Science of Emotion and Sensibility (감성과학)

Korean Society for Emotion and Sensibility (한국감성과학회)
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Emotion Recognition Method of Competition-Cooperation Using Electrocardiogram

심전도를 이용한 경쟁-협력의 감성 인식 방법

  • Park, Sangin (Industry-Academy Cooperation Foundation, Sangmyung University) ;
  • Lee, Don Won (Department of Emotion Engineering, Sangmyung University) ;
  • Mun, Sungchul (CJ Hello Future Engine Lab., CJ Hello) ;
  • Whang, Mincheol (Department of Intelligent Engineering Informations for Human, Sangmyung University)
  • 박상인 (상명대학교 산학협력단) ;
  • 이동원 (상명대학교 감성공학과) ;
  • 문성철 (CJ 헬로 Future Engine Lab.) ;
  • 황민철 (상명대학교 미래융합공학대학 휴먼지능정보공학과)
  • Received : 2017.11.15
  • Accepted : 2018.09.19
  • Published : 2018.09.30
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Abstract

Attempts have been made to recognize social emotion, including competition-cooperation, while designing interaction in work places. This study aimed to determine the cardiac response associated with classifying competition-cooperation of social emotion. Sixty students from Sangmyung University participated in the study and were asked to play a pattern game to experience the social emotion associated with competition and cooperation. Electrocardiograms were measured during the task and were analyzed to obtain time domain indicators, such as RRI, SDNN, and pNN50, and frequency domain indicators, such as VLF, LF, HF, VLF/HF, LF/HF, lnVLF, lnLF, lnHF, and lnVLF/lnHF. The significance of classifying social emotions was assessed using an independent t-test. The rule-base for the classification was determined using significant parameters of 30 participants and verified from data obtained from another 30 participants. As a result, 91.67% participants were correctly classified. This study proposes a new method of classifying social emotions of competition and cooperation and provides objective data for designing social interaction.

경쟁과 협력을 인식하는 것은 일하는 공간에서 상호작용 디자인을 하는 데에 필요한 요소이다. 본 연구는 타인과의 상호작용에서 유발되는 경쟁과 협력의 사회 감성을 심장의 생리 반응 패턴으로 객관적이고 정량적으로 인식하는 방법을 개발하는 것이 목적이다. 피험자 60명은 패턴 게임으로 구성된 과제로 경쟁-협력 실험에 참여하였고 심전도를 측정하였다. 심전도로부터 시간 영역 지표인 RRI와 SDNN, pNN50, rMSSD를 추출하였고, 주파수 영역 지표인 VLF와 LF, HF, VLF/HF, LF/HF, lnVLF, lnLF, lnHF, lnVLF/lnHF를 추출하였다. 독립 표본 t검정으로 사회 감성에 따라 추출한 지표들의 통계적 유의성을 확인하였다. 통계적으로 유의한 지표들로 단계적 판별 분석을 진행하여 선정된 SDNN, VLF, lnVLF/lnHF 지표로 경쟁-협력 규칙을 정의하고 검증하였다. 검증 결과 85%의 인식 정확도를 보였다. 본 연구에서 제안한 감성 인식 방법은 다양한 분야에 접목되어 사용자 맞춤형 서비스 제공에 활용될 수 있을 것이라 생각된다.

Keywords

References

  1. Boucsein, W., & Backs, R. W. (2009). The psychophysiology of emotion, arousal, and personality: Methods and models. Handbook of digital human modeling: Research for applied ergonomics and human factors engineering, 35.
  2. Buck, R. (1980). Nonverbal behavior and the theory of emotion: the facial feedback hypothesis. Journal of Personality and Social Psychology, 38(5), 811. DOI: 10.1037/0022-3514.38.5.811
  3. Burnett, S., & Blakemore, S. J. (2009). Functional connectivity during a social emotion task in adolescents and in adults. European Journal of Neuroscience, 29(6), 1294-1301. DOI: 10.1111/j.1460-9568.2009.06674.x
  4. Cho, J. E., Lee, D. W., Park, M., & Whang, M. (2017). Analysis of Gaze Related to Cooperation, Competition and Focus Levels (협력, 경쟁, 집중 수준에 따른 시선 분석). The Journal of the Korea Contents Association, 17(9), 281-291. DOI: 10.5392/JKCA.2017.17.09.281
  5. Darwin, C., & Prodger, P. (1998). The expression of the emotions in man and animals. Oxford University Press, USA.
  6. Gross, J. J., Fredrickson, B. L., & Levenson, R. W. (1994). The psychophysiology of crying. Psychophysiology, 31(5), 460-468. DOI: 10.1111/j.1469-8986.1994.tb01049.x
  7. Gunes, H., & Piccardi, M. (2007). Bi-modal emotion recognition from expressive face and body gestures. Journal of Network and Computer Applications, 30(4), 1334-1345. DOI: 10.1016/j.jnca.2006.09.007
  8. Hamer, M., Tanaka, G., Okamura, H., Tsuda, A., & Steptoe, A. (2007). The effects of depressive symptoms on cardiovascular and catecholamine responses to the induction of depressive mood. Biological Psychology, 74(1), 20-25. DOI: 10.1016/j.biopsycho.2006.06.003
  9. Jordan, P. J., Ashkanasy, N. M., Hartel, C. E., & Hooper, G. S. (2002). Workgroup emotional intelligence: Scale development and relationship to team process effectiveness and goal focus. Human Resource Management Review, 12(2), 195-214. DOI: 10.1016/S1053-4822(02)00046-3
  10. Kamath, M. V., & Fallen, E. L. (1993). Power spectral analysis of heart rate variability: a noninvasive signature of cardiac autonomic function. Critical Reviews in Biomedical Engineering, 21(3), 245-311.
  11. Lee, D. W., Park, S., Won, M. J., Hwang, S. T., & Whang, M. (2016). Recognition of 2D emotion using Acceleration and Amplitude of Electrocardiogram (ECG) (심전도의 가속도와 진폭을 이용한 이차원 감성 인식 기술). Extended Abstracts of Hci Korea, 2016, 59-61.
  12. Malliani, A., Pagani, M., Lombardi, F., & Cerutti, S. (1991). Cardiovascular neural regulation explored in the frequency domain. Circulation, 84(2), 482-492. DOI: 10.1161/01.CIR.84.2.482
  13. McCraty, R., & Watkins, A. (1996). Autonomic assessment report: A comprehensive heart rate variability analysis. Heart math research center reports. Boulder Creek, CA: Institute of Heart Math.
  14. Niu, X., Chen, L., & Chen, Q. (2011, October). Research on genetic algorithm based on emotion recognition using physiological signals. In Computational Problem-Solving (ICCP), 2011 International Conference on (pp. 614-618). IEEE. DOI: 10.1109/ICCPS.2011.6092256
  15. Nyklicek, I., Thayer, J. F., & Van Doornen, L. J. (1997). Cardiorespiratory differentiation of musically-induced emotions. Journal of Psychophysiology.
  16. Pan, J., & Tompkins, W. J. (1985). A real-time QRS detection algorithm. IEEE Transactions on Biomedical Engineering, 3, 230-236.
  17. Prkachin, K. M., Williams-Avery, R. M., Zwaal, C., & Mills, D. E. (1999). Cardiovascular changes during induced emotion: An application of Lang's theory of emotional imagery. Journal of Psychosomatic Research, 47(3), 255-267. DOI: 10.1016/S0022-3999(99)00036-7
  18. Parkinson, B., Fischer, A. H., & Manstead, A. S. (2005). Emotion in social relations: Cultural, group, and interpersonal processes. Psychology Press.
  19. Rainville, P., Bechara, A., Naqvi, N., & Damasio, A. R. (2006). Basic emotions are associated with distinct patterns of cardiorespiratory activity. International Journal of Psychophysiology, 61(1), 5-18. DOI: 10.1016/j.ijpsycho.2005.10.024
  20. Rottenberg, J., Wilhelm, F. H., Gross, J. J., & Gotlib, I. H. (2003). Vagal rebound during resolution of tearful crying among depressed and nondepressed individuals. Psychophysiology, 40(1), 1-6. DOI: 10.1111/1469-8986.00001
  21. Shin, H. S., Hahm, C. Y., Um, N. K., Kim, M. K., Lee, S. H., & Kim, Y. S. (2014). Trends of Emotional Information & Communication Technology (감성 ICT 기술 및 산업동향). Electronics and Telecommunications Trends, 29(5), 30-39.
  22. Stemmler, G., Aue, T., & Wacker, J. (2007). Anger and fear: Separable effects of emotion and motivational direction on somatovisceral responses. International Journal of Psychophysiology, 66(2), 141-153. DOI: 10.1016/j.ijpsycho.2007.03.019
  23. Whang, M., Chang, G., & Kim, S. (2004). Research on Emotion Evaluation using Autonomic Response (자율신경계 반응에 의한 감성 평가 연구). The Korean Society For Emotion & Sensibility, 7(3), 51-56.
  24. Zeng, Z., Pantic, M., Roisman, G., & Huang, T. S. (2009). A survey of affect recognition methods: Audio, visual, and spontaneous expressions. Pattern Analysis and Machine Intelligence, IEEE Transactions, 31(1), 39-58. DOI: 10.1109/TPAMI.2008.52