Brain-muscle Interaction Analysis with Time-variant Granger Causality

Nyi Nyi Tun, Fumiya Sanuki, Keiji Iramina

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

Abstract

This study uses time-variant Granger causality to calculate the amount of functional interaction with the inference of information flow direction. Four different motor tasks were taken into consideration. They are real movement (RM), movement intention (Inten), motor imagery (MI), and only looking at the virtual hand in three-dimensional head-mounted display (OL) tasks. For the purpose of task instructions, we designed the experimental tasks in a 3D-HMD virtual reality environment. Examining the causality between two different biological signals is still challenging, and there have been few studies of causality between brain and muscle signals. Thus, the main aim of this study is to proclaim that time-variant Granger causality is an easy-To-Apply and effective method for inferring information flow direction between ascending and descending pathways of brain and muscle signals. Generally, our final results strongly proved that brain-muscle functional interaction changes according to the motor tasks executed. Furthermore, high functional interaction appears in RM, Inten and MI tasks (in some subjects) rather than OL task in both afferent and efferent directions. Among many functional interaction methods, time-variant Granger causality is one of the most basic and reliable methods for investigating two different neurophysiological signals, such as EEG and EMG, to calculate the direction of information.

Original languageEnglish
Title of host publication2023 IEEE 19th International Conference on Body Sensor Networks, BSN 2023 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350338416
DOIs
Publication statusPublished - 2023
Event19th IEEE International Conference on Body Sensor Networks, BSN 2023 - Boston, United States
Duration: Oct 9 2023Oct 11 2023

Publication series

Name2023 IEEE 19th International Conference on Body Sensor Networks, BSN 2023 - Proceedings

Conference

Conference19th IEEE International Conference on Body Sensor Networks, BSN 2023
Country/TerritoryUnited States
CityBoston
Period10/9/2310/11/23

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Biomedical Engineering
  • Health Informatics
  • Instrumentation

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