An Approach to Estimate the Activation of Different Bands of EEG Signal using Classified Songs

Abstract

Human cognition analysis from EEG signal is one of the most significant way to find the causes which affect human brain. Songs are familiar stimuli to analyze the effectiveness of different EEG bands because it is a common source of entertainment. According to linguistic variation, subject age and preference, volume level of songs, the impact on different EEG bands varies. In this research, a work has been performed to estimate the effect of songs on different EEG bands (delta, theta, alpha, beta). The songs have been categorized into three types: mild, pop, rock according to their PSD value which are 0.2114 W/Hz, 0.3271 W/Hz and 0.8448 W/Hz respectively. the volume levels are considered as 0 %-14 % volume level for low volume, 26%- 60% volume level for comfortable volume and 61%-100% volume level for high volume. An ANOVA test has been conducted to indicate the significance variation in EEG band and in which P-value has been set 0.05. For the mild, pop, and rock songs the P-values for alpha bands are 0.0146, 0.006 and 0.0006 respectively and the values indicate that alpha band is mostly active while listening to different songs. A topographical representation has been done based on the effects of songs on the alpha band activity for mild, pop and rock songs at three volume level. The maximum percentage of alpha band activation is 60% in comfortable volume which indicates that, when the volume is high human cognition state moves from relax to stress condition in which beta band is active.