Characterization of Individual Alpha Frequency of EEG Signals as an Indicator of Cognitive Fatigue

Abstract

Cognitive fatigue is a condition caused by monotonous work which involving cognitive function in a long period that influences performance impairment. One of the methods to detect cognitive fatigue is using Individual Alpha Frequency (IAF) of brain waves which was obtained from an electroencephalography (EEG) measurement. This study aimed to calculate IAF values using power spectral density (PSD) as an indicator of cognitive fatigue in the frontal, parietal, and occipital lobes which used a cognitive task as the stimulus. The EEG was measured by using Cadwell Easy^ III with a sampling frequency of 250 Hz and the electrode impedance maintained below 20 k?. Electrodes on F3, F4, F7, F8, Fz, P3, P4, O1, and O2 were investigated in this study. The data acquisition was conducted in 46 minutes: 3 minutes before, 40 minutes during, and 3 minutes after carrying out the arithmetic test as a cognitive task. The arithmetic test was displayed through the visual display terminal (VDT). In the next stage, the preprocessing was conducted to remove noise and artifacts, followed by PSD calculation using the Welch periodogram. Finally, the values of IAF were calculated by using the Center of Gravity (CoG). The results showed that PSD in all session sorted by the largest values are delta, theta, and alpha wave. As for the IAF pre-task values shifted towards larger alpha frequency in the post-task in frontal and parietal region, showed in vigilance with increasing time spent on task, and shifted towards smaller values in occipital region which fatigue begins to occur in this region and has not occured in other region.