A novel emotion elicitation index using frontal brain asymmetry for enhanced EEG-based emotion recognition

IEEE Transactions on Information Technology in Biomedicine

Volumn 15, Issue 5, 2011, Pages 737-746

  Petrantonakis, Panagiotis C ^a   Hadjileontiadis, Leontios J ^a  

^a ARISTOTLE UNIVERSITY OF THESSALONIKI   (Greece)

Author keywords

electroencephalogram; Emotion elicitation; emotion recognition; frontal brain asymmetry; multidimensional directed information

Indexed keywords

DIRECTED INFORMATION; ELECTROENCEPHALOGRAM; EMOTION ELICITATION; EMOTION RECOGNITION; FRONTAL BRAIN ASYMMETRY;

VECTOR SPACES;

ELECTROENCEPHALOGRAPHY;

ARTICLE; BRAIN; ELECTROENCEPHALOGRAPHY; EMOTION; HUMAN; PHYSIOLOGY; THEORETICAL MODEL;

BRAIN; ELECTROENCEPHALOGRAPHY; EMOTIONS; HUMANS; MODELS, THEORETICAL;

EID: 80052593867     PISSN: 10897771     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITB.2011.2157933     Document Type: Article

References (35)

1. P. Rani, N. Sarkar, C. A. Smith, and J. A. Adams, "Affective communication for implicit human-machine interaction," IEEE Int. Conf. Syst.,Man, Cybern., pp. 4896-4903, 2003.
2. I. Cohen, A. Garg, and T. S. Huang, "Emotion recognition from facial expressions using multilevel HMM," presented at the Neural Inf. Process. Syst. Workshop Affective Computing, Colorado, 2000, available at: [Online] http://www.ifp.uiuc.edu/~ashutosh/papers/NIPS-emotion.pdf
3. F. Bourel, C. C. Chibelushi, and A. A. Low, "Robust facial expression recognition using a state-based model of spatially-localized facial dynamics," in Proc. Fifth IEEE Int. Conf. Automatic Face Gesture Recog., 2002, pp. 106-111.
4. B. Schuller, S. Reiter, R. Mueller, M. Al-Hames, and G. Rigoll, "Speaker independent speech emotion recognition by ensemble classification," in Proc. 6th Int. Conf. Multimedia Expo., 2005, pp. 864-867.
5. F. Yu, E. Chang, Y. Q. Xu, and H. Y. Shum, "Emotion detection from speech to enrich multimedia content," in Proc. IEEE Pacific Rim Conf. Multimedia, 2001, pp. 550-557.
6. R. W. Picard, E. Vyzas, and J. Healey, "Toward machine emotional intelligence: Analysis of affective physiological state," IEEE Trans. Pattern Anal. Mach. Intell., vol. 23, no. 10, pp. 1175-1191, Oct. 2001.
7. F. Nasoz, C. L. Lisetti, K. Alvarez, and N. Finkelstein, "Emotion recognition from physiological signals for user modeling of affect," in Proc. 9th Int. Conf. User Model, June 22-26, 2003, Pittsburg, USA, [Online]. available at: http://www.eurecom.fr/util/ publidownload.en.htm?id = 1806.
8. C. Busso, Z. Deng, S. Yildirim, M. Buut, C. M. Lee, A. Kazemzadeh, S. Lee, U. Neumann, and S. Narayanan, "Analysis of emotion recognition using facial expressions, speech and multimodal information," in Proc. 6th Int. Conf. Multimodal Interfaces, 2004, pp. 205-211.
9. K. Takahashi, "Remarks on emotion recognition from bio-potential signals," in Proc. of 2nd Int. Conf. Autonomous Robots and Agents, 2004, pp. 186-191.
10. A. Heraz and C. Frasson, "Predicting the three major dimensions of the learner's emotions from brainwaves," Int. J. Comput. Sci., vol. 2, no. 3, pp. 187-193, 2008.
11. D. O. Bos, EEG-based emotion recognition: The influence of visual and auditory stimuli, 2006 [Online]. Available: http://hmi. ewi.utwente.nl/ verslagen/capita-selecta/CS-Oude-Bos-Danny.pdf
12. R. J. Davidson, G. E. Schwartz, C. Saron, J. Bennett, and D. J. Goleman, "Frontal versus parietal EEG asymmetry during positive and negative affect," Psychophysiology, vol. 16, pp. 202-203, 1979.
13. O. Sakata,T. Shiina, andY. Saito, "MultidimensionalDirected Information and Its Application," Elec. Com. Jpn., vol. 4, pp. 3-85, 2002.
14. P. J. Lang, M. M. Bradley, and B. N. Cuthbert, "International affective picture system (IAPS): Affective ratings of pictures and instruction manual", Univ. Florida, Gainesville, FL, Tech. Rep. A-8, 2008.
15. R. J. Davidson, P. Ekman, C. D. Saron, J. A. Senulis, and W. V. Friesen, "Approach-withdrawal and cerebral asymmetry: Emotional expression and brain physiology," J. Personality Soc. Psychol., vol. 58, pp. 330-341, 1990.
16. H. Jasper, "The ten-twenty electrode system of the international federation," Electroencephalogr. Clin. Neurophysiol., vol. 39, pp. 371-375, 1958.
17. W. J. H. Nauta, "The problem of the frontal lobe: A reinterpretation," J. Psychiatric Res., vol. 8, pp. 167-187, 1971.
18. R. J. Davidson, "What does the prefrontal cortex 'do' in affect: Perspectives on frontal EEG asymmetry research," Biol. Psychol., vol. 67, pp. 219-233, 2004.
19. T. Kamitake, H. Harashima, andH.Miyakawa, "Time series analysis based on directed information," Trans Inst. Elect. Inf. Commun. Engineers, vol. 67-A, pp. 103-110, 1984.
20. G.Wang andM. Takigawa, "Directed coherence as a measure of interhemispheric correlation of EEG," Int. J. Psychophysiol., vol. 13, pp. 119-128, 1992.
21. M. Kaminski and K. J. Blinowska, "A new method of the description of the information flow in the brain structures," Biol. Cybern., vol. 65, pp. 203-210, 1991.
22. L. A. Baccala and K. Sameshima, "Partial directed coherence: a new concept in neural structure determination," Biol.Cybern., vol. 84, pp. 463-474, 2001.
23. W. Hesse, E. Moller, M. Arnord, and B. Schack, "The use of time-variant EEG Granger causality for inspecting directed interdependencies of neural assemblies," J. Neurosci. Methods, vol. 124, pp. 27-44, 2003.
24. J. D. Morris, "Observations:SAMthe self assessmentmannequin-An efficient cross-cultural measurement of emotional response," J. Advertising Res., vol. 35, pp. 63-68, 1995.
25. K. Coburn and M. Moreno, "Facts and artifacts in brain electrical activity mapping," Brain Topography, vol. 1, pp. 37-45, 1988.
26. D. O. Olguin, "Adaptive digital filtering algorithms for the elimination of power line interference in electroencephalographic signals", Master thesis, Instituto Tecnologico y de Estudios Superiores de Monterrey, Monterrey, Mexico, 2005.
27. M. Fatourechi, A. Bashashati, R. K. Ward, and G. E. Birch, "EMG and EOG artifacts in brain computer interface systems: A survey," Clin. Neurophysiol., vol. 118, pp. 480-494, 2007.
28. P. C. Petrantonakis and L. J. Hadjileontiadis, "Emotion recognition from EEG using higher order crossings," IEEE Trans. Inf. Technol. Biomed., vol. 14, no. 2, pp. 186-197, 2010.
29. T. Musha, Y. Terasaki, H. A. Haque, and G. A. Ivamitsky, "Feature extraction from EEGs associated with emotions," Artif. Life Robot., vol. 1, no. 1, pp. 15-19, 1997.
30. R. D. King, C. Feng, and A. Shutherland, "StatLog: Comparison of classification algorithms on large real-world problems," Appl. Artif. Intell., vol. 9, no. 3, pp. 259-287, 1995.
31. W. J. Krzanowski, Principles of Multivariate Analysis. Oxford, UK: Oxford University Press, 1988.
32. P. C. Mahalanobis, "On the generalized distance in statistics," Proc. Natl. Inst. Sci. India, vol. 2, pp. 49-55, 1936.
33. T. Mitchell, Machine Learning.. New York, NY: McGraw-Hill, 1997.
34. N. Cristianini and J. Shawe-Taylor, An Introduction to Support Vector Machines and OtherKernel-based Learning Methods.. Cambridge, UK: Cambridge University Press, 2000.
35. B. Kedem, Time Series Analysis by Higher Order Crossings. Piscataway, NJ: IEEE Press, 1994.