脳波信号を対象としたEPIAモデル構造に関する研究

抄録

EEG (Electroencephalogram) which is influenced by various factors such as thought and mental state has very high-order information. However, it is difficult to handle this since the time series waveform of EEG is complicated. Therefore, an analysis method such as mathematically modeling the behavior of the time series waveform and experimentally identifying model parameters is a possible approach. The aim of this study is to exam the optimal model structure for EEG analysis, we compared three different types of equations. Two of them are nonlinear equations, and the other is a linear equation. we considered which model is a suitable for complex EEG signals.