The effects of trunk kinematics and EMG activity of wheelchair racing T54 athletes on wheelchair propulsion speeds

Abstract

Background The purpose of this study is to examine the impact of trunk kinematic characteristics and trunk muscle electromyography (EMG) activity on propulsion speeds in wheelchair racing T54 athletes. Method The Vicon infrared high-speed 3D motion capture system was utilized to acquire kinematic data of the shoulders, elbows, wrists, and trunk from twelve T54 athletes at four different speeds (5.55 m/s, 6.94 m/s, 8.33 m/s, and personal maximum speed). Additionally, the Trigno Wireless EMG system was employed to collect synchronous surface electromyography (EMG) data from the rectus abdominis and erector spinae muscles. The kinematics and EMG data of the trunk were compared across various wheelchair propulsion speeds while also examining the correlation coefficient between wheelchair propulsion speeds and: (1) the range of motion of upper limb joints as well as the trunk; (2) the maximum angular velocities of the upper limbs joints as well as the trunk; and (3) rectus abdominis and erector spinae EMG activity. Two multiple linear stepwise regression models were utilized to examine the impact of variables that had been identified as significant through correlation coefficient tests (1) and (2) on propulsion speed, respectively. Results There were significant differences in the range of motion (p<0.01) and angular velocity (p<0.01) of the athlete’s trunk between different propulsion speeds. The range of motion (p<0.01, r = 0.725) and angular speed (p<0.01, r = 0.882) of the trunk showed a stronger correlation with propulsion speed than did upper limb joint movements. The multiple linear stepwise regression model revealed that the standardized β values of trunk motion range and angular velocity in athletes were greater than those of other independent variables in both models. In terms of the EMG variables, four of six variables from the rectus abdominis showed differences at different speeds (p<0.01), one of six variables from the erector spinae showed differences at different speeds (p<0.01). All six variables derived from the rectus abdominis exhibited a significant correlation with propulsion speed (p<0.05, r>0.3), while one variable derived from the erector spinae was found to be significantly correlated with propulsion speed (p<0.01, r = 0.551). Conclusion The movement of the trunk plays a pivotal role in determining the propulsion speed of wheelchair racing T54 athletes. Athletes are advised to utilize trunk movements to enhance their wheelchair’s propulsion speed while also being mindful of the potential negative impact on sports performance resulting from excessive trunk elevation. The findings of this study indicate that it would be beneficial for wheelchair racing T54 athletes to incorporate trunk strength training into their overall strength training regimen, with a specific emphasis on enhancing the flexion and extension muscles of the trunk.

Embedded Machine Learning System for Muscle Patterns Detection in a Patient with Shoulder Disarticulation

“…Specifically, electromyography (EMG) recording has experienced significant benefits through the transition from wired to wireless acquisition systems. The growing utilization of wireless EMG devices can be attributed to the necessity of validating electrophysiological measurements in diverse settings and situations [ 16 , 17 , 18 ], as well as their adaptability to various Human Device Interfaces (HDIs) [ 19 , 20 , 21 ] where they are expected to optimize usability, portability, and reliability in remote operational environments. Consequently, this enables the formulation of novel experimental protocols applicable in everyday contexts.…”