Spectral Analysis of EEG Patterns in Normal Adults

J Korean Neurol Assoc > Volume 17(3); 1999 > Article

Journal of the Korean Neurological Association 1999;17(3): 384-388.

정상뇌파의 스펙트럼 분석

이화의대 신경과학교실, 이화의과학 연구소

Spectral Analysis of EEG Patterns in Normal Adults

Kyoung Gyu Choi, M.D.,Ph.D

Department of Neurology, Ewha University Medical College 911-1 Mok-dong Yangcheon-ku Seoul, Korea

Abstract

Background: Recently, the quantitative analysis of biological signals has been possible due to the development of digital machines, new mathematical theories including the nonlinear time series, chaotic and dynamic theories, and convenient statistical tools. The characteristics of biological signals however, can not analyzed solely through visual interpretation or judgement. The author statistically analyzed the EEG data of normal adults by using spectral analysis.
Methods: Quantitative EEG analysis was performed in 5 normal adults in order to analyze differences between the left and right hemispheres and interelectrode differences of the power spectrum of variable frequency bands. The results were statistically analyzed using SPSS.
Results: The spectral powers of the left frontal delta, the right parietal theta and left frontal alpha were significantly higher than the opposite sides. In the analysis of interelectrode difference, the tem-poral beta band power was significantly higher than the frontal areas. There were no significant interelectrode differ-ences in other frequency bands. C o n c l u s I o n s: The results of this study show that there are differences between the visually perceived EEG patterns and the frequency domain analysis. These findings suggest that EEG waves on record-ing papers are the results of interference among variable frequency bands. The continued analysis of EEG by using nonlinear parameters will be beneficial as a powerful tool in understanding the neural network dynamic in the brain. J Kor Neurol Ass 17(3):384 ~ 388, 1999 Key Words : Spectral analysis, Power spectrum, Electroencephalograph