機能的電気刺激に基づく運動エンハンス/レジストシステム

抄録

In contrast to voluntary movement, muscle contraction stimulated by functional electrical stimulation (FES) is more likely to cause muscle fatigue. This paper proposes a method that amplifies voluntary movement using FES and motion classification to intensify muscle workouts, thereby speeding up muscle fatigue. Motion classification was performed with a probabilistic neural network using feature patterns extracted from Mechanomyogram (MMG). A compact and lightweight electrical stimulation device delivered electrical signals to subjects’ arm via stimulation electrodes. The study performed three experiments: voluntary movement, FES, and voluntary movement amplification. Experimental results demonstrated that the proposed method caused the highest intensity of muscle contraction, which could be effective for training.