A Teleoperated Manipulator Control System Based on Surface Electromyography Using Deep Learning

Zhiping Lai; Xueze Zhang; Junkongshuai Wang; Wei Mu; Aiping Wang; Lan Niu; Lihua Zhang; Hongbo Wang; Xiaoyang Kang; Jianxiong Bin

doi:10.1109/CYBER55403.2022.9907033

A Teleoperated Manipulator Control System Based on Surface Electromyography Using Deep Learning

Zhiping Lai, Xueze Zhang, Junkongshuai Wang, Wei Mu, Aiping Wang, Lan Niu, Lihua Zhang, Hongbo Wang, Xiaoyang Kang^*, Jianxiong Bin

^*Corresponding author for this work

Chemical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Gesture recognition based on surface electromyography (sEMG) is a popular topic in teleoperation field, which has the characteristics of convenience, maneuverability, flexibility and adaptability. With the continuous development of deep learning technology, the variety and accuracy of gesture recognition are constantly improving. In our previous research, a new neural network based on graph convolutional network and temporal convolutional network (STCN-GR) was proposed and achieved good results in gesture recognition task. In this paper, we develop a teleoperated manipulator control system based on STCN-GR combined with majority voting. The experimental results show that the performance of proposed system can achieve relatively excellent performance in recognition accuracy and computation speed. In this paper, we choose a mechanism hand as a peripheral to test the performance of the STCN-GR based control system, and the results show that this system can be applied in teleoperation in feature work to provide convenience for human life.

Original language	English (US)
Title of host publication	2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1281-1286
Number of pages	6
ISBN (Electronic)	9781665472678
DOIs	https://doi.org/10.1109/CYBER55403.2022.9907033
State	Published - 2022
Event	12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022 - Baishan, China Duration: Jul 27 2022 → Jul 31 2022

Publication series

Name	2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022

Conference

Conference	12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022
Country/Territory	China
City	Baishan
Period	07/27/22 → 07/31/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Control and Systems Engineering
Control and Optimization

Access to Document

10.1109/CYBER55403.2022.9907033

Cite this

Lai, Z., Zhang, X., Wang, J., Mu, W., Wang, A., Niu, L., Zhang, L., Wang, H., Kang, X., & Bin, J. (2022). A Teleoperated Manipulator Control System Based on Surface Electromyography Using Deep Learning. In 2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022 (pp. 1281-1286). (2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CYBER55403.2022.9907033

Lai, Zhiping ; Zhang, Xueze ; Wang, Junkongshuai et al. / A Teleoperated Manipulator Control System Based on Surface Electromyography Using Deep Learning. 2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 1281-1286 (2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022).

@inproceedings{fa14d44d646e40ec879d24b5a87114c0,

title = "A Teleoperated Manipulator Control System Based on Surface Electromyography Using Deep Learning",

abstract = "Gesture recognition based on surface electromyography (sEMG) is a popular topic in teleoperation field, which has the characteristics of convenience, maneuverability, flexibility and adaptability. With the continuous development of deep learning technology, the variety and accuracy of gesture recognition are constantly improving. In our previous research, a new neural network based on graph convolutional network and temporal convolutional network (STCN-GR) was proposed and achieved good results in gesture recognition task. In this paper, we develop a teleoperated manipulator control system based on STCN-GR combined with majority voting. The experimental results show that the performance of proposed system can achieve relatively excellent performance in recognition accuracy and computation speed. In this paper, we choose a mechanism hand as a peripheral to test the performance of the STCN-GR based control system, and the results show that this system can be applied in teleoperation in feature work to provide convenience for human life.",

author = "Zhiping Lai and Xueze Zhang and Junkongshuai Wang and Wei Mu and Aiping Wang and Lan Niu and Lihua Zhang and Hongbo Wang and Xiaoyang Kang and Jianxiong Bin",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022 ; Conference date: 27-07-2022 Through 31-07-2022",

year = "2022",

doi = "10.1109/CYBER55403.2022.9907033",

language = "English (US)",

series = "2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1281--1286",

booktitle = "2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022",

address = "United States",

}

Lai, Z, Zhang, X, Wang, J, Mu, W, Wang, A, Niu, L, Zhang, L, Wang, H, Kang, X & Bin, J 2022, A Teleoperated Manipulator Control System Based on Surface Electromyography Using Deep Learning. in 2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022. 2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022, Institute of Electrical and Electronics Engineers Inc., pp. 1281-1286, 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022, Baishan, China, 07/27/22. https://doi.org/10.1109/CYBER55403.2022.9907033

A Teleoperated Manipulator Control System Based on Surface Electromyography Using Deep Learning. / Lai, Zhiping; Zhang, Xueze; Wang, Junkongshuai et al.
2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 1281-1286 (2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A Teleoperated Manipulator Control System Based on Surface Electromyography Using Deep Learning

AU - Lai, Zhiping

AU - Zhang, Xueze

AU - Wang, Junkongshuai

AU - Mu, Wei

AU - Wang, Aiping

AU - Niu, Lan

AU - Zhang, Lihua

AU - Wang, Hongbo

AU - Kang, Xiaoyang

AU - Bin, Jianxiong

PY - 2022

Y1 - 2022

N2 - Gesture recognition based on surface electromyography (sEMG) is a popular topic in teleoperation field, which has the characteristics of convenience, maneuverability, flexibility and adaptability. With the continuous development of deep learning technology, the variety and accuracy of gesture recognition are constantly improving. In our previous research, a new neural network based on graph convolutional network and temporal convolutional network (STCN-GR) was proposed and achieved good results in gesture recognition task. In this paper, we develop a teleoperated manipulator control system based on STCN-GR combined with majority voting. The experimental results show that the performance of proposed system can achieve relatively excellent performance in recognition accuracy and computation speed. In this paper, we choose a mechanism hand as a peripheral to test the performance of the STCN-GR based control system, and the results show that this system can be applied in teleoperation in feature work to provide convenience for human life.

AB - Gesture recognition based on surface electromyography (sEMG) is a popular topic in teleoperation field, which has the characteristics of convenience, maneuverability, flexibility and adaptability. With the continuous development of deep learning technology, the variety and accuracy of gesture recognition are constantly improving. In our previous research, a new neural network based on graph convolutional network and temporal convolutional network (STCN-GR) was proposed and achieved good results in gesture recognition task. In this paper, we develop a teleoperated manipulator control system based on STCN-GR combined with majority voting. The experimental results show that the performance of proposed system can achieve relatively excellent performance in recognition accuracy and computation speed. In this paper, we choose a mechanism hand as a peripheral to test the performance of the STCN-GR based control system, and the results show that this system can be applied in teleoperation in feature work to provide convenience for human life.

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DO - 10.1109/CYBER55403.2022.9907033

M3 - Conference contribution

AN - SCOPUS:85141208476

T3 - 2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022

SP - 1281

EP - 1286

BT - 2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022

Y2 - 27 July 2022 through 31 July 2022

ER -

Lai Z, Zhang X, Wang J, Mu W, Wang A, Niu L et al. A Teleoperated Manipulator Control System Based on Surface Electromyography Using Deep Learning. In 2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 1281-1286. (2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022). doi: 10.1109/CYBER55403.2022.9907033

A Teleoperated Manipulator Control System Based on Surface Electromyography Using Deep Learning

Abstract

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Bibliographical note

ASJC Scopus subject areas

Access to Document

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