Prediction and classification of sEMG-based pinch force between different fingers

Author:

Wu YanshengORCID,Liang ShiliORCID,Ma YongkaiORCID,Li BowenORCID

Funder

Department of Science and Technology of Jilin Province

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference65 articles.

1. Electromyography data for non-invasive naturally-controlled robotic hand prostheses;Atzori;Scientific Data,2014

2. Simultaneous force regression and movement classification of fingers via surface EMG within a unified Bayesian framework;Baldacchino;Frontiers in Bioengineering and Biotechnology,2018

3. Performance comparison of artificial neural network and Gaussian mixture model in classifying hand motions by using sEMG signals;Baspinar;Biocybernetics and Biomedical Engineering,2013

4. A hand-modeled feature extraction-based learning network to detect grasps using sEMG signal;Baygin;Sensors,2022

5. Stable responsive EMG sequence prediction and adaptive reinforcement with temporal convolutional networks;Betthauser;I.E.E.E. Transactions on Bio-Medical Engineering,2019

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