Method for analyzing electroencephalogram and electromyographic coupling among multiple time-frequency scales on basis of wavelet-transfer entropy

A technology of coupling analysis and transfer entropy, which is applied in the directions of sensors, medical science, diagnostic recording/measurement, etc., can solve the problem of nonlinear coupling and information transmission of EEG and EMG time-frequency domain characteristics, etc. question

Active Publication Date: 2016-11-09
YANSHAN UNIV
View PDF2 Cites 30 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, there are still some deficiencies in the above studies: the coarse-grained and moving average methods only time-scale the EEG and EMG signals, and cannot describe the time-frequency domain characteristics of EEG and EMG signals and the relationship between different time-frequency scales. Nonlinear Coupling and Information Transfer of EEG Signals

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method for analyzing electroencephalogram and electromyographic coupling among multiple time-frequency scales on basis of wavelet-transfer entropy
  • Method for analyzing electroencephalogram and electromyographic coupling among multiple time-frequency scales on basis of wavelet-transfer entropy
  • Method for analyzing electroencephalogram and electromyographic coupling among multiple time-frequency scales on basis of wavelet-transfer entropy

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0038] Such as figure 2 As shown, the method steps are as follows:

[0039] In step 1, a 64-lead Neuroscan device was used to collect EEG signals and EMG signals synchronously.

[0040] The structure of the Neuroscan device is as follows figure 1 As shown, it consists of EEG electrodes, electrode caps, EEG collectors, EMG lead wires, and EMG electrode connections.

[0041] EEG signal acquisition: The EEG electrodes adopt the international standard 10-20 electrode placement standard, and the EEG electrode 1 is in contact with the scalp through the electrode cap 2. The brain electromyography signal synchronous acquisition experiment was carried out under the static grip force output movement of the hand. The M1 and M2 leads were respectively connected to the left and right retroauricular mastoids as reference electrodes, and the ground electrode was placed in the center of the top of the head. The C3, C4 and CPZ regions were selected from the 32-lead scalp EEG acquisition eq...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a method for analyzing electroencephalogram and electromyographic coupling among multiple time-frequency scales on the basis of wavelet-transfer entropy. The method includes an electroencephalogram and electromyographic signal synchronous acquisition portion and a signal processing portion. The electroencephalogram and electromyographic signal synchronous acquisition portion includes acquiring electroencephalogram signals and acquiring electromyographic signals; the signal processing portion includes preprocessing the signals and carrying out processes for analyzing the electroencephalogram and electromyographic wavelet-transfer entropy. The method has the advantages of applicability, admissibility and important value in the field of rehabilitation medicine.

Description

technical field [0001] The invention relates to the fields of neurorehabilitation engineering and exercise mechanism research, in particular to a multi-time-frequency scale inter-brain myoelectric coupling analysis method based on wavelet-transfer entropy. Background technique [0002] Electroencephalogram (EEG) and electromyographic (EMG) signals contain body movement control information and muscle functional response information to the brain's control intention, respectively. The multi-scale coupling information between EEG signals reflects the multi-level cortex-muscle Functional coupling (Functional corticomuscular coupling, FCMC) connection information. At present, the research on EEG synchronization characteristics is mainly based on coherence analysis to obtain the functional connection characteristics between the brain's motor awareness drive and muscle motion response, but the traditional coherence analysis cannot reflect the coupling direction characteristics. In ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/00A61B5/0476A61B5/0488
CPCA61B5/7203A61B5/7235A61B5/369A61B5/389
Inventor 谢平杨芳梅张园园陈晓玲吴晓光张晋铭王霄
Owner YANSHAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap