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Journal of Medical Systems

, 43:22 | Cite as

Study on Brain Electromyography Rehabilitation System Based on Data Fusion and Virtual Rehabilitation Simulation

  • Shuxia Li
  • Juncheng YangEmail author
Image & Signal Processing
  • 138 Downloads
Part of the following topical collections:
  1. Artificial Intelligence Application in Health Informatics

Abstract

In this paper, a virtual rehabilitation training system based on electroencephalogram (EMG) feedback is proposed to solve the problem that the existing virtual rehabilitation training methods can not reflect the initiative of patients and lack of individual adaptability. Aiming at the EEG data fusion rehabilitation system based on Virtual Prototyping technology, a motion pattern recognition method based on the feature fusion of EEG and EMG signals is studied to improve the accuracy and flexibility of the rehabilitation training system. The corresponding virtual rehabilitation training scene is designed, and the control and feedback adjustment of the virtual scene are realized by using the above EEG feature analysis method. Finally, the virtual rehabilitation training is realized. The multi-level coupling relationship between EEG and EMG signals under different grip forces was explored by using the synchronous coupling characteristics between EEG and EMG signals, which provided a theoretical basis for further application in clinical rehabilitation evaluation.

Keywords

Virtual prototyping technology EEG data EMG data Rehabilitation system Data fusion 

Notes

Funding

This research is based upon work supported in part by the National Natural Science Foundation of China (No. 61502350).

Compliance with Ethical Standards

Ethical Approval

This article does not contain any studies with human participants performed by any of the authors.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Electronic and Information EngineeringHenan Polytechnic InstituteZhengzhouChina

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