Evaluation of Lower Limb Muscles Fatigue and Force during Running 400-Meters Using Learning Machine

Abstract

The main goal of this research work is to study and evaluate the muscles force and fatigue of Gastrocnemius Medialis (GMS), Gluteus Maximus (GM), and Gastrocnemius Lateralis (GL) during running for 400-meters based on surface Electromyography (sEMG) signals. The sEMG signals of the selected muscles from the right leg have been collected by using bipolar electrodes from 15 subjects during the run on the tartan athletic track with two pacing strategies. The first strategy: 1st 200-meters running 87% - 94% of full speed and last 200-meters sprinting (full speed). The second strategy: 1st 300-meters running 87% - 94% of sprinting and last 100-meters sprinting. The rate of fatigue has been calculated by using Root Mean Square (RMS) and Median Frequency (MDF) features. Then, the slopes of linear regression were calculated from both RMS and MDF at each 100-meters. The linear slope values represented the rate of fatigue and force. From the results of 1st and 2nd running strategies, the force of GM and GL muscles increased during the 4th 100-meters of the 1st strategy and decreased with GM and GMS muscles during the 4th 100-meters of the 2nd strategy. The less index fatigues were during the 1st strategy for most selected muscles. Finally, it can be concluded the running with the 1st strategy get less fatigues and the force of most selected muscles increased compared with the 2nd strategy based on the results of time and frequency domain features (RMS and MDF).