Brain-muscle Interaction Analysis with Time-variant Granger Causality

被引:0
|
作者
Tun, Nyi Nyi [1 ,2 ]
Sanuki, Fumiya [3 ]
Iramina, Keiji [2 ]
机构
[1] Kyushu Univ, Grad Sch, Nishi Ku, 744 Motooka, Fukuoka 8190395, Japan
[2] Kyushu Univ, Fac Informat Sci & Elect Engn, Nishi Ku, 744 Motooka, Fukuoka 8190395, Japan
[3] Kyushu Univ, Grad Sch Syst Life Sci, Nishi Ku, 744 Motooka, Fukuoka 8190395, Japan
来源
2023 IEEE 19TH INTERNATIONAL CONFERENCE ON BODY SENSOR NETWORKS, BSN | 2023年
关键词
electroencephalogram; electromyogram; functional interaction; Granger causality; motor task performance;
D O I
10.1109/BSN58485.2023.10330913
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
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页数:4
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