A Current-Based Surface Electromyography (sEMG) System for Human Motion Recognition: Preliminary Study

Cheng Zeng; Enhao Zheng; Qining Wang; Hong Qiao

doi:10.1007/978-3-030-89095-7_70

A Current-Based Surface Electromyography (sEMG) System for Human Motion Recognition: Preliminary Study

Cheng Zeng
, Enhao Zheng
, Qining Wang
, Hong Qiao

CAS - Institute of Automation
China University of Geosciences, Beijing
Peking University

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

Abstract

The myoelectric interface acts as an important role in the field of wearable robotics. This study explores the current-based sEMG technology for upper-limb motion recognition. Different from the voltage-based sEMG system, the current-based sampling approach can directly extract the current signals and be free from the cross talks. The technology facilitate the myoelectric sampling in a non-ideal environment such as underwater. We designed the sensing circuit with a feedback-loop current amplification module, and analyzed the stability. After development of the system, three healthy subjects participated in the experiment. Six basic wrist joint motions were investigated. With the selected feature set and the designed classification method, The average recognition accuracies across the subjects were 96.3%, 94.2%, and 95.8% respectively. The preliminary results demonstrate that the current-based sEMG technology is a promising solution to upper-limb motion recognition in a rigorous environment.

Original language	English
Title of host publication	Intelligent Robotics and Applications - 14th International Conference, ICIRA 2021, Proceedings
Editors	Xin-Jun Liu, Zhenguo Nie, Jingjun Yu, Fugui Xie, Rui Song
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	737-747
Number of pages	11
ISBN (Print)	9783030890940
DOIs	https://doi.org/10.1007/978-3-030-89095-7_70
State	Published - 2021
Externally published	Yes
Event	14th International Conference on Intelligent Robotics and Applications, ICIRA 2021 - Yantai, China Duration: 22 Oct 2021 → 25 Oct 2021

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13013 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	14th International Conference on Intelligent Robotics and Applications, ICIRA 2021
Country/Territory	China
City	Yantai
Period	22/10/21 → 25/10/21

Keywords

Current-based sEMG
Human upper limb
Motion recognition
Stability

Access to Document

10.1007/978-3-030-89095-7_70

Cite this

Zeng, C., Zheng, E., Wang, Q., & Qiao, H. (2021). A Current-Based Surface Electromyography (sEMG) System for Human Motion Recognition: Preliminary Study. In X.-J. Liu, Z. Nie, J. Yu, F. Xie, & R. Song (Eds.), Intelligent Robotics and Applications - 14th International Conference, ICIRA 2021, Proceedings (pp. 737-747). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13013 LNAI). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-89095-7_70

Zeng, Cheng ; Zheng, Enhao ; Wang, Qining et al. / A Current-Based Surface Electromyography (sEMG) System for Human Motion Recognition : Preliminary Study. Intelligent Robotics and Applications - 14th International Conference, ICIRA 2021, Proceedings. editor / Xin-Jun Liu ; Zhenguo Nie ; Jingjun Yu ; Fugui Xie ; Rui Song. Springer Science and Business Media Deutschland GmbH, 2021. pp. 737-747 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{f0f3073ee5af4b0bae758da35e99e797,

title = "A Current-Based Surface Electromyography (sEMG) System for Human Motion Recognition: Preliminary Study",

abstract = "The myoelectric interface acts as an important role in the field of wearable robotics. This study explores the current-based sEMG technology for upper-limb motion recognition. Different from the voltage-based sEMG system, the current-based sampling approach can directly extract the current signals and be free from the cross talks. The technology facilitate the myoelectric sampling in a non-ideal environment such as underwater. We designed the sensing circuit with a feedback-loop current amplification module, and analyzed the stability. After development of the system, three healthy subjects participated in the experiment. Six basic wrist joint motions were investigated. With the selected feature set and the designed classification method, The average recognition accuracies across the subjects were 96.3\%, 94.2\%, and 95.8\% respectively. The preliminary results demonstrate that the current-based sEMG technology is a promising solution to upper-limb motion recognition in a rigorous environment.",

keywords = "Current-based sEMG, Human upper limb, Motion recognition, Stability",

author = "Cheng Zeng and Enhao Zheng and Qining Wang and Hong Qiao",

note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 14th International Conference on Intelligent Robotics and Applications, ICIRA 2021 ; Conference date: 22-10-2021 Through 25-10-2021",

year = "2021",

doi = "10.1007/978-3-030-89095-7\_70",

language = "英语",

isbn = "9783030890940",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "737--747",

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booktitle = "Intelligent Robotics and Applications - 14th International Conference, ICIRA 2021, Proceedings",

}

Zeng, C, Zheng, E, Wang, Q & Qiao, H 2021, A Current-Based Surface Electromyography (sEMG) System for Human Motion Recognition: Preliminary Study. in X-J Liu, Z Nie, J Yu, F Xie & R Song (eds), Intelligent Robotics and Applications - 14th International Conference, ICIRA 2021, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13013 LNAI, Springer Science and Business Media Deutschland GmbH, pp. 737-747, 14th International Conference on Intelligent Robotics and Applications, ICIRA 2021, Yantai, China, 22/10/21. https://doi.org/10.1007/978-3-030-89095-7_70

A Current-Based Surface Electromyography (sEMG) System for Human Motion Recognition: Preliminary Study. / Zeng, Cheng; Zheng, Enhao; Wang, Qining et al.
Intelligent Robotics and Applications - 14th International Conference, ICIRA 2021, Proceedings. ed. / Xin-Jun Liu; Zhenguo Nie; Jingjun Yu; Fugui Xie; Rui Song. Springer Science and Business Media Deutschland GmbH, 2021. p. 737-747 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13013 LNAI).

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

TY - GEN

T1 - A Current-Based Surface Electromyography (sEMG) System for Human Motion Recognition

T2 - 14th International Conference on Intelligent Robotics and Applications, ICIRA 2021

AU - Zeng, Cheng

AU - Zheng, Enhao

AU - Wang, Qining

AU - Qiao, Hong

PY - 2021

Y1 - 2021

N2 - The myoelectric interface acts as an important role in the field of wearable robotics. This study explores the current-based sEMG technology for upper-limb motion recognition. Different from the voltage-based sEMG system, the current-based sampling approach can directly extract the current signals and be free from the cross talks. The technology facilitate the myoelectric sampling in a non-ideal environment such as underwater. We designed the sensing circuit with a feedback-loop current amplification module, and analyzed the stability. After development of the system, three healthy subjects participated in the experiment. Six basic wrist joint motions were investigated. With the selected feature set and the designed classification method, The average recognition accuracies across the subjects were 96.3%, 94.2%, and 95.8% respectively. The preliminary results demonstrate that the current-based sEMG technology is a promising solution to upper-limb motion recognition in a rigorous environment.

AB - The myoelectric interface acts as an important role in the field of wearable robotics. This study explores the current-based sEMG technology for upper-limb motion recognition. Different from the voltage-based sEMG system, the current-based sampling approach can directly extract the current signals and be free from the cross talks. The technology facilitate the myoelectric sampling in a non-ideal environment such as underwater. We designed the sensing circuit with a feedback-loop current amplification module, and analyzed the stability. After development of the system, three healthy subjects participated in the experiment. Six basic wrist joint motions were investigated. With the selected feature set and the designed classification method, The average recognition accuracies across the subjects were 96.3%, 94.2%, and 95.8% respectively. The preliminary results demonstrate that the current-based sEMG technology is a promising solution to upper-limb motion recognition in a rigorous environment.

KW - Current-based sEMG

KW - Human upper limb

KW - Motion recognition

KW - Stability

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DO - 10.1007/978-3-030-89095-7_70

M3 - 会议稿件

AN - SCOPUS:85118219432

SN - 9783030890940

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 737

EP - 747

BT - Intelligent Robotics and Applications - 14th International Conference, ICIRA 2021, Proceedings

A2 - Liu, Xin-Jun

A2 - Nie, Zhenguo

A2 - Yu, Jingjun

A2 - Xie, Fugui

A2 - Song, Rui

PB - Springer Science and Business Media Deutschland GmbH

Y2 - 22 October 2021 through 25 October 2021

ER -

Zeng C, Zheng E, Wang Q, Qiao H. A Current-Based Surface Electromyography (sEMG) System for Human Motion Recognition: Preliminary Study. In Liu XJ, Nie Z, Yu J, Xie F, Song R, editors, Intelligent Robotics and Applications - 14th International Conference, ICIRA 2021, Proceedings. Springer Science and Business Media Deutschland GmbH. 2021. p. 737-747. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-89095-7_70

A Current-Based Surface Electromyography (sEMG) System for Human Motion Recognition: Preliminary Study

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