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Determination of Fatigue Following Maximal Loaded Treadmill Exercise by Using Wavelet Packet Transform Analysis and MLPNN from MMG-EMG Data Combinations

  • Systems-Level Quality Improvement
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Abstract

The muscle fatigue can be expressed as decrease in maximal voluntary force generating capacity of the neuromuscular system as a result of peripheral changes at the level of the muscle, and also failure of the central nervous system to drive the motoneurons adequately. In this study, a muscle fatigue detection method based on frequency spectrum of electromyogram (EMG) and mechanomyogram (MMG) has been presented. The EMG and MMG data were obtained from 31 healthy, recreationally active men at the onset, and following exercise. All participants were performed a maximally exercise session in a motor-driven treadmill by using standard Bruce protocol which is the most widely used test to predict functional capacity. The method used in the present study consists of pre-processing, determination of the energy value based on wavelet packet transform, and classification phases. The results of the study demonstrated that changes in the MMG 176–234 Hz and EMG 254–313 Hz bands are critical to determine for muscle fatigue occurred following maximally exercise session. In conclusion, our study revealed that an algorithm with EMG and MMG combination based on frequency spectrum is more effective for the detection of muscle fatigue than EMG or MMG alone.

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Acknowledgments

The research has been supported with project number: 2014.01.0102.001 by the Research Project Department of Akdeniz University, Antalya, Turkey. This study was approved as ethically by Akdeniz University, Faculty of Medicine, Scientific Research Assessing Authority with date/number:21.12.2010/220.

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Authors and Affiliations

  1. Vocational School of Technical Sciences, Mehmet Akif Ersoy University, Burdur, Turkey

    Gürkan Bilgin

  2. School of Physical Education and Sports, Akdeniz University, Antalya, Turkey

    İ. Ethem Hindistan & Y. Gül Özkaya

  3. Faculty of Engineering, Department of Electrical and Electronics Engineering, Gazi University, Ankara, Turkey

    Etem Köklükaya

  4. Faculty of Engineering, Department of Electrical and Electronics Engineering, Akdeniz University, Antalya, Turkey

    Övünç Polat & Ömer H. Çolak

  5. Institute of Natural Science, Department of Electrical and Electronics Engineering, Sakarya University, Sakarya, Turkey

    Gürkan Bilgin

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  1. Gürkan Bilgin
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  2. İ. Ethem Hindistan
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  3. Y. Gül Özkaya
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  6. Ömer H. Çolak
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Correspondence to Ömer H. Çolak.

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This article is part of the Topical Collection on Systems-Level Quality Improvement

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Bilgin, G., Hindistan, İ.E., Özkaya, Y.G. et al. Determination of Fatigue Following Maximal Loaded Treadmill Exercise by Using Wavelet Packet Transform Analysis and MLPNN from MMG-EMG Data Combinations. J Med Syst 39, 108 (2015). https://doi.org/10.1007/s10916-015-0304-5

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