A mathematical Model to Predict Transition-to-Fatigue During Isometric Exercise on Muscles of the Lower Extremities

Jorge Garza-Ulloa, Huiying Yu, T. Sarkodie- Gyan, Pablo Rangel, Olatunde Adeoye, Noe Vargas Hernandez

Department of Electrical and Computer Engineering, UTEP, El Paso, Texas, USA.
Mechanical Engineering Department, UTEP, El Paso, Texas, USA.

DOI: 10.4236/eng.2012.410B005                

Abstract

Surface Electromyography (sEMG) activities of the four muscles were studied from twelve healthy subjects to analyze muscle fatigue. Data were recorded while subjects performed isometric exercises for a period of time until fatigue. The signal was segmented with 5000 samples to enable the evolutionary process. Based on the mean power spectrum and Median Frequency (MDF) of each segment, we developed a methodology that is able to detect the signal into a meaningful sequence of Non-Fatigue to Transition-to-Fatigue. By identifying this transitional fatigue stage, it is possible to predict when fatigue will occur, which provides the foundation of the automated system that has the potential to aid in many applications of our lives, including sports, rehabilitation and ergonomics.

Keywords

Surface Electromyography; Transition-to-Fatigue; Signal Processing; Median Frequency and Power Spectrum; Polynomial Regression Models

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	M.R. Al-Mulla , F. Sepulveda, M. Colley. A Review of Non-Invasive Techniques to Detect and Predict Localised Muscle Fatigue. Sensors, 2011,11(4), pp. 3545-3594.
[2]	KM.Calder, DW. Stashuk, L. McLean, Physiological characteristics of motor units in the brachioradialis muscle across fatiguing low-level isometric contractions. J. Electromyograph. Kinesiol. 2008, 18(1):, pp. 2–15.
[3]	D. Kay , A. St Clair Gibson , M.J. Mitchell, M.I. Lambert , T.D. Noakes, Different neuromuscular recruitment patterns during eccentric, concentric and isometric contractions. Journal of Electromyography Kinesiology, 2000, 10(6): pp. 425–431.
[4]	M.R.. Al-Mulla, Statistical class separation using sEMG features towards automated muscle fatigue detection and prediction. International congress on image and signal processing, Tianjin, China, 17–19 October 2009; pp. 1–5.
[5]	R. Srivastra. Polynomial Regression, I.A.S.R.I. Library Avenue, New Delhi.
[6]	M.R. Al-Mulla, F Sepulveda,. M. Colley, sEMG Techniques to Detect and Predict Localised Muscle Fatigue. EMG Methods for Evaluating Muscle and Nerve Function, ISBN: 978-953-307-793-2. 2011.
[7]	J.A. Faulkner, L.M. Larkin, D.R. Claflin, S.V. Brooks, Age-related changes in the structure and function of skeletal muscles. Clin. Exp. Pharmacol. Physiol. 2007, 34 (11): pp. 1091–1096.
[8]	R. Merletti, P.A. Parker, Electromyography: Physiology, Engineering and Non-Invasive Applications, John Wiley and sons, Inc.: New York, NY, USA, 2004.
[9]	S.D. Mair, A.V. Seaber, R.R Glisson, W.E Garrett, The role of fatigue in susceptibility to acute muscle strain injury. Am. J. Sport. Med. 1996, 24(2): pp. 137–143.
[10]	P. Herberts, R.. Kadefors, H Broman. Arm positioning in manual tasks: An electromyographic study of localized muscle fatigue. Ergonomics 1980, 23 (7): pp. 655–665.
[11]	M. B. I. Reaz, M. S. Hussain, F. Mohd-Yasin. Techniques of EMG signal analysis: detection, processing, classification and applications. Biological Procedures Online, 2006, 8: pp. 11-35.
[12]	Mohammadreza Asghari Oskoei, Huosheng Hu and John Q. Gan. Manifestation of Fatigue in Myoelectric Signals of Dynamic Contractions Produced During Playing PC Games. 30th Annual International IEEE EMBS Conference Vancouver, Canada, August 20-24, 2008.
[13]	Q. Zhou, Y. Chen, C. Ma, X. Zheng, Evaluation of upper limb muscle fatigue based on surface electromyography. Sci China Life Sci. 2011 Vol.54(10): pp. 939–944.
[14]	Isa Halim, Abdul Rahman Omar, Alias Mohd Saman, Ibrahim Othaman. Assessment of Muscle Fatigue Associated with Prolonged Standing in the Workplace. Safe Health Work 2012;(3): pp.31-42.
[15]	P. V. Komi, P. Tesch. EMG frequency spectrum, muscle structure, and fatigue during dynamic contractions in man. European Journal of Applied Physiology and Occupational Physiology, 1979;42(1): pp. 41-50.
[16]	D.A. Winter. Biomechanics and Motor Control of Human Movement. 3rd Edition, John Wiley and Sons Inc., 2005.
[17]	Marieb, Human Anatomy & Physiology, 5th Edition, Benjamin Cummings, San Francisco, 2001.
[18]	Sheir, Butler, & Lewis Hole, Book: Human Anatomy 10th Edition, McGraw Hill, 2004.
[19]	Gerold Ebenbichler, Josef Kollmitzer, Michael Quittan, Frank Uhl,Chris Kirtley, Veronika Fialka. EMG fatigue patterns accompanying isometric fatiguing knee-extensions are different in mono- and bi-articular muscles. Electroencephalography and clinical Neurophysiology 109 (1998) : pp. 256–262.
[20]	M. Mischi, C. Rabotti, and M. Cardinale. Electromyographic Assessment of Muscle Fatigue During Isometric Vibration Training at Varying Frequencies. 32nd Annual International Conference of the IEEE EMBS Buenos Aires, Argentina, August 31 - September 4, 2010.
[21]	Stephen Minning , Colin A. Eliot, Tim L. Uhl, Terry R. Malone. EMG analysis of shoulder muscle fatigue during resisted isometric shoulder elevation. Journal of Electromyography and Kinesiology, 2007, 17: pp. 153–159.