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A Method for Structure Analysis of EEG Data -Application to ANOVA in Vegetable Ingestion-


Takashi Ajiro, Akiko Yamanouchi, Koichiro Shimomura, Hirobumi Yamamoto, Kenichi Kamijo


Vol. 9  No. 9  pp. 70-82


Electroencephalogram (EEG) data, which consist of weak voltage values of the brain measured over time, are recorded by EEG measuring instruments (Brain Builder Unit in this study). These data are captured in real time and written to a file in CSV (Comma Separated Values) format. By applying several processes using the data, we extract the crossed data and conduct an analysis of variance (ANOVA), and we assess the significance of the influence of the measuring object on the EEG of a human examinee. First, we captured EEG patterns of examinees ingesting the vegetable komatsuna and then conducted the ANOVA to determine whether the growing condition of the vegetable affects the EEG pattern of the examinee. However, much manual work and time are needed to convert the EEG to the data for displaying graph on Microsoft Excel 2003, and analysing it by ANOVA software. Therefore, we propose an automation algorithm for converting the captured data from the EEG measuring device, and we develop (implement) a program based on this algorithm. Specifically, the automation algorithm combines these manual processes to make the two kinds of data needed for ANOVA and for Excel graphs, and the C++ program generates the actual data.


ANOVA, SOC, EEG, vegetable ingestion, komatsuna, algorithm, program implementation