Journal of the Ergonomics Society of Korea (대한인간공학회지)

Ergonomics Society of Korea (대한인간공학회)
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The Effect of the Signal Stationarity on the EMG Frequency Analysis

허리 근육의 근전도 신호 안정성이 주파수 분석에 미치는 영향

  • Cho, Young-Jin (Department of Information and Industrial Engineering, Hanyang University) ;
  • Kim, Jung-Yong (Department of Information and Industrial Engineering, Hanyang University)
  • 조영진 (한양대학교 산업경영공학과) ;
  • 김정룡 (한양대학교 산업경영공학과)
  • Published : 2010.04.30
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Abstract

The purpose of this study is to investigate the stationarity of the electromyographic signal in various flexion angles, loads, and window sizes, which influence the result of the mean power frequency (MPF) and median frequency (MNF) analysis. Six healthy subjects participated in the experiment. They were tested in the combination of 3-level flexion angles (0 degree, 22.5 degree, 45 degree) and 3-level loads (0Nm, 30Nm, 60Nm). Electromyographic data were collected for 20 seconds during isometric contraction. The stationarity of collected data were analyzed with four different window sizes including 250, 500, 1000 and 2000ms. Two test methods for stationarity such as Reverse Arrangements Test and Modified Reverse Arrangements Test were used. In order to show the effect of nonstationarity, the increasing/decreasing trend of MPF and MNF trend were discussed. In results, the stationarity of the electromyographic signal decreased as flexion angle increased and load decreased while window size decreased based on Reverse Arrangements Test. The highest stationarity was shown at 500 ms window in Modified Reverse Arrangements Test. The inclination of MNF and MPF indicated 3.6-6.3%, 3.8-5.1% discrepancy compared to the result from stationary data.

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References

  1. Beck, T. W., Housh, T. J., Johnson, G. O., Weir, J. P., Cramer, J. T. andCoburn, J. W., Mechanomyographic and electromyographic time andfrequency domain responses during submaximal to maximal isokineticmuscle actions of the biceps brachii, European Journal of AppliedPhysiology, 92, 352-9, 2004.
  2. Beck, T. W., Housha, T. J., Weir, J. P., Cramer, J. T., Vardaxis, V., Johnson,G. O., Coburn, J. W., Malek, M. H. and Mielke, M., An examinationof the Runs Test, Reverse Arrangements Test, and modified ReverseArrangements Test for assessing surface EMG signal stationarity,Journal of Neuroscience Methods, 156(1-2), 242-248, 2006. https://doi.org/10.1016/j.jneumeth.2006.03.011
  3. Bilodeau, M., Cincera, M., Bertrand A. A., Gravel, D., Normality andstationarity of EMG signals of elbow flexor muscles during rampand step isometric contractions, Journal of Electromyography andKinesiology, 7, 87-96, 1997. https://doi.org/10.1016/S1050-6411(96)00024-7
  4. Blanco, S., Garcia, H., Quian, R., Quian, Q. R., Romanelli, L. and Rosso,O. A., Stationarity of the EEG series, IEEE Engineering in Medicineand Biology, 14, 395-9, 1995. https://doi.org/10.1109/51.395321
  5. Coburn, J. W., Housh, T. J., Cramer, J. T., Weir, J. P., Miller, J. M. and Beck,T. W., Mechanomyographic and electromyographic responses of thevastus medialis muscle during isometric and concentric muscleactions, The Journal of Strength and Conditioning Research, 19, 412-420, 2005. https://doi.org/10.1519/15744.1
  6. Coorevits, P., Danneels, L., Cambier, D., Ramon, H., Druyts, H., Karlsson,J. S., Moor, G. D. and Vanderstraeten, G., Correlations between shorttimeFourier- and continuous wavelet transforms in the analysis oflocalized back and hip muscle fatigue during isometric contractions,Journal of Electromyography and Kinesiology, 18(4), 637-644, 2008. https://doi.org/10.1016/j.jelekin.2007.01.006
  7. Cram, J. R. and Kasman, G. S., Introduction to Surface Electromyography,Gaitherburg, Md: Aspen Publishers, Inc, 1998.
  8. Duchêne, J. and Goubel, F., Surface electromyogram during voluntarycontraction: processing tools and relation to physiological events,CRC Critical Reviews in Bioengineering, 21, 313-97, 1993.
  9. Horita, T. and Ishiko, T., Relationships between muscle lactate accumulationand surface EMG activities during isokinetic contractions in man,European Journal of Applied Physiology, 56, 18-23, 1987. https://doi.org/10.1007/BF00696370
  10. Inbar, G. F. and Noujaim, A. E., On surface EMG spectral characterizationand its application to diagnostic classification, IEEE Transactions onBiomedical Engineering, 31(9), 597-604, 1984. https://doi.org/10.1109/TBME.1984.325303
  11. Kim, J. Y., Jung, M. C. and Haight, J. M., The sensitivity of autoregressivemodel coefficient in quantification of trunk muscle fatigue during asustained isometric contraction, International Journal of IndustrialErgonomics, 35(4), 321-330, 2005.
  12. McGill, G. A. and Norman, R. W., Partitioning the L4-L5 dynamic momentinto disc, ligamentous, and muscular components during lifting, Spine,11, 666-678, 1986. https://doi.org/10.1097/00007632-198609000-00004
  13. Oppenheim, A. V. and Schafer, R. W., Discrete-time signal processing, 2nded. Upper Saddle River: Prentice Hall, 1999.
  14. Perry, S. R., Housh, T. J., Weir, J. P., Johnson, G. O., Bull, A. J. andEbersole, K. T., Mean power frequency and amplitude of themechanomyographic and electromyographic signals during incrementalcycle ergometry, Journal of Electromyography and Kinesiology, 11,299-305, 2001. https://doi.org/10.1016/S1050-6411(00)00057-2
  15. Petrofsky, J. S., Frequency and amplitude analysis of the EMG duringexercise on the bicycle ergometer, European Journal of AppliedPhysiology, 41, 1-15, 1979.
  16. Polikar, R., The story of wavelets in Physics and Modern Topics inMechanical and Electrical Engineering, World Scientific andEngineering Society Press, 1999.
  17. Popivanov, D. and Todorov, A., Statistical procedures for interferenceEMG power spectra estimation, Medical & Biological Engineering& Computing, 24, 344-350, 1986. https://doi.org/10.1007/BF02442686
  18. Shankar, S., Gander, R. E. and Brandell, B. R., Changes in the myoelectricsignal (MES) power spectra during dynamic contractions,Electroencephalography and Clinical Neurophysiology, 73, 142-150,1989. https://doi.org/10.1016/0013-4694(89)90193-4
  19. Siegel, S. and Castellan, Jr. N. J., Nonparametric statistics for the behavioralsciences. 2nd ed. New York: McGraw-Hill, 1988.
  20. Soderberg, G. L., Selected Topics in Surface electromyography for Use inthe Occupational Setting: Expert Perspectives, Rockville, Md: USDept of Health and Human Services, Public Health Service,Publication No. 91-100, 1992.
  21. Waters, T. R., Putz-Anderson V. and Garg, A., Applications manual for the revised NIOSH lifting equation, DHHS(NIOSH) Pub. No. 94-110, U. S. Department of Health and Human services, National Institute for Occupational Safety and Health, Cincinnati, Ohio, 1994.

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