Research progress on analysis methods in electroencephalography-electromyography synchronous coupling.
10.7507/1001-5515.201804005
- Author:
Sujiao LI
1
,
2
;
Su LIU
3
;
He LAN
3
;
Hongliu YU
1
,
4
,
5
Author Information
1. Institute of Rehabilitation Engineering and Technology, School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, P.R.China
2. Shanghai Engineering Research Center of Assistive Devices, Shanghai 200093, P.R.China.
3. Institute of Rehabilitation Engineering and Technology, School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, P.R.China.
4. Shanghai Engineering Research Center of Assistive Devices, Shanghai 200093, P.R.China
5. Key Laboratory of Neuro-functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs, Shanghai 200093, P.R.China.
- Publication Type:Journal Article
- Keywords:
Granger causality;
coherence analysis;
mutual information;
transfer entropy
- MeSH:
Electroencephalography;
Electromyography;
Humans;
Motor Cortex;
physiology;
Muscle, Skeletal;
physiology;
Research
- From:
Journal of Biomedical Engineering
2019;36(2):334-337
- CountryChina
- Language:Chinese
-
Abstract:
The motor nervous system transmits motion control information through nervous oscillations, which causes the synchronous oscillatory activity of the corresponding muscle to reflect the motion response information and give the cerebral cortex feedback, so that it can sense the state of the limbs. This synchronous oscillatory activity can reflect connectivity information of electroencephalography-electromyography (EEG-EMG) functional coupling. The strength of the coupling is determined by various factors including the strength of muscle contraction, attention, motion intention etc. It is very significant to study motor functional evaluation and control methods to analyze the changes of EEG-EMG synchronous coupling caused by different factors. This article mainly introduces and compares coherence and Granger causality of linear methods, the mutual information and transfer entropy of nonlinear methods in EEG-EMG synchronous coupling, and summarizes the application of each method, so that researchers in related fields can understand the current research progress on analysis methods of EEG-EMG synchronous systematically.
