Analysis of the EEG Signals Response to Musical Signal Stimuli

In recent years, many studies have shown that music can reflect quantifiable physiological effects on human. However, in the part of EEG, not many research projects have made use of EEG to verify the music influence on human brain activity. This research has emphasized on the development of analytical tools and methods for bio-signals, especially focused on the part of EEG with musical signal stimuli. We can use frequency distribution analysis and linear separation algorithms such as the Independent Component Analysis (ICA) to analyze the data collected from the scalp electrodes. The ultimate goal is to analyze EEG responses of subjects with different musical signal stimuli. It is expected that different musical signal stimuli can be classified and therefore the correlation between music and bio-signal characteristics can be demonstrated. In this study, we have found out that when subjects were listening to Soft and subject-preferred music, the EEG power at parietal points-P3 P4 Pz located on alpha band and theta band-were both on the rise. When subjects were listening to rock music and at baseline, however, the EEG power at parietal was decreasing. These findings have confirmed that the differences in music stimulation have reflected physiological effects on human EEG.