전기학회논문지 (The Transactions of The Korean Institute of Electrical Engineers)

  • 제56권4호
  • /
  • Pages.809-816
  • /
  • 2007
  • /
  • 1975-8359(pISSN)
  • /
  • 2287-4364(eISSN)
대한전기학회 (The Korean Institute of Electrical Engineers)
권호 표지

일정한 자의 수축 시 표면 근전도 신호에 대한 Spike 변수 해석

Spike Variable Analysis of Surface EMG Signal During Constant Voluntary Contraction

  • 양희원 (강원대학교 삼척캠퍼스 제어계측공학과) ;
  • 정의곤 (강원대학교 삼척캠퍼스 제어계측공학과) ;
  • 이진 (강원대학교 삼척캠퍼스 제어계측공학과)
  • 발행 : 2007.04.01
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

This paper presents an analysis of the SEMG signal quantitatively and automatically using spike variables : MSF, MSA, MSS, and MSD. The SEMG signals were recorded in three muscle parts, first dorsal interosseus, biceps brachii and abductor policis brevis, from 14 normal subjects. Emphasis was placed on the following 3 points in the experiments. 1) Suggest proper window length to estimate the spike variables 2) Investigate variation of the spike variables to varying %MVC. 3) Investigate variation of the spike variables to the sustained contraction for 30 minutes. Quantitative results were showed and examined in point of practical clinical application.

키워드

참고문헌

  1. J. V. Basmaiian and C. J. De Luca, Muscles alive : Their functions revealed by electromyography., Baltimore, MD, Williams & Wilkins, 1985
  2. R. S. LeFever and C. J. De Luca, ' A procedure for decomposing the myoelectric signal into its constituent action potentials,' IEEE Trans. Biomed. Eng., vol. BME-29, pp. 149-153, 1982 https://doi.org/10.1109/TBME.1982.324881
  3. D. Zennaro, P. Wellig, V. M. Koch, G. S. Moschytz and T. Laubli, ' A software package for decomposition of long-term multichannel EMG signals using wavelet coefficients,' IEEE Trans. Biomed. Eng., vol. BME-50, pp. 58-69, 2003
  4. R. Merletti, ' Surface electromyography: possibilities and limitations,' J. Rehab. Sci., vol. 7, 24-34, 1994
  5. R. Merletti and L.R. Lo Conte,' Advances in processing of surface myoelectric signal processing, Part I and Part Il,' Med. Biol. Eng. Comput., vol. 33, 362-384, 1995 https://doi.org/10.1007/BF02510518
  6. S. D. Nandedkar, D. B. Sanders and E. V. Stalberg,' Simulation and analysis of the electromyographic interference pattern in normal muscle. Part I: Turns and amplitude measurements,' Muscle Nerve, vol. 9, pp, 423-430, 1986 https://doi.org/10.1002/mus.880090507
  7. 이진, 강원희, 김성환, 'T/A 변수를 이용한 표면근전도 간섭패턴의 정량적 해석에 관한 연구', 대한전기학회지, 제54D권, 제5호, pp.348-357, 2005
  8. D.A. Gabriel, 'Reliability of SEMG spike parameters during concentric contractions', Electrornyogr. Clin. Neurophysiol., vol. 40, pp. 423-430, 2000
  9. D.A. Gabriel, J.R. Basford, K.N An, 'Assessing fatigue with electromyographic spike parameters', IEEE Eng. in Medicine and Biology Magazine, pp. 90-96, Nov./Dee., 2001
  10. A. Papoulis, Probability, random variables and stochastic processes, Mcgraw-Hill, NY, 1965
  11. R. Merletti and L.R. Lo Conte,' Surface EMG signal processing during isometric contraction,' J. Electromyogr. Kinesiol., vol. 7, No.4, pp. 241-250, 1997
  12. D. Farina and R. Merletti,' Comparison of algorithms for estimation of EMG variables during voluntary isometric contraction,' J. Eleetromyogr. Kinesiol., vol. 10, pp. 337-349, 2000 https://doi.org/10.1016/S1050-6411(00)00025-0
  13. http://www.delsys.com
  14. C. M. Thompson and L. Shure, Matlab and Simulink User's Guide, T Mathworks Inc., 2002