EEG-EMG Correlation Analysis with Linear and Nonlinear Coupling Methods Across Four Motor Tasks

Nyi Nyi Tun, Fumiya Sanuki, Keiji Iramina

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

4 被引用数 (Scopus)

抄録

Correlation between brain and muscle signal is referred to as functional coupling. The amount of correlation between two signals greatly depends on the motor task performance. In this study, we designed the experimental paradigm with four types of motor tasks such as real hand grasping movement (RM), movement intention (Inten), motor imagery (MI) and only looking at virtual hand in three dimensional head mounted display (OL). We aimed to investigate EEG-EMG correlation with linear and nonlinear coupling methods. The results proved that high correlation could be occurred in RM and Inten tasks rather than MI and OL tasks in both linear and nonlinear methods. High coherence occurred in beta and gamma bands of RM and Inten tasks whereas no coherence was detected in MI and OL tasks. In terms of nonlinear correlation, the high mutual information was detected in RM and Inten tasks. There was slight mutual information in MI and OL tasks. The results showed that the coherence in the contralateral brain cortex was higher than in the ipsilateral motor cortex during motor tasks. Furthermore, the amount of EEG-EMG functional coupling changed according to the motor task executed.

本文言語英語
ホスト出版物のタイトル43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
出版社Institute of Electrical and Electronics Engineers Inc.
ページ783-786
ページ数4
ISBN(電子版)9781728111797
DOI
出版ステータス出版済み - 2021
イベント43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021 - Virtual, Online, メキシコ
継続期間: 11月 1 202111月 5 2021

出版物シリーズ

名前Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN(印刷版)1557-170X

会議

会議43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
国/地域メキシコ
CityVirtual, Online
Period11/1/2111/5/21

!!!All Science Journal Classification (ASJC) codes

  • 信号処理
  • 生体医工学
  • コンピュータ ビジョンおよびパターン認識
  • 健康情報学

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