Wavelet-Based Entropy Analysis of Electromyography during 100 Jumps

Authors

  • L. Daniuseviciute Lithuanian Academy of Physical Education
  • K. Pukenas Lithuanian Academy of Physical Education
  • M. Brazaitis Lithuanian Academy of Physical Education
  • A. Skurvydas Lithuanian Academy of Physical Education
  • S. Sipaviciene Lithuanian Academy of Physical Education
  • I. Ramanauskiene Kaunas University of Technology
  • V. Linonis Kaunas University of Technology

Abstract

Muscle fatigue is a complex process that is most often defined as an exercise induced reduction in the ability of a muscle to generate force, and has been studied over numerous exercises for decades in an attempt to understand and indentify the mechanisms that lead to the loss of force production. One of muscle fatigue estimation is to assess changes in frequency measures of muscle electromiography signals. Electromiography signal is essentially a non-stationary signal, where muscle contraction can reach very high or small amplitudes. We used wavelet-based Shannon entropy to estimate the complexity of electromiography signals. Wavelet analysis is suitable tool for detecting and characterizing specific phenomena in time and frequency planes.

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Published

2010-10-12

How to Cite

Daniuseviciute, L., Pukenas, K., Brazaitis, M., Skurvydas, A., Sipaviciene, S., Ramanauskiene, I., & Linonis, V. (2010). Wavelet-Based Entropy Analysis of Electromyography during 100 Jumps. Elektronika Ir Elektrotechnika, 104(8), 93-96. Retrieved from https://eejournal.ktu.lt/index.php/elt/article/view/9237

Issue

Vol. 104 No. 8 (2010)

Section

MEDICINE TECHNOLOGY

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