Affective computation on EEG correlates of emotion from musical and vocal stimuli

Proceedings of the International Joint Conference on Neural Networks

Volumn , Issue , 2009, Pages 1590-1594

  Khosrowabadi, Reza ^a   Wahab, Abdul ^a   Ang, Kai Keng ^b   Baniasad, Mohammad H ^c  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b INSTITUTE FOR INFOCOMM RESEARCH   (Singapore)

^c ISLAMIC AZAD UNIVERSITY   (Iran)

Author keywords

[No Author keywords available]

Indexed keywords

AFFECTIVE INTERFACES; BRAIN-COMPUTER INTERFACE; CLASSIFICATION ALGORITHM; DENSITY ESTIMATION; GAUSSIAN MIXTURE MODEL; HEALTHY SUBJECTS; HUMAN COMPUTER INTERFACES; KERNEL SMOOTHING; ONE-RULE; VALIDATION STUDY;

BAYESIAN NETWORKS; ELECTROENCEPHALOGRAPHY; INFERENCE ENGINES; LEARNING ALGORITHMS; NEURAL NETWORKS; OPTICAL SENSORS;

INTERFACES (COMPUTER);

EID: 70449384921     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2009.5178748     Document Type: Conference Paper

References (39)

1. J. Tao and T. Tan, "Affective Computing: A Review, " in Affective Computing and Intelligent Interaction. J. Tao, T. Tan, and R. W. Picard, Eds. Lecture Notes in Computer Science, vol. 3784, Berlin, Heidelberg: Springer 2005, pp. 981-995.
2. M. Pantic and L. J. M. Rothkrantz, "Automatic analysis of facial expressions: the state of the art, " IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, pp. 1424-1445, 2000.
3. L. C. De Silva, T. Miyasato, and R. Nakatsu, "Facial emotion recognition using multi-modal information, " in Proceedings of International Conference on Information, Communications and Signal Processing, 1997, pp. 397-401.
4. T. Baumgartner, M. Esslen, and L. Jäncke, "From emotion perception to emotion experience: Emotions evoked by pictures and classical music, " International Journal of Psychophysiology, vol. 60, pp. 34-43, 2006.
5. G. Erdmann and W. Janke, "Interaction between physiological and cognitive determinants of emotions: Experimental studies on Schachter's theory of emotions, " Biological Psychology, vol. 6, pp. 61- 74, 1978.
6. L. S. Chen, T. S. Huang, T. Miyasato, and R. Nakatsu, "Multimodal human emotion/expression recognition, " in Proceedings of Third IEEE International Conference on Automatic Face and Gesture Recognition., 1998, pp. 366-371.
7. G. H. Bower, "Mood and memory, " American Psychologist, vol. 36, pp. 129-148, 1981.
8. L. C. De Silva and N. Pei Chi, "Bimodal emotion recognition, " in Proceedings of the 4th IEEE International Conference on Automatic Face and Gesture Recognition, 2000, pp. 332-335.
9. J. Kim, "Bimodal Emotion Recognition using Speech and Physiological Changes, " in Robust Speech Recognition and Understanding. M. Grimm and K. Kroschel, Eds. Vienna, Austria: I- Tech Education and Publishing, 2007, pp. 265-280.
10. A. Haag, S. Goronzy, P. Schaich, and J. Williams, "Emotion Recognition Using Bio-sensors: First Steps towards an Automatic System, " in Affective Dialogue Systems. E. André, D. Laila, W. Minker, and P. Heisterkamp, Eds. Lecture Notes in Computer Science, vol. 3068, 2004, pp. 36-48.
11. J. Kim, E. André, M. Rehm, T. Vogt, and J. Wagner, "Integrating information from speech and physiological signals to achieve emotional sensitivity, " in Proceedings of the 9th European Conference on Speech Communication and Technology, 2005, pp. 809-812.
12. O. Villon and C. Lisetti, "A User-Modeling Approach to Build User's Psycho-Physiological Maps of Emotions using Bio-Sensors, " in Proceedings of the 15th IEEE International Symposium on Robot and Human Interactive Communication, 2006, pp. 269-276.
13. R. W. Picard, Affective Computing. Cambridge, Mass.: MIT Press, 2000.
14. J. Panksepp, Affective Neuroscience: The Foundations of Human and Animal Emotions. New York: Oxford University Press, 1998.
15. P. Ekman, "Basic Emotions, " in Handbook of cognition and emotion. T. Dagleish and M. Power, Eds. Sussex, U. K.: John Wiley & Sons Ltd., 1999, pp. 45-60.
16. A. Ortony and T. J. Turner, "What's basic about basic emotions?, " Psychological Review, vol. 97, pp. 315-331, 1990.
17. A. J. Gerber, J. Posner, D. Gorman, T. Colibazzi, S. Yu, Z. Wang, A. Kangarlu, H. Zhu, J. Russell, and B. S. Peterson, "An affective circumplex model of neural systems subserving valence, arousal, and cognitive overlay during the appraisal of emotional faces, " Neuropsychologia, vol. 46, pp. 2129-2139, 2008.
18. I. Peretz and S. Hébert, "Toward a Biological Account of Music Experience, " Brain and Cognition, vol. 42, pp. 131-134, 2000.
19. P. J. Lang, M. M. Bradley, and B. N. Cuthbert, "International affective picture system (IAPS) : Affective ratings of pictures and instruction manual, " University of Florida, Gainesville, FL, Technical Report A- 6, 2005.
20. J. J. Gross and R. W. Levenson, "Emotion elicitation using films, " Cognition & Emotion, vol. 9, pp. 87-108, 1995.
21. A. J. Blood, R. J. Zatorre, P. Bermudez, and A. C. Evans, "Emotional responses to pleasant and unpleasant music correlate with activity in paralimbic brain regions, " Nature Neuroscience, vol. 2, pp. 382-387, 1999.
22. J. Bhattacharya, H. Petsche, and E. Pereda, "Interdependencies in the spontaneous EEG while listening to music, " International Journal of Psychophysiology, vol. 42, pp. 287-301, 2001.
23. S. Khalfa, M. Guye, I. Peretz, F. Chapon, N. Girard, P. Chauvel, and C. Liégeois-Chauvel, "Evidence of lateralized anteromedial temporal structures involvement in musical emotion processing, " Neuropsychologia, vol. 46, pp. 2485-2493, 2008.
24. C. M. Krause, V. Viemerö, A. Rosenqvist, L. Sillanmäki, and T. Åström, "Relative electroencephalographic desynchronization and synchronization in humans to emotional film content: an analysis of the 4-6, 6-8, 8-10 and 10-12 Hz frequency bands, " Neuroscience Letters, vol. 286, pp. 9-12, 2000.
25. L. I. Aftanas and S. A. Golocheikine, "Human anterior and frontal midline theta and lower alpha reflect emotionally positive state and internalized attention: high-resolution EEG investigation of meditation, " Neuroscience Letters, vol. 310, pp. 57-60, 2001.
26. K. Takahashi, "Remarks on Emotion Recognition from Bio-Potential Signals, " in Proceedings of the 2nd International Conference on Autonomous Robots and Agents, Palmerston North, New Zealand, 2004, pp. 186-191.
27. W. C. Lin, H. W. Chiu, and C. Y. Hsu, "Discovering EEG Signals Response to Musical Signal Stimuli by Time-frequency analysis and Independent Component Analysis, " in Proceedings of the 27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005, pp. 2765-2768.
28. Y. P. Lin, C. H. Wang, T. L. Wu, S. K. Jeng, and J. H. Chen, "Multilayer perceptron for EEG signal classification during listening to emotional music, " in Proceedings of the IEEE TENCON 2007, Taipei, Taiwan, 2007, pp. 1-3.
29. M. Murugappan, M. Rizon, R. Nagarajan, S. Yaacob, D. Hazry, and I. Zunaidi, "Time-Frequency Analysis of EEG Signals for Human Emotion Detection, " in 4th Kuala Lumpur International Conference on Biomedical Engineering 2008. N. A. Abu Osman, F. Ibrahim, W. A. B. Wan Abas, H. S. Abdul Rahman, and H. N. Ting, Eds. IFMBE Proceedings, 2008, vol. 21, pp. 262-265.
30. M. Schafföner, "Estimation of Nonparametric Probability Density Functions with Applications to Automatic Speech Recognition, " Ph. D. Thesis, Institut für Elektronik, Signalverarbeitung und Kommunikationstechnik, Otto-von-Guericke University of Magdeburg, Germany, 2007.
31. E. Parzen, "On Estimation of a Probability Density Function and Mode, " The Annals of Mathematical Statistics, vol. 33, pp. 1065-1076, 1962.
32. R. O. Duda, P. E. Hart, and D. G. Stork, "Pattern Classification, " 2nd ed New York: John Wiley, 2001.
33. S. J. Sheather, "Density estimation, " Statistical Science, vol. 19, pp. 588-597, 2004.
34. S. Theodoridis and K. Koutroumbas, Pattern Recognition, 2nd ed. Amsterdam: Elsevier/Academic Press, 2003.
35. N. Friedman, D. Geiger, and M. Goldszmidt, "Bayesian Network Classifiers, " Machine Learning, vol. 29, pp. 131-163, 1997.
36. S. S. Haykin, "Neural Networks: A Comprehensive Foundation, " 2nd ed Upper Saddle River, NJ: Prentice Hall, 1999.
37. R. C. Holte, "Very Simple Classification Rules Perform Well on Most Commonly Used Datasets, " Machine Learning, vol. 11, pp. 63-90, 1993.
38. L. Breiman, "Random Forests, " Machine Learning, vol. 45, pp. 5-32, 2001.
39. I. H. Witten and E. Frank, Data Mining: Practical machine learning tools and techniques, 2nd ed. San Francisco: Morgan Kaufmann, 2005.