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

Nyi Nyi Tun, Fumiya Sanuki, Keiji Iramina

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

4 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publication43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages783-786
Number of pages4
ISBN (Electronic)9781728111797
DOIs
Publication statusPublished - 2021
Event43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021 - Virtual, Online, Mexico
Duration: Nov 1 2021Nov 5 2021

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

Conference43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
Country/TerritoryMexico
CityVirtual, Online
Period11/1/2111/5/21

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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