Continuous Wrist Joint Control Using Muscle Deformation Measured on Forearm Skin

Akira Kato, Masato Hirabayashi, Yuya Matsurnoto, Yasutaka Nakashima, Yo Kobayashi, Masakatsu G. Fujie, Shigeki Sugano

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    Continuous, easy-to-implement, accurate inference of intended joint angles is important for effectively controlling powered prosthetic devices that can improve the lives and capabilities of upper-limb amputees. Estimation of intended joint angles is difficult because conventional biosignals are not directly related to the intended angle motion. In previous work, we began to address this issue by confirming that both transra-dial amputees and intact subjects, the measured deformation of the muscle bulge on the skin surface change according to the intended wrist joint angle. This paper presents a continuous prosthesis wrist joint control method using this deformation signal. We here verify the effectiveness of the distribution of the muscle bulge for accurate and stable wrist joint angle control in real time. The wrist joint angles were calculated in real time from a muscle viscoelastic model using the previously determined algorithm. We compared the error between measured and estimated angles with a conventional method, the Voigt model, and the KelvinVoigt model. Experimental results obtained for three intact people over three trials of wrist movement tasks gave the accuracy and stability of 7.96\pm 6.16{\circ} when using the Voigt model; this is a similar performance compared to related work using a surface electromyogram. A method for continuously controlling the wrist joint angle for a prosthesis using the distribution of the muscle bulge was thus successfully established.

    Original languageEnglish
    Title of host publication2018 IEEE International Conference on Robotics and Automation, ICRA 2018
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages1818-1824
    Number of pages7
    ISBN (Electronic)9781538630815
    DOIs
    Publication statusPublished - 2018 Sep 10
    Event2018 IEEE International Conference on Robotics and Automation, ICRA 2018 - Brisbane, Australia
    Duration: 2018 May 212018 May 25

    Publication series

    NameProceedings - IEEE International Conference on Robotics and Automation
    ISSN (Print)1050-4729

    Conference

    Conference2018 IEEE International Conference on Robotics and Automation, ICRA 2018
    CountryAustralia
    CityBrisbane
    Period18/5/2118/5/25

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    ASJC Scopus subject areas

    • Software
    • Control and Systems Engineering
    • Artificial Intelligence
    • Electrical and Electronic Engineering

    Cite this

    Kato, A., Hirabayashi, M., Matsurnoto, Y., Nakashima, Y., Kobayashi, Y., Fujie, M. G., & Sugano, S. (2018). Continuous Wrist Joint Control Using Muscle Deformation Measured on Forearm Skin. In 2018 IEEE International Conference on Robotics and Automation, ICRA 2018 (pp. 1818-1824). [8460491] (Proceedings - IEEE International Conference on Robotics and Automation). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICRA.2018.8460491