the category of excitable cells. When muscle cells are gradually excited by activities of human body tissues, the response made in the very beginning is usually action potential, or the so-called conductible potential. It is distributed on two sides of the cell membrane. Contraction of muscle tissues and cells are transmitted through the action potential. During the process, the cell membrane serves as the medium, and the contraction is transmitted to the depth of cells to further stimulate excitement of muscle cells and tissues(dietz, Macauda and Schraflaltermatt, 2015). When muscle fibers are not excited, there is only resting potential. The potential difference does not exist or is too small to be captured. Nor will it cause response of the cell membrane. The cells and tissues will not transmit relevant information via the cell membrane to the deeper areas. The phenomenon is called the membrane potential or the cross-membrane resting potential. (See Fig. 3) (a) (b) Figure 3. Simulation of the muscle excitement transmission factor When the human body is moving, the muscle tissues and the neural cells will make response to the body movement. It is mainly reflected as decrease of the membrane potential. When the movement reaches certain intensity, the membrane potential can decrease swiftly within a short period of time. This will give rise to potential difference. The changing speed is decided by sensitivity of the muscular and neural system and by the movement range (Furuya, Aoki and Nakahara,2012). When the membrane potential turns from negative to positive, the change will continue to alternate between positive and negative. The reversible change is called the action potential. The minor changes in EMG can be captured and observed by the membrane potential. Generally, contraction of muscle cells (fibers) is controlled by the neural system, and the motor neurons are the direct control tissues of the contraction process. When the motor neurons transmit the relevant sports information via the neural system and reach the muscle cells, the action potential will quickly be generated and transmitted to the nerve endings to cause the follow-up excitement reflection. This is the basic principle of EMG measurement and capturing of the biomechanical phenomena. The extracellular record electrical machinery transmits the transmembrane resting potential and potential difference of muscles to the EMG machine. The smoothing equipment is adopted to remove noises, and amplify them to more clearly observe potential changes, including the amplitude of variation, peak value, low ebb, frequency and waveform, and to form EMG as well. 3.3 Biomechanical features In terms of biomechanical features, the hip joint is adopted as the focus of research. The hip joint biomechanical features of sports aerobics athletes and college students during their movement are different from each other(jobe, Tibone and Perry,1983). To be specific, when the angular speed increases, the PT value of flexors and extensors of the observation group and the control group is both on a decreasing trend. No matter how the angular speed changes, the decreasing trend will not show obvious changes, but stay at a relatively constant status. When such difference is reflected as data, the PT value of the observation group is higher than that of the control group. When the movement speed reaches 30 /s, the PT value of the observation group and the control group is both high, both being above 120 /s, and their difference is significant. Then, the change 478

becomes increasingly significant. The amplitude of variation and the amplitude of movement are generally positively correlated with each other. When the movement speed reaches 120 /s, the difference between the two groups decreases significantly. When the movement speed reaches 300 /s, the difference between the two groups is no longer significant. (See Fig. 4) Figure 4. EMG Biomechanical model simulation results Further analysis shows that the relative peak torque of the hip joint extensors in the control group is slightly lower than that of the observation group. However, the relative peak torque of the hip joint extensors changes along with changes of the movement speed. A significant negative correlation is observed between the hip joint extensors and the movement speed. To be specific, the faster the movement speed is, the lower the relative peak torque value of hip joint extensors is. When the movement speed is 30 /s, the relative peak torque of extensors of the observation group, captured at any period of time, is higher than that of the control group. Besides, the difference is highly significant. When the movement speed reaches 120 /s and 300 /s, the difference shows no obvious changes. However, at other periods of time, the movement speed of the observation group can lead to changes of the relative peak torque of extensors. Though the relative peak torque of extensors of the control group is also influenced by the movement speed, the amplitude of variation is smaller. This is closely related with the variation of an element. (See Fig. 5) Figure 5. Chemical generation process of the element which can influence the physical ability 479

Research shows that the total work of flexors in the two groups both decreases along with increase of speed. Besides, the total work of extensors is obviously higher than that of flexors. In the control group, when the movement speed reaches 30 /s, the difference has been extremely significant. The total work of flexors is huge, and the total work of extensors is small. When the movement speed reaches 120 /s and 300 /s, respectively, the total work of flexors and extensors is still different, but the difference has been relatively less significant. In the observation group, when the speed reaches 30 /s, the total work of extensors is relatively large, but that of flexors is relatively small. The difference between the two is significant. When the movement speed increases to 120 /s and 300 /s, the total work of flexors and the difference of the total work between flexors and extensors becomes more and more significant. On the whole, changes of the difference between the total work of flexors and extensors in the control group is negatively correlated with the movement speed. Conversely, a positive correlation is observed between the changing difference between flexors and extensors and the movement speed. When the movement speed reaches above 120 /s, the positive correlation becomes even more significant. 4. CONCLUSIONS Analysis shows that mechanical features of the hip joint of samples in the two groups are different, and that the differences follow certain rules. Compared with the ordinary people, sports aerobics athletes have a stronger muscular contraction; a higher flexor and extensor peak torque, overall power and average power; and a lower degree of movement fatigue. All this suggests a stronger athletic ability of sports aerobics athletes. REFERENCES: Alberton C L, Pinto S S, Cadore E L. (2014) Oxygen uptake, muscle activity and ground reaction force during water aerobic exercises. International Journal of Sports Medicine, 35(14), pp.1161-9. Barton C, Balachandar V, Lack S. (2014) Patellar taping for patellofemoral pain: a systematic review and meta-analysis to evaluate clinical outcomes and biomechanical mechanisms. British Journal of Sports Medicine, 48(6), pp.417. Dietz V, Macauda G, Schraflaltermatt M, et al. (2015) Neural coupling of cooperative hand movements: a reflex and FMRI study. Cerebral Cortex, 25(4), pp.948. Furuya S, Aoki T, Nakahara H. (2012) Individual differences in the biomechanical effect of loudness and tempo on upper-limb movements during repetitive piano keystrokes. Human Movement Science, 31(1), pp.26-39. Jobe F W, Tibone J E, Perry J. (1983) An EMG analysis of the shoulder in throwing and pitching. A preliminary report. American Journal of Sports Medicine, 11(1), pp.3. Kim C N. (2002) The Kinematical Analysis of Straddle Jump to Push up Motion on Sports Aerobics. Nature, 12(2), pp.77-90. Maia A C, Rodrigues-De-Paula F, Magalhães L C. (2013) Cross-cultural adaptation and analysis of the psychometric properties of the Balance Evaluation Systems Test and MiniBESTest in the elderly and individuals with Parkinson's disease: application of the Rasch model. Brazilian Journal of Physical Therapy, 17(3), pp.195. Pinto S S, Cadore E L, Alberton C L. (2011) Cardiorespiratory and neuromuscular responses during water aerobics exercise performed with and without equipment. International Journal of Sports Medicine, 32(12), pp.916. Verikas A, Parker J, Bacauskiene M. (2017) Exploring relations between EMG and biomechanical data recorded during a golf swing. Expert Systems with Applications, 88, pp.109-117. 480