Muscle activation state revealing system based on sEMG measurement of leg muscles during pedaling exercise

Abstract

Recently, the movement and muscle usage principles have been elucidated by analyzing the kinematic and dynamic parameters of various body parts during movements and exercises. Feedback training methods based on these findings have also been proposed to improve athlete performance. For instance, prior research on pedaling exercises has shown that considering muscle contraction patterns and activation states can help cyclists avoid muscle fatigue. However, few studies have investigated the effects of both muscle contraction patterns and muscle activation states during pedaling exercises. Therefore, this study proposes a novel pedaling training system that provides visual and auditory feedback on the muscle contraction and activation of a cyclist's lower limb during pedaling exercise. This may help cyclists better understand and optimize muscle contraction and activation patterns. The proposed system visualizes muscle contraction patterns and activation states during pedaling motion and generates sound for cyclists at the ideal crank angle for optimal muscle activation timing. This allows cyclists to recognize the optimal timing for muscle activation based on these patterns. The effectiveness of the proposed system was validated by performing a trial pedaling training session for an amateur cyclist and comparing the muscle contraction and activation states among the pre-trial, feedback-trial, and post-trial. The experimental results confirmed that the proposed system improves muscle activation timing effectively during pedaling training.

Keywords

• semg measurement
• visual feedback
• auditory feedback
• pedaling motion
• muscle contraction patterns