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A Study on Low Frequency Band Selection as a Fatigue Parameter in Surface EMG during Isotonic Exercise of Biceps Brachii Muscle

상완이두근의 등장성 운동시 근피로인자로서 표면근전도의 저주파수대역 선정에 관한 연구

  • Lee, Sang-Sik (Dept. of Biomedical Engineering, Kwandong University) ;
  • Lee, Ki-Young (Dept. of Biomedical Engineering, Kwandong University)
  • Received : 2011.05.12
  • Accepted : 2011.07.26
  • Published : 2011.08.30

Abstract

Muscle fatigue is characterized as a progressive increase in discomfort arising from the active muscle at moderate load levels are maintained. The median frequency is the most commonly used as a parameter to describe muscle fatigue. However, the estimate of the median frequency is difficult to indicate muscle fatigue because of its high standard deviation and instability. This paper investigates the power changes of the appropriate low frequency band as a fatigue parameter in EMG during isotonic exercise. To select the appropriate band, linear regression lines are employed to calculate the slopes and the coefficient of determination. Three females and seven males volunteered to participate in surface EMG recordings placed on the biceps brachii and each recording experiment continued until their exhaustion. The results of experiment shows that the power changes of the selected low frequency band (15~45 Hz) have linear slopes and high determinant coefficients. Therefore, this fatiguing parameter using the power changes of the low frequency band is valid to measure the state of muscular fatigue.

Keywords

References

  1. Allison, G. T. and T. Fujiwara. 2002. The Relationship between EMG Median Frequency and Low Frequency Band Amplitude Changes at different Levels of Muscle Capacity, Clinical Biomechanics 17:464-469. https://doi.org/10.1016/S0268-0033(02)00033-5
  2. Arabadzhiev, T. I., G. V. Dimitrov and N. A. Dimitrova. 2005. Simulation analysis of the performance of a novel high sensitive spectral index for quantifying M-wave changes during fatigue, J. of Electromyography and Kinesiology 15:149-158. https://doi.org/10.1016/j.jelekin.2004.08.003
  3. Bigland-Ritchie, B., E. F. Donovan. and C. S. Roussos. 1981. Conduction Velocity and EMG Power Spectrum Changes in Fatigue of Sustained Maximal Efforts, Journal of Applied Physiol 51:1300-1305.
  4. Chanran, E., B. Maton. and A. Fourment 2002. Effect of Postural Muscle Fatigue on the Relation between Segmental Posture and Movement, Journal Electromyography and Kinesiology 12:67-69. https://doi.org/10.1016/S1050-6411(01)00027-X
  5. De, Luca C. J. 1997. The Use of Surface Electromyography in Biomechanics, Journal Appl. Physiol 13(2):135-163.
  6. Duchene, J. and F. Goubel. 1990. EMG Spectral Shift as an Indicator of Fatigability in an Heterogeneous Muscle Group, Eur. Journal Appl. Physiol 61:81-87. https://doi.org/10.1007/BF00236698
  7. Hagg, G. 1981. Electromyographic Fatigue Analysis based on the Number of Zero Crossings, Pflugers Arch. 391:78-80. https://doi.org/10.1007/BF00580699
  8. Jennifer, L. Olive. Jill M. Slade. Gary A. Dudley and Kevin K. McCully. 2003. Blood Flow and Muscle Fatigue in SCI Individuals during Electrical Stimulation, ISBN United States:934.
  9. Jukka, H., Viitasalo T. and Paavo V. Komi. 1977. Signal Characteristics of EMG during Fatigue, European Journal of Applied Physiol 37(2):111-121. https://doi.org/10.1007/BF00421697
  10. Jung, Ilkyu. and Yun Jinhwan. 2006. Human Performance & Exercise Physiology, Daekyung books:404-412. (In Korean)
  11. Kendall Atkinson. 1993. Elementary Numerical Analysis, John Wiley &Sons.
  12. Lee, K. Y., K. Y. Shin. H. S. Kim and J. H. Mun. 2009. Estimating Muscle Fatigue of the Biceps Brachii using High to Low Band Ratio in EMG during Isotonic Exercise, International Journal of Precision Engineering and Manufacturing 10(3):147-153. https://doi.org/10.1007/s12541-009-0060-x
  13. Lim, D. S., K. S. Lee, A. R. Choi, Y. J. Kim, J. H. Mun. 2009. Bio-mechanical Analysis on the Lower Back using Human Model during Pushing the Manual Vehicles, Journal of Biosystem Engineering 34(4):286-294. (In Korean) https://doi.org/10.5307/JBE.2009.34.4.286
  14. Lim, D. S., Y. J. Kim, K. S. Lee, J. H. Mun. 2011. Biomechanical Evaluation of Squatting Posture with Asymmetric Trunk Motion, Journal of Biosystem Engineering 36(1):58-67. (In Korean) https://doi.org/10.5307/JBE.2011.36.1.58
  15. Lowery, M., P. O. Nolan and M. Malley. 2002. Electromyogram median frequency, spectral compression and muscle fibre conduction velocity during sustained sub-maximal contraction of the brachioradialis muscle, Journal Electromyography and Kinesiology 12(2):111-118. https://doi.org/10.1016/S1050-6411(02)00004-4
  16. Masuda, K., T. Masuda. T. Sadoyama. M. Inaki and S. Katsuta. 1999. Changes in Surface EMG Parameters during Static and Dynamic Fatiguing Contractions, Journal Electromyography and Kinesiology 9(1):39-46. https://doi.org/10.1016/S1050-6411(98)00021-2
  17. Petrofsky, J. S., R. M. Glaser. C. A. Phillips. A. R. Lind and C. Williams. 1982. Evaluation of the Amplitude and Frequency Components of the Surface EMG as an Index of Muscle Fatigue, Ergonomics 25(3):213-223. https://doi.org/10.1080/00140138208924942
  18. Ritter, A. B. 2005. Biomedical Engineering Principles, Taylor & Francis.
  19. R. Merletti. L. R. Lo Conte and C. Orizio. 1991. Indices of Muscle Fatigue, Journal of Electromyograhy and Kinesiology 1(1):20-33. https://doi.org/10.1016/1050-6411(91)90023-X
  20. Roman-Liu, D. and M. Konarska. 2009. Characteristics of Power Spectrum Density Function of EMG during Muscle Contraction below 30%MVC, Journal of Electromyograhy and Kinesiology 19:864-874. https://doi.org/10.1016/j.jelekin.2008.05.002
  21. Stulen, F. B. and C. J. De Luca. 1981. Frequency Parameters of the Myoelectric Signal as a Measure of Muscle Conduction Velocity, IEEE Trans. Biomed. Eng 28:515-523. https://doi.org/10.1109/TBME.1981.324738

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