Prediction and Fitting of Nonlinear Dynamic Grip Force of the Human Upper Limb Based on Surface Electromyographic Signals

This study aimed to predict and fit the nonlinear dynamic grip force of the human upper limb using surface electromyographic (sEMG) signals. The research employed a time-series-based neural network, NARX, to establish a mapping relationship between the electromyographic signals of the forearm muscle...

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Veröffentlicht in:	Sensors (Basel, Switzerland) Switzerland), 2025-01, Vol.25 (1), p.13
Hauptverfasser:	Cai, Zixiang, Qu, Mengyao, Han, Mingyang, Wu, Zhijing, Wu, Tong, Liu, Mengtong, Yu, Hailong
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Adult Algorithms Electrodes Electromyography - methods Force Forearm - physiology grip force prediction Hand Strength - physiology Hands Humans Implants, Artificial Investigations Male Muscle contraction Muscle, Skeletal - physiology NARX neural network Neural networks Neural Networks, Computer nonlinear dynamic grip force Nonlinear Dynamics Prostheses Prosthesis R&D Research & development Sensors Signal Processing, Computer-Assisted surface electromyographic signals Upper Extremity - physiology Young Adult
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