부산대학교 도서관

Electroencephalogram (EEG) signal is one of the tools for neuroscience to study the brain activity behavior. There are several methods to extract information from the EEG signal, in this work, we studied three methods to characterize the EEG signals: spectral analysis to measure the power of certain brain regions on alpha band, fractal dimension to measure complexity level of EEG signals and correlation coefficient to measure the level of interhemispheric synchrony. We discuss the advantages of each method and how it could be used in neuroscience. We also present an application example evaluating EEG signal features changes produced as an effect of a meditation program. It was not found a trend effect for all subjects, nevertheless interesting individual behaviors were found, especially in synchrony behavior for corresponding interhemispheric channels.