Real-Time Control of Intelligent Prosthetic Hand Based on the Improved TCN

Intelligent prosthetic hand is an important branch of intelligent robotics. It can remotely replace humans to complete various complex tasks and also help humans to complete rehabilitation training. In human-computer interaction technology, the prosthetic hand can be accurately controlled by surface...

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Bibliographic Details
Published in:Applied bionics and biomechanics 2022, Vol.2022, p.6488599-13
Main Authors: Liu, Xiaoguang, Wang, Jiawei, Han, Tingwen, Lou, Cunguang, Liang, Tie, Wang, Hongrui, Liu, Xiuling
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Body mass index
Decomposition
Deep learning
Discriminant analysis
Electrodes
Electromyography
Experiments
Gesture recognition
Implants, Artificial
Machine learning
Methods
Neural networks
Prostheses
Prosthesis
Real time
Rehabilitation
Robotics
Robotics industry
Robots
Task complexity
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Summary:Intelligent prosthetic hand is an important branch of intelligent robotics. It can remotely replace humans to complete various complex tasks and also help humans to complete rehabilitation training. In human-computer interaction technology, the prosthetic hand can be accurately controlled by surface electromyography (sEMG). This paper proposes a new multichannel fusion scheme (MSFS) to extend the virtual channels of sEMG and improve the accuracy of gesture recognition. In addition, the Temporal Convolutional Network (TCN) in deep learning has been improved to enhance the performance of the network. Finally, the sEMG is collected by the Myo armband and the prosthetic hand is controlled in real time to validate the new method. The experimental results show that the method proposed in this paper can improve the accuracy of the control intelligent prosthetic hand, and the accuracy rate is 93.69%.
ISSN:1176-2322
1754-2103
DOI:10.1155/2022/6488599