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Virtual Rehabilitation Training System Based on Surface EMG Feature Extraction and Analysis.

Aiming at the characteristics that electromyography (EMG) signals can reflect the human body's motive intention and the information of muscle's motive state, this paper makes a thorough study on the evaluation of surface electromyography signals' motive state. At the same time, EMG signals can refle...

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Published in:Journal of Medical Systems Vol. 43; no. 3; pp. 1 - 2
Main Authors: Meng, Qiang, Zhang, Jianjun, Yang, Xi
Format: equations & formulas review tables/charts tracings Journal Article
Published: Springer Nature Mar2019
Online Access:View this record in EBSCOhost
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      dt: Mar2019
      vid: 43
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s10916-019-1166-z
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        atl: Virtual Rehabilitation Training System Based on Surface EMG Feature Extraction and Analysis.
      aug:
        au:
          Meng, Qiang
          Zhang, Jianjun
          Yang, Xi
        affil: Department of Physical Education, Physical Education College of Zhengzhou University, Zhengzhou, China
      sug:
        subj:
          Rehabilitation Methods
          Electromyography Methods
          Virtual Reality
          Biofeedback
          Signal Processing, Computer Assisted Evaluation
          Algorithms
          Fatigue
          Extremities
          Movement
          Electromyography Equipment and Supplies
          Stroke Rehabilitation
          Electrodes, Implanted
          Video Games
          Image Processing, Computer Assisted
          Information Management
          Intention
      ab: Aiming at the characteristics that electromyography (EMG) signals can reflect the human body's motive intention and the information of muscle's motive state, this paper makes a thorough study on the evaluation of surface electromyography signals' motive state. At the same time, EMG signals can reflect the characteristics of limb movement and its changing rules, and can acquire the functional characteristics of limb movement so as to accurately evaluate the rehabilitation status of patients. In this paper, EMG signal analysis and feedback control are introduced into the virtual rehabilitation system to study the methods of EMG parameter identification and dynamic feature extraction, and obtain the EMG characteristics and variation rules related to human motion patterns. In this paper, a rehabilitation training system based on EMG feedback and virtual reality is built, and the validity of the system is verified by patient experiment. The feasibility of the system is verified by the methods of validity of the algorithm, recognition rate of the system action pattern and fatigue evaluation.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        review
        tables/charts
        tracings
        Journal Article
      ougenre: Article
    language: English
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