InRes-ACNet: Gesture Recognition Model of Multi-Scale Attention Mechanisms Based on Surface Electromyography Signals

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成果类型：

期刊论文

作者：

Ziyi Wang;Yihua Li;Xiaoyuan Luo;Xiaogang Duan;Wenjing Huang*

通讯作者：

Wenjing Huang

作者机构：

[Ziyi Wang; Xiaoyuan Luo] School of Materials Science and Engineering, Central South University of Forestry, Changsha 410004, China

Author to whom correspondence should be addressed.

[Xiaogang Duan] Central South Intelligence Collaborative Research Center, Changsha 410004, China

[Yihua Li] School of Logistics & Traffic, Central South University of Forestry, Changsha 410004, China

[Wenjing Huang] School of Materials Science and Engineering, Central South University of Forestry, Changsha 410004, China<&wdkj&>Author to whom correspondence should be addressed.

通讯机构：

[Wenjing Huang] S

School of Materials Science and Engineering, Central South University of Forestry, Changsha 410004, China<&wdkj&>Author to whom correspondence should be addressed.

语种：

英文

关键词：

multi-scale attention mechanisms;deep learning model;sEMG signals;gesture recognition;electromyography manipulator

期刊：

Applied Sciences-Basel

ISSN：

2076-3417

年：

2024

卷：

期：

页码：

3237-

DOI：

10.3390/app14083237

基金类别：

Conceptualization, X.L. and W.H.; methodology, X.L.; software, X.L.; validation, X.L.; formal analysis, X.L.; investigation, X.L.; resources, X.L. and W.H.; data curation, X.L. and W.H.; writing—original draft preparation, X.L. and W.H.; writing—review and editing, X.L., W.H. and Y.L.; visualization, X.L.; supervision, W.H. and Z.W.; project administration, X.L., W.H., and X.D.; funding acquisition, W.H. and Y.L. All authors have read and agreed to the published version of the manuscript. This research was funded by the Hunan Natural Science Foundation (No. 2022JJ31015), General Project of the National Social Science Fund (No. 22BGL173), Major Project of the Social Science Evaluation Committee of Hunan Province (No. XSP22ZDA006), Hunan Teaching Reform Research Project (No. HNJG-20230470), and the Graduate Science and Technology Innovation Fund of Central South University of Forestry and Technology (No. 2023CX02070).

机构署名：

本校为第一且通讯机构

摘要：

Surface electromyography (sEMG) signals are the sum of action potentials emitted by many motor units; they contain the information of muscle contraction patterns and intensity, so they can be used as a simple and reliable source for grasping mode recognition. This paper introduces the InRes-ACNet (inception–attention–ACmix-ResNet50) model, a novel deep-learning approach based on ResNet50, incorporating multi-scale modules and self-attention mechanisms. The proposed model aims to improve gesture recognition performance by enhancing its ability...

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