Energy Spectral Density Analysis of Muscle Fatigue

Abstract

Driver’s vigilance level is easily distracted when in a state of fatigue and drowsiness. Most drivers’ shows sign of visual fatigue and loss of vigilance during long and monotonous driving. Their ability to maintain adequate driving performance is affected by various factors. A Popular technique to estimate driver’s vigilance level is physiological measure that uses electromyogram (EMG) signal in estimating driver muscle fatigue while driving. In this project, the EMG signal will be obtained by attaching the electrodes to the biceps brachii of each 15 subjects during playing Need for Speed (NFS) game for two hours. Be-fore that, subjects will answer a set of questionnaires and the scores obtained will be calculated. From the questionnaires, driver condition can be determined whether the driver is non-fatigue or mild fatigue or fatigue. Then signal preprocessing is applied to remove artifact in EMG signal. Next, the EMG signal is analyzed by using frequency domain analysis and Energy Spectral Density (ESD) extracted from the analysis. Mean, variance and peak energy of ESD is obtained from all the samples. Based on results obtained, the normalized mean (non-fatigue: 0.0514–0.1255), (mild fatigue: 0.0554–0.0802) and (fatigue: 0.0069–0.0188). For the variance range (non-fatigue: 0.0050–0.0311), (mild fatigue: 0.0054–0.0802) and (fatigue: 0.0006–0.0047). While for the peak energy of ESD (non-fatigue: 28,480–2,943,000 J/Hz), (mild fatigue: 99,440–120,500 J/Hz) and (fatigue: 537.7–11,440 J/Hz).