The Transactions of The Korean Institute of Electrical Engineers (전기학회논문지)

The Korean Institute of Electrical Engineers (대한전기학회)
권호 표지
DOI QR코드

DOI QR Code

A Study on Application of the Multi-layor Perceptron to the Human Sensibility Classifier with Eletroencephalogram

뇌파의 감성 분류기로서 다층 퍼셉트론의 활용에 관한 연구

  • Kim, Dong Jun (Division of Electronic Engineering Convergence, Cheongju University)
  • Received : 2018.06.08
  • Accepted : 2018.10.22
  • Published : 2018.11.01
Download PDF
⟨ Previous Next ⟩

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.

Keywords

References

  1. R. J. Davidson, "Anterior cerebral asymmetry and the nature of emotion", Brain and Cognition, Vol. 20, pp. 125-151, 1992. https://doi.org/10.1016/0278-2626(92)90065-T
  2. A. Myrden, T. Chau, "A passive EEG-BCI for single-trial detection of changes in mental state", IEEE Trans. Neural systems and Rehab. Eng., Vol. 25, No. 4, pp. 345-356, 2017. https://doi.org/10.1109/TNSRE.2016.2641956
  3. T. Yoshida, "The estimation of mental stress by 1/f frequency fluctuation of EEG", Brain topography, pp. 771-777, 1998.
  4. T. Musha, Y. Terasaki, H. A. Haque, and G. A. Ivanisky, "Feature extraction from EEGs associated with emotions", Intl. Sympo. Artif. Life Robotics (Invited Paper), Vol. 1, pp. 15-19, 1997.
  5. C. W. Anderson and Z. Sijercic, "Classification of EEG signals from four subjects during five mental tasks", In Solving Engineering Problems with Neural Networks : Proceedings of the Conference on Engineering Applications in Neural Networks(EANN), pp. 407-414, 1996.
  6. S. Rodrak, Y. Wongsawat, "On the classification of EEG/ HEG-based attention levels via time-frequency selective multilayer perceptron for BCI-based neurofeedback system", Asia-Pacific Signal & Information Processing Association Annual Summit and Conference (APAIPA ASC), California, USA, Dec. 2013.
  7. D. Kim, "Sensibility Classification Algorithm of EEGs using Multi-template Method", The transactions of the Korean Institute of Electrical Engineers., D. Vol. 53, No. 12, pp. 834-838, 2004.
  8. J. D. Markel and A. H. Gray, Jr., Linear Prediction of Speech, Springer-Verlag. Berlin Heidelberg.New York, 1980.
  9. S. J. Orfanidis, Optimun Signal Processing : An Introduction, 2nd ed., Macmillan Publishing Co., 1988.
  10. T. Musha, S. Kimura, K. I, Kaneko, K. Nishida, and K. Sekine, "Emotion spectrum analysis method(ESAM) for Monitoring the effects of art therapy applied on demented patients", CyberPsychology & Behavior., Vol. 3, No. 3, pp. 441-446, 2000. https://doi.org/10.1089/10949310050078904
  11. M. T. Hagan, H. B. Demuth, and M. Beale, Neural Network Design, PWS Publishing Co., 1996.
  12. M. R. Lakshmi, T. V. Prasad, V. C. Prakash, "Survey on EEG signal processing methods", International journal of advanced research in computer science and software engineering, 4, 84-91. 2014.
  13. S. Sanei, J.A. Chambers, EEG signal processing, John Wiley & Sons, Ltd. 2007.
  14. D. Kim, D. Kang, H. Kim, S. Lee, H, Ko, S. Park, "A Study on the Human Sensibility Evaluation Technique Using EEGs of 4 Emotions", The transactions of the Korean Institute of Electrical Engineers., D. Vol. 51, No. 11, pp. 528-534, 2002.
  15. D. Kim, "A Study on Comfortableness Evaluation Technique of Chairs using Electroencephalogram", The transactions of the Korean Institute of Electrical Engineers., D. Vol. 52, No. 12, pp. 702-707, 2003.
  16. D. Kim, H. Kim, "Comfortableness Evaluation Method using EEGs of the Frontopolar and the Parietal Lobes", The transactions of the Korean Institute of Electrical Engineers., D. Vol. 53, No. 5, pp. 374-379, 2004.