JOURNAL ARTICLE

Grasping Pattern Recognition and Grasping Force Estimation For Prosthetic Hands

Bingke ZhangGuoliang ZhongHua Deng

Year: 2016 Journal:   ITM Web of Conferences Vol: 7 Pages: 09016-09016   Publisher: EDP Sciences

Abstract

\nHuman’s movement can be decoded by surface electromyography (EMG), and the prosthetic hand can be controlled freely through EMG signal. This paper proposes a grasping pattern and force synchronized decoding method for prosthetic hands. Considering pattern recognition and force estimation simultaneously, this paper analyzes whether different muscle contraction levels affect pattern recognition and whether different grasping modes have impact on force estimation, then proposes two schemes to complete EMG simultaneously decoding. Experiments compare the accuracy of the two methods. The results show that there is no much difference between two methods in force estimation, the former’s accuracy of pattern recognition is a little higher than the latter.\n

Keywords:
Electromyography Decoding methods Computer science Artificial intelligence Pattern recognition (psychology) SIGNAL (programming language) Computer vision Prosthetic hand Speech recognition Physical medicine and rehabilitation Algorithm

Metrics

3
Cited By
0.34
FWCI (Field Weighted Citation Impact)
11
Refs
0.66
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Muscle activation and electromyography studies
Physical Sciences →  Engineering →  Biomedical Engineering
EEG and Brain-Computer Interfaces
Life Sciences →  Neuroscience →  Cognitive Neuroscience
Neuroscience and Neural Engineering
Life Sciences →  Neuroscience →  Cellular and Molecular Neuroscience
© 2026 ScienceGate Book Chapters — All rights reserved.