Cross-Comparison of EMG-to-Force Methods for Multi-DoF Finger Force Prediction Using One-DoF Training

• Published in: IEEE access Vol. 8; pp. 13958 - 13968
• Main Authors: Chen, Yuyang, Dai, Chenyun, Chen, Wei
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial neural networks; Crosstalk; Degrees of freedom; Electromyography; EMG signal processing; EMG-force prediction; Fingers; Force; Force measurement; Forearm; Muscles; Neural networks; Recurrent neural networks; Training

Surface electromyography (sEMG) signal is one of the widely applied biological signals in the research field of the force intention prediction. However, due to the severe cross-talk issue of sEMG signals during fine hand contractions, few studies have related sEMG to multiple degree-of-freedom (DoF)...