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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 11
3258-3263

Multi-stream convolutional myoelectric gesture recognition networks fusing attentional mechanisms

Li Yanhong
Jiang Xi
Zou Ke
Yuan Xuedong
College of Computer Science, Sichuan University, Chengdu 610065, China
DOI: 10.19734/j.issn.1001-3695.2021.04.0100

Abstract

In order to solve the problems of insufficient feature extraction of sEMG end-to-end gesture recognition and low accuracy of multi-gesture recognition, this paper proposed a multi-stream convolutional EMG gesture recognition network model fusing attention mechanism. The proposed model generated sub-myoelectrograms from multi-channel time-domain sEMG through sliding windows and used a multi-stream convolutional neural network to fully extract the semantic features of each sampled channel sEMG, and then aggregated them to obtain rich multi-channel gesture semantic features. At the same time, the proposed model calculated the attention distribution map of semantic features from temporal and feature channel dimensions to strengthen the useful features and weaken the useless features, further improved the accuracy of multi-gesture recognition. The experiment used the Ninapro dataset for training and testing and compared with the mainstream electromyogram recognition model. The experimental results show that the proposed model has better performance in recognition accuracy, which proves the effectiveness of the proposed model.

Foundation Support

四川省重点研发计划资助项目(2020YFG0075)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.04.0100
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 11
Section: Algorithm Research & Explore
Pages: 3258-3263
Serial Number: 1001-3695(2021)11-009-3258-06

Publish History

[2021-11-05] Printed Article

Cite This Article

李沿宏, 江茜, 邹可, 等. 融合注意力机制的多流卷积肌电手势识别网络 [J]. 计算机应用研究, 2021, 38 (11): 3258-3263. (Li Yanhong, Jiang Xi, Zou Ke, et al. Multi-stream convolutional myoelectric gesture recognition networks fusing attentional mechanisms [J]. Application Research of Computers, 2021, 38 (11): 3258-3263. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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