Portable sEMG-Controlled Hand Electrical Stimulation System

Contralateral controlled functional electrical stimulation (CCFES) serves as a stroke rehabilitative intervention capable of inducing bilateral hands’ engagement in restorative movements. Clinical practice has shown that CCFES significantly improves hand movement control and dexterity. Existing CCFES systems, leveraging technologies such as myoelectric sensors, flexion sensors, and Lidar, can trigger movements but lack real-time muscle status feedback and a rehabilitation movement control strategy, limiting assistance in intricate daily activities. This study introduces an innovative, portable CCFES system based on surface electromyography (sEMG). This system facilitates adaptive amplitude modulation using bilateral hand surface electromyographic signals and enables real-time transitions between rehabilitation movements according to user intent. In the domain of online gesture recognition, the system demonstrated exceptional performance, achieving an average F1 score of 0.935. Furthermore, the system possesses the capability to adaptively modulate stimulation amplitudes by evaluating the differences in sEMG signals between the participant’s hands. The conclusive “object taking” experiment substantiates the system’s potential applicability in the rehabilitation training of daily activities.

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Publication Details

Journal
IEEE Sensors Journal
Published
2024-12-04
DOI
https://doi.org/10.1109/jsen.2024.3506788
Citations
2
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.69

Funders

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article

Portable sEMG-Controlled Hand Electrical Stimulation System

Shuxian Zhang, Longhan Xie, Yumeng Cai, Zhitao Chen et al.
2 citations
IEEE Sensors Journal
EEG and Brain-Computer Interfaces
0.69
article

Portable sEMG-Controlled Hand Electrical Stimulation System

Shuxian Zhang, Longhan Xie, Yumeng Cai, Zhitao Chen, Hao Huang, Shuxin Liu, Li Huang, Yan Chen
article en
2 citations

Abstract

Contralateral controlled functional electrical stimulation (CCFES) serves as a stroke rehabilitative intervention capable of inducing bilateral hands’ engagement in restorative movements. Clinical practice has shown that CCFES significantly improves hand movement control and dexterity. Existing CCFES systems, leveraging technologies such as myoelectric sensors, flexion sensors, and Lidar, can trigger movements but lack real-time muscle status feedback and a rehabilitation movement control strategy, limiting assistance in intricate daily activities. This study introduces an innovative, portable CCFES system based on surface electromyography (sEMG). This system facilitates adaptive amplitude modulation using bilateral hand surface electromyographic signals and enables real-time transitions between rehabilitation movements according to user intent. In the domain of online gesture recognition, the system demonstrated exceptional performance, achieving an average F1 score of 0.935. Furthermore, the system possesses the capability to adaptively modulate stimulation amplitudes by evaluating the differences in sEMG signals between the participant’s hands. The conclusive “object taking” experiment substantiates the system’s potential applicability in the rehabilitation training of daily activities.

IEEE Sensors JournalVol. 25(2)
Sun Yat-sen University (CN), Third Affiliated Hospital of Sun Yat-sen University (CN), South China University of Technology (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Affordable and clean energy
Openalex Percentile: Top 29%
EEG and Brain-Computer Interfaces
0.69
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