EMG signal analysis of fatigue muscle activity in manual lifting

Abstract

In manufacturing industries, manual lifting is commonly practiced by workers in their routine to move or transport the objects to a desired place. Manual lifting with high repetition and loading on the arm will contribute the effects of soft tissues and muscle fatigue that will affect the performance of the worker to work with efficient. This paper presents the analysis of EMG signal from muscle activity to see the performance of muscle fatigue. Various researchers have proposed fast Fourier transforms (FFT) in analysing the EMG signal. However, this technique only gives spectral information but does not provide temporal information. Thus, the technique is not suitable for EMG analysis that consists of magnitude and frequency variation. To overcome the limitation, spectrogram is proposed to analyse the signal because it can represent the signal in jointly time-frequency representation (TFR). In fatigue muscle activities, ten volunteers in fresh condition and no previous of history injury are used as the subjects. Data is taken from right Biceps Branchii with lifting height of 140 cm and load mass of 5 kg. This research shows that the repeatability of manual lifting will contribute to the muscle fatigue for all the phases stated in this paper. This study concludes that phase 2 contribute highest effort by doing manual lifting task, compared to phase 1, 3 and 4, but all phases experienced the muscle fatigue.