Motor command detection for a repetitive facilitation exercise assistance system

Satoshi Miura, Junichi Takazawa, Yo Kobayashi, Masakatsu G. Fujie

    研究成果: Conference contribution

    1 被引用数 (Scopus)

    抄録

    This paper presents a feasibility study of a brain-machine interface system to assist repetitive facilitation exercise. Repetitive facilitation exercise is an effective rehabilitation method for patients with hemiplegia. In repetitive facilitation exercise, a therapist stimulates the paralyzed part of the patient while motor commands run along the nerve pathway. However, successful repetitive facilitation exercise is difficult to achieve and even a skilled practitioner cannot detect when a motor command occurs in patient's brain. We proposed a brain-machine interface system for automatically detecting motor commands and stimulating the paralyzed part of a patient. To determine motor commands from patient electroencephalogram (EEG) data, we constructed a support vector machine (SVM) system. In this paper, we validated that the discrimination ratio of the motor command by EEG using SVM was higher than the success rate of the repetitive facilitation exercise administered by a therapist. In the experiments, we measured the EEG when the participant bent their elbow when prompted to do so. We analyzed the EEG data using a cross-validation method. We found that the discrimination ratio for each participant was at least 69%, which is above the success rate for repetitive facilitation exercise administered by a therapist. We conclude that the EEG using SVM is useful for detecting motor commands.

    本文言語English
    ホスト出版物のタイトル2017 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2017
    出版社Institute of Electrical and Electronics Engineers Inc.
    ページ267-272
    ページ数6
    2017-July
    ISBN(電子版)9781538620342
    DOI
    出版ステータスPublished - 2018 3 9
    イベント2017 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2017 - Okinawa, Japan
    継続期間: 2017 7 142017 7 18

    Other

    Other2017 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2017
    CountryJapan
    CityOkinawa
    Period17/7/1417/7/18

    ASJC Scopus subject areas

    • Control and Optimization
    • Artificial Intelligence

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