• DocumentCode
    2447860
  • Title

    Research of Feature Extraction Method for Stroke Patients´ Surface Electromyography

  • Author

    Liye, Ren ; Xiaoli, Wang ; Xiao, Wang

  • Author_Institution
    Dept. of Electron. Inf. Eng., Changchun Univ., Changchun, China
  • fYear
    2012
  • fDate
    1-3 Nov. 2012
  • Firstpage
    322
  • Lastpage
    324
  • Abstract
    Surface electromyography is a one-dimensional time series signal of neuromuscular system recorded from skin surface. It can reflect the states of muscle activity and muscle function accurately. All the subjects had to perform dynamic contraction for stroke´s knee flexion and extension in experiment. The surface electromyography were collected by surface electrodes and then processed by linear time and frequency-domain method. SEMG characteristics extraction has been done and an eigenvector space of mode recognition was built, and lies the theoretical and technical foundation for stroke patients´ rehabilitation training.
  • Keywords
    electromyography; feature extraction; frequency-domain analysis; medical signal processing; patient rehabilitation; SEMG characteristics extraction; dynamic contraction; eigenvector space; feature extraction method; frequency-domain method; linear time method; mode recognition; muscle activity; muscle function; neuromuscular system; one-dimensional time series signal; skin surface; stroke knee flexion; stroke patient rehabilitation training; stroke patient surface electromyography; surface electrode; Eigenvalues and eigenfunctions; Electrodes; Electromyography; Frequency domain analysis; Muscles; Skin; Time domain analysis; feature extraction; storke; surface electromyography;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Networks and Intelligent Systems (ICINIS), 2012 Fifth International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-1-4673-3083-1
  • Type

    conf

  • DOI
    10.1109/ICINIS.2012.78
  • Filename
    6376553