バーチャルハンドを利用した相互学習型筋電義手トレーニングシステム

芝軒 太郎, 中村 豪, 渡橋 史典, 早志 英朗, 栗田 雄一, 高木 健, 本田 雄一郎, 溝部 二十四, 陳 隆明, 辻 敏夫

研究成果: Contribution to journalArticle査読

抄録

This paper proposes an interactive training system for control of myoelectric prostheses. The proposed training system is capable of selecting suitable motions (EMG patterns) for each user by eliminating ineffective ones, and can also provide consistency between user's motor images and the corresponding prosthetic movements using a virtual prosthetic hand (VH). In the experiments performed, a one-day training session using the proposed system was conducted with nine healthy males (including an experienced) and an upper limb amputee. In addition, EMG discrimination ability of each subject during VH control without any feedback information was evaluated before and after the training to verify the training effects of the proposed system. The results showed that the discrimination rates for selected motions were sufficiently high (98.9 ± 1.24%) by using the proposed selection method, and the accuracy in discrimination for VH control was significantly improved after training (for healthy subjects and the amputee at the 0.1% and 1% level, respectively). It is therefore confirmed that the proposed system can be used for myoelectric prosthesis control training.
寄稿の翻訳タイトルAn Interactive Training System for Myoelectric Prostheses using Virtual Hand
本文言語日本語
ページ(範囲)404-410
ページ数7
ジャーナル日本ロボット学会誌
34
6
DOI
出版ステータス出版済み - 2016

フィンガープリント

「バーチャルハンドを利用した相互学習型筋電義手トレーニングシステム」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル