EMG-based Fatigue Assessment During Endurance Testing With Different VT Protocols

BACKGROUND: Muscle fatigue can be defined as the failure of a muscle to maintain a reasonably expected force output. The multivariate approach to fatigue assessment is used because the multiple (EMG) feature provides more information than anyone. OBJECTIVE: This study presents a method of assessing muscle fatigue during endurance testing at 50% maximal voluntary contraction (MVC) using electromyography (EMG) information as indirect indices of fatigability in the forearm muscles, namely, flexor carpi ulnaris (FCU); flexor digitorum superficialis (FDS); extensor carpi ulnaris (ECU) and extensor carpi radialis brevis (ECRB). METHODS: A randomized comparative experimental design was used during endurance test with 8 VT protocols based on the different combinations of vibration frequency (35 and 45 Hz), amplitude (3g ± 0.5g and 9g ± 0.5g) and exposure duration (30 and 60 seconds) were given to the participants for 4 days. Random sampling of participants was done from two groups (56 / group): persons having a sedentary lifestyle (SL) and a group of construction workers (CW). RESULTS: MANOVA results showed a significant increase in EMG rms, median frequency, waveform length, mean absolute value (p<0.001) and variance of EMG signal (p<0.05) (except in ECU for SL and ECRB for CW on variance of EMG signal) after VT in all muscles of both groups. Therefore, an increase in the EMG parameter value after a grip endurance task that shows an increase in EMG signal amplitude is indicative of muscle fiber fatigue. Furthermore, the best correlation was found between the grip endurance with WL (r = 0.471, p < 0.001) and EMG rms (r = 0.401, p < 0.001) of the ECU muscle in the SL group only. CONCLUSIONS: The patterns of EMG signal represent the amplitude and spectral parameters of the signal, enabling real-time fatigue analysis. In addition, surface EMG information is useful for indirectly evaluating performance fatigue during the endurance test.