身体的特徴を考慮したEMGに基づく筋負荷推定―身体的特徴の分類と推定精度の向上―

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2013/05/01

タイトル(英語): Estimation of Muscular Load Based on EMG by Considering Bodily Features―Clustering of Bodily Features and Improvement of Estimation Accuracy―

著者名: 櫛田　大輔（鳥取大学大学院工学研究科），永冨　裕美（鳥取大学大学院工学研究科），北村　章（鳥取大学大学院工学研究科）

著者名(英語): Daisuke Kushida (Graduate School of Engineering, Tottori University), Yumi Nagatomi (Graduate School of Engineering, Tottori University), Akira Kitamura (Graduate School of Engineering, Tottori University)

キーワード: 筋活動電位，身体的特徴，クラスタリング，筋力係数，筋負荷，リハビリテーション　　EMG，Bodily features，Clustering，Muscular power coefficient，Muscular load，Rehabilitation

要約(英語): In the rehabilitation for the motor function recovery, the menu of the rehabilitation has been decided based on doctor's subjectivity by knowledge and the experience. However, the decision based on doctor's subjectivity has the possibility of inviting the result that the judgement is different in each doctor. On the other hand, authors were relating "muscular power coefficient", that showed the relation of EMG (Electromyogram) and muscular load, and bodily features in the nonlinear model by GP (Genetic Programing). As a result, a muscular condition was enabled to be estimated objectively only by knowing patient's bodily features. This paper proposed the improvement of the estimation accuracy by clustering based on subject's bodily features, and constructing the nonlinear model in each class. The effectiveness of the proposed method is shown by the experimental work using the subjects at two or more ages.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.133 No.5 （2013） 特集：新たな産業への応用が進む無線通信技術

本誌掲載ページ: 978-984 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/133/5/133_978/_article/-char/ja/