No fucking clue what this is or can be used for.
https://www.frontiersin.org/articles/10.3389/fneur.2017.00716/full?
- 1College of Automation, Intelligent Control & Robotics Institute, Hangzhou Dianzi University, Hangzhou, China
- 2Department of Biomedical Engineering, University of Houston, Houston, TX, United States
- 3Guangdong Provincial Work-Injury Rehabilitation Hospital, Guangzhou, China
The coupling strength between electroencephalogram (EEG) and
electromyography (EMG) signals during motion control reflects the
interaction between the cerebral motor cortex and muscles. Therefore,
neuromuscular coupling characterization is instructive in assessing
motor function. In this study, to overcome the limitation of losing the
characteristics of signals in conventional time series symbolization
methods, a variable scale symbolic transfer entropy (VS-STE) analysis
approach was proposed for corticomuscular coupling evaluation.
Post-stroke patients (
n = 5) and healthy volunteers (
n =
7) were recruited and participated in various tasks (left and right hand
gripping, elbow bending). The proposed VS-STE was employed to evaluate
the corticomuscular coupling strength between the EEG signal measured
from the motor cortex and EMG signal measured from the upper limb in
both the time-domain and frequency-domain. Results showed a greater
strength of the bi-directional (EEG-to-EMG and EMG-to-EEG) VS-STE in
post-stroke patients compared to healthy controls. In addition, the
strongest EEG–EMG coupling strength was observed in the beta frequency
band (15–35 Hz) during the upper limb movement. The predefined coupling
strength of EMG-to-EEG in the affected side of the patient was larger
than that of EEG-to-EMG. In conclusion, the results suggested that the
corticomuscular coupling is bi-directional, and the proposed VS-STE can
be used to quantitatively characterize the non-linear synchronization
characteristics and information interaction between the primary motor
cortex and muscles.
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