Abstract
The automatic detection and study of human emotions has always been an area of interest within the scientific community. The AUBADE European Union funded project has addressed this problem by developing an innovative, intelligent, multi-sensor and wearable system for the assessment of the emotional state of humans under special conditions (i.e. neurological diseases, stress, etc.). The system recognizes the emotions after processing biomedical signals (electromyogram, electrocardiogram, respiration rate and galvanic skin response) and can be applied in diverse areas. Currently, a health care sector scenario has been considered and validated, primarily in the neurology and psychology areas, in order to contribute to get precise diagnosis and treatment procedures for patients.
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AUBADE project, IST 507605. European Commission Six Framework Programme.
Automatic analysis of facial expressions: The state of the art, IEEE Trans. Pattern Anal. Machine Intell. 22: 1424–1445, Dec. 2000.
Bisquerra, R. (2000). Educación Emocional y Bienestar. Barcelona: Praxis.
Bradley, M. M. and Lang, P. Measuring Emotions: The Self Assessment Manikin and the semantic Differential.J Behav. Ther. Exp. Psy. 25(1): 49–59, 1994.
Bradley M. M., Codispoti M., Cuthbert B. N., Lang P. J. Emotion and Motivation I: Defensive and Appetitive Reactions in Picture Processing. Emotion 1(3): 276–298, 2001.
Darwin C. The Expression of the Emotions in Man and Animals. J. Murray, London, 1872.
Ekman P. and Friesen W. V. Constants across cultures in the face and emotion. Journal of Personality and Social Psychology 17: 124–129, 1971.
Ekman P. Facial Expression and Emotion. American Psychologist 48(4): 384–392, April 1993.
Ekman, P. and Friesen. W. V. Facial action coding system: A technique for the measurement of facial movement. Palo Alto, CA: Consulting Psychologists Press, 1978.
Ekman, P. and Rosenberg, E. L. What the face reveals: Basic and applied studies of spontaneous expression using the facial action coding system (FACS), New York: Oxford University Press, 1997. Second expanded edition 2004.
Goleman, D. Emotional Intelligence, New York: Bantam Books, 1995.
Kan Y. et al. Recognition of emotion from facial, prosodic and written verbal stimuli in Parkinson’s disease. Cortex 38(4): 623–30, 2002.
Katsis C. D., Ganiatsas G., and Fotiadis D. I. An integrated telemedicine platform for the assessment of affective physiological states. Diagnostic Pathology 1:16 doi:10.1186/1746–1596-1–16, August 2006.
Lang P. J. et al. The international affective pictures system (IAPS). Technical Manual and Affective Ratings. Gainsville, FL: University of Florida, 1999.
Lang P. J., Greenwald M. K., Bradley M. M. and Hamm A. O. Looking at pictures: affective, facial, visceral, and behavioral reactions. Psychophysiology 30(3):261–73, May 1993.
Pantic M. and Rothkrantz L. J. M. Facial Action Recognition for Facial Expression Analysis from Static Face Images. IEEE Transactions on Systems, Man, and Cybernetics–Part B, 34(3): 1449–1461, June 2004.
Rigas, G., Katsis, C., Ganiatsas, G. and Fotiadis, D. I.: IEEE Engineering in Medicine and Biology Society in conjunction with the biennial Conference of the French Society of Biological and Medical Engineering (SFGBM). August 23–26, 2007. Convention Center, Cité Internationale, Lyon, France.
Sprengelmeyer R. et al. Facial expression recognition in people with medicated and unmedicated Parkinson’s disease. Neuropsychologia 41(8): 1047–57, 2003.
Vera, C. et al. Results of a wearable EMG monitoring system for neurological patients Telemedicine and Health Journal, Volume 12, Number 2, April 2006, pp 207 (ISSN 1530–5627), San Diego, California (USA).
Vera, C. et al. Wearable System for Automatic Emotion Detection in Extreme Conditions. Applied Technologies in Medicine and Neuroscience (Proceedings of the first international conference on Applied Technologies in Medicine and Neuroscience), pp 97–102 (ISBN: 3–85184-027–5), June 2005.
Vyzas E. and Picard R. W. Offline and Online Recognition of Emotion Expression from Physiological Data.Workshop on Emotion-Based Agent Architectures, Third International Conference on Autonomous Agents, Seattle, WA, 1999.
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Vera-Munoz, C., Pastor-Sanz, L., Fico, G., Arredondo, M., Benuzzi, F., Blanco, A. (2008). A Wearable Emg Monitoring System for Emotions Assessment. In: Westerink, J.H.D.M., Ouwerkerk, M., Overbeek, T.J.M., Pasveer, W.F., de Ruyter, B. (eds) Probing Experience. Philips Research, vol 8. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6593-4_13
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DOI: https://doi.org/10.1007/978-1-4020-6593-4_13
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