GTGR-Net: Graph Attentional-Temporal Network for Surface-Electromyography-Based Gesture Recognition

Xiaoxu Jia, Hongbo Wang*, Jingjing Luo, Zhiping Lai, Xueze Zhang, Weiqi Zhang, Xiuhong Tang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this process of active rehabilitation assisted by hand rehabilitation robot, the patient's hand motion intention, that is, the patient's gesture recognition, plays an important role. Gesture recognition based on sEMG signal is a hot research topic. Due to the spatial correlation and time non-stationary of sEMG signal, this research topic has many difficulties. In order to solve this problem, we come up with a gesture recognition network GTGR-Net based on sEMG signal, which uses the combination of graph attention network and time convolution network to extract the spatiotemporal information of sEMG signal. We verify the effect of our algorithm on three public data sets and achieve good results, which is better than the other ways.

Original languageEnglish (US)
Title of host publicationProceedings - 2022 3rd International Conference on Computing, Networks and Internet of Things, CNIOT 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages182-185
Number of pages4
ISBN (Electronic)9781665469104
DOIs
StatePublished - 2022
Event3rd International Conference on Computing, Networks and Internet of Things, CNIOT 2022 - Qingdao, China
Duration: May 20 2022May 22 2022

Publication series

NameProceedings - 2022 3rd International Conference on Computing, Networks and Internet of Things, CNIOT 2022

Conference

Conference3rd International Conference on Computing, Networks and Internet of Things, CNIOT 2022
Country/TerritoryChina
CityQingdao
Period05/20/2205/22/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

  • gesture recognition
  • Graph attention network
  • graph structure
  • sEMG
  • temporal convolutional network

ASJC Scopus subject areas

  • Information Systems and Management
  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems

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