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

  • Authors:

  • Dongjun Kim;Seungjin Woo;Jeongwhan Lee;Kyeongseop Kim

  • Affiliations:

  • School of Electronics & Information Engineering, College of Science & Engineering, Cheongju University, Cheongju 360-764, Republic of Korea;School of Electronics & Information Engineering, College of Science & Engineering, Cheongju University, Cheongju 360-764, Republic of Korea;School of Biomedical Engineering, College of Biomedical & Health Science, Konkuk University, Chungju 380-701, Republic of Korea;School of Biomedical Engineering, College of Biomedical & Health Science, Konkuk University, Chungju 380-701, Republic of Korea

  • Venue:
  • ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
  • Year:
  • 2007

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Abstract

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.