29 / 2023-08-29 01:00:30
Research on sEMG pattern recognition algorithm and implementation of a gesture recognition system
sEMG, CNN, RNN, Attention Mechanisms, Embedded Systems, Pattern Recognition
Final Paper
Yuepeng Tian / Southeast University
Zhimin Zhang / China Pharmaceutical University
Yuwen Li / Southeast University
Pattern recognition of surface electromyogram (surface EMG, sEMG) signals can obtain human movement information. In recent years, this technology has been widely used in many fields. In the algorithm part, this paper proposes a model based on Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) . The effects of different algorithm structures and parameter selections are compared. On this basis, Depthwise separable convolution is introduced to reduce the number of parameters while maintaining high accuracy. In addition, the attention module SElayer is introduced to further improve the performance of the algorithm. The final algorithm achieved an accuracy rate of 93.41% on the NinaPro-DB2 dataset. In addition to the algorithm, this paper also builds a sEMG gesture recognition system with the help of an embedded platform. The system is mainly composed of an 8-channel sEMG acquisition board and a computer, and includes four functional modules: data acquisition and annotation, data preprocessing, model training and real-time classification. Finally, the system collected sEMG data from 7 subjects. The model achieved good results on the dataset and completed the real-time classification.
Important Date
  • Conference Date

    Nov 02

    2023

    to

    Nov 04

    2023

  • Dec 15 2023

    Draft paper submission deadline

  • Dec 20 2023

    Registration deadline

Sponsored By
IEEE Instrumentation and Measurement Society
Xidian University