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.
This work was supported by the Regional Research Center Program on the Ministry of Education & Human Resources Development in Korea.
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References
Yoshida, T.: The Estimation of Mental Stress by 1/f Frequency Fluctuation of EEG. Brain Topography, 771–777 (1998)
Davidson, R.J.: Anterior Cerebral Asymmetry and the Nature of Emotion. Brain and Cognition 20, 125–151 (1992)
Eysenck, H.J., Eysenck, M.W.: Personality and Individual Differences: a Natural Science Approach. Plenum Press, New York (1985)
Schmidtke, J.I., Heller, W.: Personality, Affect and EEG: Predicting Patterns of Regional Brain Activity Related to Extraversion and Neuroticism. Personality and Individual Differences (2003)
Musha, T., Terasaki, Y., Haque, H.A., Ivanisky, G.A.: Feature Extraction from EEGs Associated with Emotions. In: Intl. Sympo. Artif. Life Robotics (Invited Paper), vol. 1, pp. 15–19 (1997)
Anderson, C.W., Sijercic, Z.: Classification of EEG Signals from Four Subjects during Five Mental Task. In: Solving Engineering Problems with Neural Networks Proceedings of the Conference on Engineering Applications in Neural Networks (EANN), pp. 407–414 (1996)
Hagan, M.T., Demuth, H.B., Beale, M.: Neural Network Design. PWS Publishing Co., Boston (1996)
Robinson, D.L.: The Technical, Neurological, and Psychological Significance of ‘Alpha’, ’Theta’, and ‘Delta’ Waves Confounded in EEG Evoked Potentials. Personality and Individual Differences 28, 673–693 (2000)
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Kim, D., Woo, S., Lee, J., Kim, K. (2007). Human Sensibility Evaluation Using Neural Network and Multiple-Template Method on Electroencephalogram (EEG). In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4492. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72393-6_140
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DOI: https://doi.org/10.1007/978-3-540-72393-6_140
Publisher Name: Springer, Berlin, Heidelberg
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