Research ArticleOpen AccessGoogle Scholar indexed
A mathematical Model to Predict Transition-to-Fatigue During Isometric Exercise on Muscles of the Lower Extremities
Department of Electrical and Computer Engineering, UTEP, El Paso, Texas, USA
Department of Electrical and Computer Engineering, UTEP, El Paso, Texas, USA
Department of Electrical and Computer Engineering, UTEP, El Paso, Texas, USA
Department of Electrical and Computer Engineering, UTEP, El Paso, Texas, USA
Department of Electrical and Computer Engineering, UTEP, El Paso, Texas, USA
Mechanical Engineering Department, UTEP, El Paso, Texas, USA
- 1 Department of Electrical and Computer Engineering, UTEP, El Paso, Texas, USA
- 2 Department of Electrical and Computer Engineering, UTEP, El Paso, Texas, USA
- 3 Department of Electrical and Computer Engineering, UTEP, El Paso, Texas, USA
- 4 Department of Electrical and Computer Engineering, UTEP, El Paso, Texas, USA
- 5 Department of Electrical and Computer Engineering, UTEP, El Paso, Texas, USA
- 6 Mechanical Engineering Department, UTEP, El Paso, Texas, USA
Copy link · social · email
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.
KeywordsSurface ElectromyographyTransition-to-FatigueSignal ProcessingMedian Frequency and Power SpectrumPolynomial Regression Models
- 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.
- 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.
- 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.
- 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.
- R. Srivastra. Polynomial Regression, I.A.S.R.I. Library Avenue, New Delhi.
- 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.
- 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.
- R. Merletti, P.A. Parker, Electromyography: Physiology, Engineering and Non-Invasive Applications, John Wiley and sons, Inc.: New York, NY, USA, 2004.
- 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.
- 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.
- 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.
- 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.
- 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.