Brain Wave Real Time Monitoring System: The influence of music on brain wave

• Main Authors: Yun-tzai Liao, 廖允在
• Other Authors: Wing-kwong Wong
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/86821594400681511646

碩士 === 國立雲林科技大學 === 電子與資訊工程研究所 === 95 === The aim of this study is to develop a real time system for electroencephalogram (EEG) signal analysis. We use the system for real time acquisition and real time analysis of the EEG signals of a volunteer who is listening to different types of music (techno and classical). The δ, θ, α and β brain waves were observed and analyzed with wavelet transformation. The analogue EEG signal is measured by biomedical signal machine and transferred to digital signal using data acquisition module connected to a computer. The graphical user interface is developed with LabVIEW and the signal wavelet transformation algorithms are implemented with MATLAB programs. The advantages of our developed system are rapid prototyping and effective observation of dynamic variation of any biomedical signals. In this study, we found that when the music type changed, the volunteer’s brain wave variation can be clearly monitored in real time by the wavelet-based system. In this study, we investigate the musical influence on human’s EEG when a volunteer listens to different types of music (classical and techno). We collected data from forty people in an experiment. In the statistical results, we found that the volunteer’s brain wave energy (δ, θ, α, β) changed as a result of the music played. The volunteer’s α activity increased when listening to classical music (soft music). However, the volunteer’s α activity dropped when listening to techno-music (high music). Besides, we found that the volunteers felt very tense and excited when listening to techno-music (β activity increased).