| Title |
A Study on Application of the Multi-layor Perceptron to the Human Sensibility Classifier with Eletroencephalogram |
| DOI |
http://doi.org/10.5370/KIEE.2018.67.11.1506 |
| Keywords |
Human sensibility classifier ; Neural network ; Multiple-template method ; Linear prediction ; EEG signal |
| Abstract |
This study presents a human sensibility evaluation method using neural network and multiple-template method on electroencephalogram(EEG). We used a multi-layer perceptron type neural network as the sensibility classifier using EEG signal. 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 used 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 the proposed scheme achieved good performances for evaluation of human sensibility. |