Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
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An Analysis on the Changes in ERP According to Type of Stimuli about Fear of Crime

범죄의 두려움에 대한 자극의 유형에 따른 ERP 변화 분석

  • Kim, Yong-Woo (Dept. of Media Engineering, Catholic University of Korea) ;
  • Kang, Hang-Bong (Dept. of Media Engineering, Catholic University of Korea)
  • Received : 2017.07.25
  • Accepted : 2017.10.25
  • Published : 2017.12.31
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Abstract

The ultimate goal of multimedia in bio-signal research is to approach multimedia contents through bio-signal. Hence it is important to interpret user's emotions by analyzing his or her bio-signals. In this paper, we construct ERP task of oddball component to analyze EEG signal between normal stimuli and fear stimuli and measure EEG during ERP task. The results from extracted ERP component show that there is a difference in N200 in visual stimuli, P300 in auditory stimuli, and N100 and P300. Moreover, there are larger changes in audiovisual stimuli, indicating that users recognize greater fear of crime when visual and auditory stimuli are simultaneously presented.

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References

  1. J. Kim and E. Andre, "Emotion Recognition Using Physiological and Speech Signal in Short-Term Observation," Proceeding of Perception Interactive Technologies, Vol. 4021, pp. 53-64, 2006.
  2. J. Kim and E. Andre, “Emotion Recognition based on Physiological Changes in Music Listening,” IEEE Transactions on Pattern Analysis Machine Intelligence, Vol. 30, No. 12, pp. 2067-2083, 2008. https://doi.org/10.1109/TPAMI.2008.26
  3. K.H. Kim, S.W. Bang, and S.R. Kim, “Emotion Recognition System Using Short-Term Monitoring of Physiological Signals,” Medical Biological Engineering Computing, Vol. 42, No. 3, pp. 419-427, 2004. https://doi.org/10.1007/BF02344719
  4. R.W. Picard, E. Vyzas, and J. Healey, “Toward Machine Emotional Intelligence: Analysis of Affective Physiological State,” IEEE Transactions on Pattern Analysis Machine Intelligence, Vol. 23, No. 10, pp. 1175-1191, 2001. https://doi.org/10.1109/34.954607
  5. J.J.B. Allen, J.A. Coan, and M. Nazarian, “Issues and Assumptions on the Road from Raw Signals to Metrics of Frontal EEG Asymmetry in Emotion,” Biological Psychological, Vol. 67, No. 1-2, pp. 183-218, 2004. https://doi.org/10.1016/j.biopsycho.2004.03.007
  6. L.A. Schmidt and L.J. Trainor, “Frontal Brain Electrical Activity (EEG) Distinguishes Valence and Intensity of Musical Emotions,” Cognition Emotion, Vol. 15, No. 4, pp. 487-500, 2001. https://doi.org/10.1080/02699930126048
  7. W. Heller, “Neuropsychological Mechanisms of Individual Differences in Emotion, Personality and Arousal,” Neuropsychology, Vol. 7, No. 4, pp. 476-489, 1993. https://doi.org/10.1037/0894-4105.7.4.476
  8. D.J.L. Schutter, P. Putman, E. Hermans, and J. Van Honk, “Parietal Electroencephalogram Beta Asymmetry and Selective Attention to Angry Facial Expressions in Healthy Human Subjects,” Neuroscience Letters, Vol. 314, No. 1-2, pp. 13-16, 2001. https://doi.org/10.1016/S0304-3940(01)02246-7
  9. M. Balconi and C. Lucchiari, "Consciousness and Arousal Effects on Emotional Face Processing as Revealed by Brain Oscillations. A Gamma Band Analysis," International Journal of Psychophysiology, Vol. 67, No. 1, pp. 41-46, 2008. https://doi.org/10.1016/j.ijpsycho.2007.10.002
  10. E. Basar, C. Basar Eroglu, S. Karakas, and M. Schurmann, “Oscillatory Brain Theory: A New Ttrend in Neuroscience-The Role of Oscillatory Processes in Sensory and Cognitive Functions,” IEEE Engineering in Medicine and Biology Magazine, Vol. 18, No. 3, pp. 56-66, 1999. https://doi.org/10.1109/51.765190
  11. N.N. Van Dongen, J.W. Van Strien, and K. Dijkstra, “Implicit Emotion Regulation in the Context of Viewing Artworks: ERP Evidence in Response to Pleasant and Unpleasant Pictures,” Journal of Brain and Cognition, Vol. 107, No. 7, pp. 48-54, 2016. https://doi.org/10.1016/j.bandc.2016.06.003
  12. P.J. Lang, M.M. Bradley, and B.N. Cuthbert, International Affective Picture System: Instruction Manual and Affective Ratings, The Center for Research in Psychophysiology, 1999.
  13. B.D. Nelson, A. Weinberg, J. Pawluk, M. Gawlowska, and G.H. Proudfit, “An Event-Related Potential Investigation of Fear Generalization and Intolerance of Uncertainty,” Journal of Behavior Therapy, Vol. 46, No. 5, pp. 661-670, 2015. https://doi.org/10.1016/j.beth.2014.09.010
  14. J. Kissler, C. Herbert, I. Winkler, and M. Junghofer, "Emotion and Attention in Visual Word Processing-An ERP Study," Journal of Biological Psychology, Vol. 80, No. 1, pp. 75-83, 2009. https://doi.org/10.1016/j.biopsycho.2008.03.004
  15. M.B. Kostyunina and M.A. Kulikov, “Frequency Characteristics of EEG Spectra in the Emotions,” J ournal of Neuroscience and Behavioral Physiology, Vol. 26, No. 4, pp. 340-343, 1996. https://doi.org/10.1007/BF02359037
  16. X.W. Wang, D. Nie, and B.L. Lu, "EEG-based Emotion Recognition Using Frequency Domain Features and Support Vector Machines," Proceeding of International Conference on Neural Information Processing, pp. 734-743, 2011.
  17. Y.P. Lin, C.H. Wang, T.P. Jung, T.L. Wu, S.K. Jeng, J.R. Duann, et al., "EEG-based Emotion Recognition in Music Listening," Biomedical Engineering, Vol. 57, No. 7, pp. 1798-1806, 2010.
  18. M.S. Park, H.S. Oh, H. Jeong, and J.H. Sohn, "Eeg-based Emotion Recogntion During Emotionally Evocative Films," Proceeding of Brain-Computer Interface Conference, pp. 56-57, 2013.
  19. T. Lorenc, M. Petticrew, M. Whitehead, D. Neary, S. Clayton, K. Wright, et al., “Fear of Crime and the Environment: Systematic Review of UK Qualitative Evidence,” BMC Public Health, Vol. 13, No. 1, pp. 496, 2013. https://doi.org/10.1186/1471-2458-13-496
  20. T. Lorenc, S. Clayton, D. Neary, M. Whitehead, M. Petticrew, H. Thomson, et al., “Crime, Fear of Crime, Environment, and Mental Health and Wellbeing: Mapping Review of Theories and Causal Pathways,” Health and Place, Vol. 18, No. 4, pp. 757-765, 2012. https://doi.org/10.1016/j.healthplace.2012.04.001
  21. W. Hollway and T. Jefferson, "Anxiety, Biography and the Experience of Locality," The Turn to Biographical Methods in Social Science, Routledge, Abingdon, pp. 167-180, 2000.
  22. W. Hollway and T. Jefferson, "The Role of Anxiety in the Fear of Crime," Crime, Risk and Insecurity, Routledge, Abingdon, pp. 31-49, 2000.
  23. P.E. Hopkins and S.J. Smith, "Scaling Segregation; Racialising Fear," Fear: Critical Geopolitics and Everyday Life, Routledge, Abingdon, pp. 103-116, 2008.
  24. J. Little, R. Panelli, and A. Kraack, "Women's Fear of Crime: A Rural Perspective," Journal of Rural Studies, Vol. 21, No. 2, pp. 151-163, 2005. https://doi.org/10.1016/j.jrurstud.2005.02.001
  25. J.A. Uriguen and G.Z. Begona, "EEG Artifact Removal-State-of-the-Art and Guidelines," Journal of Neural Engineering, Vol. 12, No. 3, pp. 1-31, 2015.
  26. S. Caldenhove, L.G.J.M. Borghans, A. Blokland, and A. Sambeth, "Role of Acetylcholine and Serotonin in Novelty Processing Using an Oddball Paradigm," Behavioural Brain Research, Vol. 331, pp. 199-204, 2017. https://doi.org/10.1016/j.bbr.2017.05.031
  27. Y.W. Kim and H.B. Kang, “An Analysis of the Change in ERP Caused from Watching Fear of Crime Video Contents,” Journal of Korea Multimedia Society, Vol. 20, No. 6, pp. 950-959, 2017. https://doi.org/10.9717/KMMS.2017.20.6.950

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