hypothesis that PPG is not precise enough for HRV
spectral analysis.
AKNOWLEGMENTS
Portions of the research in this paper uses the
MAHNOB database collected by Professor Pantic
and the iBUG group at imperial College London,
and in part collected in collaboration with Prof. Pun
and his team of University of Geneva, in the scope
of MAHNOB project financially supported by the
European Research Council under the European
Community’s 7
th
Framework Programme
(FP7/2007-2013)/ERC Starting Grant agreement
N°203143.
REFERENCES
André, E., Rehm, M., Minker, W., Bühler, D., 2004.
Endowing spoken language dialogue systems with
emotional intelligence, in: proceedings affective
dialogue systems 2004. Springer, pp. 178–187.
Chanel, G., Ansari-Asl, K., Pun, T., 2007. Valence-arousal
evaluation using physiological signals in an emotion
recall paradigm, in: Systems, Man and Cybernetics,
2007. ISIC. IEEE International Conference on. pp.
2662–2667.
Cover, T. M., Thomas, J. A., 2012. Elements of
information theory. John Wiley & Sons.
Ekman, P., 2005. Basic Emotions. Psychol. Rev. -
PSYCHOL REV 99, 45 – 60.
Ekman, P., Levenson, R. W., Friesen, W. V., 1983.
Autonomic nervous system activity distinguishes
among emotions. Science 221, 1208–1210.
Ertin, E., Stohs, N., Kumar, S., Raij, A., al’ Absi, M., Shah,
S., 2011. AutoSense: Unobtrusively Wearable Sensor
Suite for Inferring the Onset, Causality, and
Consequences of Stress in the Field, in: Proceedings of
the 9th ACM Conference on Embedded Networked
Sensor Systems, SenSys ’11. ACM, New York, NY,
USA, pp. 274–287.
Fleureau, J., Guillotel, P., Huynh-Thu, Q., 2012.
Physiological-Based Affect Event Detector for
Entertainment Video Applications. IEEE Trans. Affect.
Comput. 3, 379–385.
Gaggioli, A., Pallavicini, F., Morganti, L., Serino, S.,
Scaratti, C., Briguglio, M., Crifaci, G., Vetrano, N.,
Giulintano, A., Bernava, G., Tartarisco, G., Pioggia, G.,
Raspelli, S., Cipresso, P., Vigna, C., Grassi, A.,
Baruffi, M., Wiederhold, B., Riva, G., 2014.
Experiential Virtual Scenarios With Real-Time
Monitoring (Interreality) for the Management of
Psychological Stress: A Block Randomized Controlled
Trial. J. Med. Internet Res. 16, e167.
Gini, C., 1912. Variabilite e mutabilita (Italian). Mem.
Metodol. Stat.
Guyon, I., Elisseeff, A., 2003. An introduction to variable
and feature selection. J. Mach. Learn. Res. 3, 1157–
1182.
Hall, M. A., Smith, L. A., 1999. Feature Selection for
Machine Learning: Comparing a Correlation-Based
Filter Approach to the Wrapper., in: FLAIRS
Conference. pp. 235–239.
Healey, J. A., 2000. Wearable and automotive systems for
affect recognition from physiology (Thesis).
Massachusetts Institute of Technology.
Healey, J. A., Picard, R.W., 2005. Detecting stress during
real-world driving tasks using physiological sensors.
IEEE Trans. Intell. Transp. Syst. 6, 156–166.
Healey, J., Picard, R.W., 2002. Eight-emotion Sentics
Data, MIT Affective Computing Group.
Janecek, A., Gansterer, W.N., Demel, M., Ecker, G., 2008.
On the Relationship Between Feature Selection and
Classification Accuracy., in: FSDM. Citeseer, pp. 90–
105.
Koelstra, S., Muhl, C., Soleymani, M., Lee, J.-S., Yazdani,
A., Ebrahimi, T., Pun, T., Nijholt, A., Patras, I., 2012.
Deap: A database for emotion analysis; using
physiological signals. Affect. Comput. IEEE Trans. On
3, 18–31.
Kreibig, S. D., 2010. Autonomic nervous system activity in
emotion: A review. Biol. Psychol., The biopsychology
of emotion: Current theoretical and empirical
perspectives 84, 394–421.
Lang, P. J., Greenwald, M. K., Bradley, M. M., Hamm,
A.O., 1993. Looking at pictures: Affective, facial,
visceral, and behavioral reactions. Psychophysiology
30, 261–273.
Liu, H., Setiono, R., 1995. Chi2: Feature selection and
discretization of numeric attributes, in: 2012 IEEE 24th
International Conference on Tools with Artificial
Intelligence. IEEE Computer Society, pp. 388–388.
Mauss, I. B., Robinson, M. D., 2009. Measures of emotion:
A review. Cogn. Emot. 23, 209–237.
Picard, R.W., Vyzas, E., Healey, J., 2001. Toward machine
emotional intelligence: analysis of affective
physiological state. IEEE Trans. Pattern Anal. Mach.
Intell. 23, 1175–1191.
Posner, J., Russell, J. A., Peterson, B. S., 2005. The
circumplex model of affect: An integrative approach to
affective neuroscience, cognitive development, and
psychopathology. Dev. Psychopathol. 17, 715–734.
Roy, R. N., Charbonnier, S., Bonnet, S., 2014. Eye blink
characterization from frontal EEG electrodes using
source separation and pattern recognition algorithms.
Biomed. Signal Process. Control 14, 256–264.
Saeys, Y., Inza, I., Larrañaga, P., 2007. A review of
feature selection techniques in bioinformatics.
bioinformatics 23, 2507–2517.
Soleymani, M., Lichtenauer, J., Pun, T., Pantic, M., 2012.
A Multimodal Database for Affect Recognition and
Implicit Tagging. IEEE Trans. Affect. Comput. 3, 42–
55.
PhyCS2015-2ndInternationalConferenceonPhysiologicalComputingSystems
24