From Forearm to Wrist: Deep Learning for Surface Electromyography-Based Gesture Recognition

• Published in: IEEE transactions on neural systems and rehabilitation engineering Vol. 32; p. 1
• Main Authors: He, Jiayuan, Niu, Xinyue, Zhao, Penghui, Lin, Chuang, Jiang, Ning
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.01.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial neural networks; Convolutional neural networks; Deep Learning; Electrodes; Electromyography; Electromyography - methods; Forearm; Gesture recognition; Gestures; Humans; Machine learning; Myoelectric control; Myoelectricity; Neural networks; Prostheses; Prosthetics; surface electromyography (sEMG); Thumb; Wearable computers; Wrist

Though the forearm is the focus of the prostheses, myoelectric control with the electrodes on the wrist is more comfortable for general consumers because of its unobtrusiveness and incorporation with the existing wrist-based wearables. Recently, deep learning methods have gained attention for myoele...