TITLE:
A mathematical Model to Predict Transition-to-Fatigue During Isometric Exercise on Muscles of the Lower Extremities
AUTHORS:
Jorge Garza-Ulloa, Huiying Yu, T. Sarkodie- Gyan, Pablo Rangel, Olatunde Adeoye, Noe Vargas Hernandez
KEYWORDS:
Surface Electromyography; Transition-to-Fatigue; Signal Processing; Median Frequency and Power Spectrum; Polynomial Regression Models
JOURNAL NAME:
Engineering,
Vol.4 No.10B,
January
16,
2013
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.