Human Sensibility Evaluation Using Neural Network and Multiple-Template Method on Electroencephalogram (EEG)

摘要

This study presents a human sensibility evaluation method using neural network and multiple-template method on electroencephalogram (EEG). For our research objective, 10-channel EEG signals are collected from the healthy subjects. After the necessary preprocessing is performed on the acquired signals, the various EEG parameters are estimated and their discriminating performance is evaluated in terms of pattern classification capability. In our study, Linear Prediction (LP) coefficients are utilized as the feature parameters extracting the characteristics of EEG signal, and a multi-layer neural network is evaluated for indicating the degree of human sensibility. Also, the estimation for human comfortableness is performed by varying temperature and humidity environment factors and our results showed that our proposed scheme achieved the good performance for evaluating human sensibility.