1 |
Wu, G., Liu, G., & Hao, M. (2010). The analysis of emotion recognition from GSR based on PSO. In Intelligence Information Processing and Trusted Computing (IPTC), 2010 International Symposium on (pp. 360-363). IEEE. DOI: 10.1109/iptc.2010.60
DOI
|
2 |
Zhang, W., Meng, X., Li, Z., Lu, Q., & Tan, S. (2015). Emotion Recognition in Speech Using Multiclassification SVM. In Ubiquitous Intelligence and Computing and 2015 IEEE 12th Intl Conf on Autonomic and Trusted Computing and 2015 IEEE 15th Intl Conf on Scalable Computing and Communications and Its Associated Workshops (UICATC- ScalCom), 2015 IEEE 12th Intl Conf on (pp. 1181-1186). IEEE. DOI: 10.1109/uic-atc-scalcomcbdcom- iop.2015.215
|
3 |
Aldemir, R., & Tokmakci, M. (2015). Investigation of respiratory and heart rate variability in hypertensive patients. Turkish Journal of Electrical Engineering & Computer Sciences, 23(1), 67-79. DOI: 10.3906/elk-1211-110
DOI
|
4 |
Bänziger, T., Grandjean, D., & Scherer, K. R. (2009). Emotion recognition from expressions in face, voice, and body: the Multimodal Emotion Recognition Test (MERT). Emotion, 9(5), 691-704. DOI: 10.1037/a0017088
DOI
|
5 |
Bettadapura, V. (2012). Face expression recognition and analysis: the state of the art. arXiv preprint arXiv:1203.6722.
|
6 |
Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: the self-assessment manikin and the semantic differential. Journal of Behavior Therapy and Experimental Psychiatry, 25(1), 49-59. DOI:10.1016/0005-7916(94)90063-9
DOI
|
7 |
Brosch, T., Scherer, K. R., Grandjean, D. M., & Sander, D. (2013). The impact of emotion on perception, attention, memory, and decision-making. Swiss Medical Weekly, 143, w13786. DOI: 10.4414/smw.2013.13786
|
8 |
Daubechies, I. (1990). The wavelet transform, timefrequency localization and signal analysis. IEEE Transactions on Information Theory, 36(5), 961-1005. DOI: 10.1109/18.57199
DOI
|
9 |
Ekman, P. (1992). An argument for basic emotions. Cognition & Emotion, 6(3-4), 169-200. DOI:10.1080/02699939208411068
DOI
|
10 |
Ford, J. H., Addis, D. R., & Giovanello, K. S. (2012). Differential effects of arousal in positive and negative autobiographical memories. Memory, 20(7), 771-778. DOI: 10.1080/09658211.2012.704049
DOI
|
11 |
Geer, J. H. (1966). Fear and autonomic arousal. Journal of Abnormal Psychology, 71(4), 253-255. DOI:10.1037/h0023544
DOI
|
12 |
Goshvarpour, A., Abbasi, A., & Goshvarpour, A. (2014). Impact of Music on College Students: Analysis of Galvanic Skin Responses. Applied Medical Informatics, 35(4), 11-20.
|
13 |
Heino, A., Van der Molen, H.H., & Wilde, G.J.S. (1990). Risk-homeostatic processes in car following behaviour: electrodermal responses and verbal risk estimates as indicators of the perceived level of risk during a car-driving task. Groningen, NL: Traffic Research Center.
|
14 |
Lang, P. J. (1980). Behavioral treatment and biobehavioral assessment: Computer applications.
|
15 |
Lewis, M. (1995). Self-conscious emotions. American scientist, 83(1), 68-78.
|
16 |
Najarian, K., & Splinter, R. (2005). Biomedical signal and image processing. CRC press.
|
17 |
Christie, I. C. (2002). Multivariate discrimination of emotion-specific autonomic nervous system activity. Unpublished master's thesis, Virginia Polytechnic Institute and State University, Blacksburg, VA.
|
18 |
Norton, J. J., Lee, D. S., Lee, J. W., Lee, W., Kwon, O., Won, P., ... & Umunna, S. (2015). Soft, curved electrode systems capable of integration on the auricle as a persistent brain-computer interface. Proceedings of the National Academy of Sciences, 112(13), 3920-3925. DOI: 10.1073/pnas.1424875112
DOI
|
19 |
Misiti, M., Misiti, Y., Oppenheim, G., & Poggi, J. M. (1996). Wavelet toolbox. The MathWorks Inc., Natick, MA, 15, 21.
|
20 |
Murry, J. P., & Dacin, P. A. (1996). Cognitive moderators of negative-emotion effects: Implications for understanding media context. Journal of Consumer Research, 22(4), 439-447. DOI: 10.1086/209460
DOI
|
21 |
Picard, R. W., Vyzas, E., & Healey, J. (2001). Toward machine emotional intelligence: Analysis of affective physiological state. IEEE transactions on pattern analysis and machine intelligence, 23(10), 1175-1191. DOI: 10.1109/34.954607
DOI
|
22 |
Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39, 1161-1178. DOI: 10.1037/h0077714
DOI
|
23 |
Singh, N. (2013). Arousal Level Determination in Video Game Playing Using Galvanic Skin Response (Doctoral dissertation, Thapar University, Patiala).
|
24 |
Soleymani, M., Pantic, M., & Pun, T. (2012). Multimodal emotion recognition in response to videos. IEEE transactions on affective computing, 3(2), 211-223. DOI: 10.1109/t-affc.2011.37
DOI
|
25 |
Swangnetr, M., & Kaber, D. B. (2013). Emotional state classification in patient–robot interaction using wavelet analysis and statistics-based feature selection. IEEE Transactions on Human-Machine Systems, 43(1), 63-75. DOI: 10.1109/tsmca.2012.2210408
DOI
|
26 |
Tarvainen, M. P., Karjalainen, P. A., Koistinen, A. S., & Valkonen-Korhonen, M. V. (2000). Principal component analysis of galvanic skin responses. In Engineering in Medicine and Biology Society, 2000. Proceedings of the 22nd Annual International Conference of the IEEE (Vol. 4, pp. 3011-3014). IEEE. DOI: 10.1109/iembs.2000.901513
DOI
|