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

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Intelligent Robotics and Applications (ICIRA 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13013))

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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.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (No. 62073318).

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Authors and Affiliations

  1. The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Cheng Zeng, Enhao Zheng & Hong Qiao

  2. School of Information Engineering, China University of Geosciences (Beijing), Beijing, 100083, China

    Cheng Zeng

  3. Department of Advanced Manufacturing and Robotics, College of Engineering, Peking University, Beijing, 100871, China

    Qining Wang

Authors
  1. Cheng Zeng
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  2. Enhao Zheng
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  3. Qining Wang
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  4. Hong Qiao
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Corresponding author

Correspondence to Enhao Zheng .

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Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Xin-Jun Liu

  2. Tsinghua University, Beijing, China

    Zhenguo Nie

  3. Beihang University, Beijing, China

    Jingjun Yu

  4. Tsinghua University, Beijing, China

    Fugui Xie

  5. Shandong University, Shandong, China

    Rui Song

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Zeng, C., Zheng, E., Wang, Q., Qiao, H. (2021). A Current-Based Surface Electromyography (sEMG) System for Human Motion Recognition: Preliminary Study. In: Liu, XJ., Nie, Z., Yu, J., Xie, F., Song, R. (eds) Intelligent Robotics and Applications. ICIRA 2021. Lecture Notes in Computer Science(), vol 13013. Springer, Cham. https://doi.org/10.1007/978-3-030-89095-7_70

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  • DOI: https://doi.org/10.1007/978-3-030-89095-7_70

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-89094-0

  • Online ISBN: 978-3-030-89095-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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