A New Approach to Noninvasive-Prolonged Fatigue Identification Based on Surface EMG Time-Frequency and Wavelet Features.

In sports, fatigue management is vital as adequate rest builds strength and enhances performance, whereas inadequate rest exposes the body to prolonged fatigue (PF) or also known as overtraining. This paper presents PF identification and classification based on surface electromyography (EMG) signals. An experiment was performed on twenty participants to investigate the behaviour of surface EMG during the inception of PF.

Features selection for Bayes classification of prolonged fatigue on rectus femoris muscle.

Sports training is very important to athletes in improving and maintaining their performances. It commonly involves high intensity exercise and requires longer time for fatigue to recover, compares to normal activity. During training, adequate rest is essential to allow recuperation and build body strength.

Amplitude and frequency changes in surface EMG of biceps femoris during five days Bruce Protocol treadmill test.

Electromyography (EMG) is one of the indirect tools in indexing fatigue. Fatigue can be detected when there are changes on amplitude and frequency. However, various outcomes from literature make researchers conclude that EMG is not a reliable tool to measure fatigue.