Commenced in January 2007
Paper Count: 31097
Non-Invasive Technology on a Classroom Chair for Detection of Emotions Used for the Personalization of Learning Resources
Abstract:Emotions are related with learning processes and physiological signals can be used to detect them for the personalization of learning resources and to control the pace of instruction. A model of relevant emotions has been developed, where specific combinations of emotions and cognition processes are connected and integrated with the concept of 'flow', in order to improve learning. The cardiac pulse is a reliable signal that carries useful information about the subject-s emotional condition; it is detected using a classroom chair adapted with non invasive EMFi sensor and an acquisition system that generates a ballistocardiogram (BCG), the signal is processed by an algorithm to obtain characteristics that match a specific emotional condition. The complete chair system is presented in this work, along with a framework for the personalization of learning resources.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1079802Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1327
 Nakasone, Arturo, Prendinger, Helmut and Ishizuka, Mitsuru Emotion Recognition from Electromyography and Skin Conductance.. 2005. The Fifth International Workshop on Biosignal Interpretation BSI-05.
 Zhai, Jing and Barreto, Armando Stress Detection in Computer Users Based on Digital Signal Processing of Noninvasive Physiological Variables.. New York City : s.n., 2006. Proceedings of the 28th IEEE EMBS Annual International Conference.
 Picard, Rosalind W. Affective Computing. s.l. : MIT Press, 2000.
 Arroyo-Palacios, J. and Romano, D.M. Towards a Standarization in the Use of Physiological Signals for Affective Recognition Systems. The Netherlands : s.n., 2008. Proceedings of Measuring Behavior.
 Cs├¡kszentmih├ílyi, Mih├íly. Flow: The Psychology of Optimal Experience. New York : Harper and Row, 1990.
 Steels, L. An Architecture of Flow.
[book auth.] M. Tokoro and L. Steels. A Learning Zone of One's Own. Amsterdam : IOS Press, 2004, pp. 137-150.
 Kort, B., Reilly, R. and Picard, R.W. An Affective Model of Interplay between Emotions and Learning. Madison, WI : IEEE, 2001. Conference on Advanced Learning Technologies. pp. 43-46.
 Kleine, M., et al. The structure of students' emotions experienced during a mathematical achievement test. 2005, ZDM.
 Pekrun, R., Frenzel, A. and Goetz, T. The Control-Value Theory of Achievement Emotions: An Integrative Approach to Emotion in Education.
[book auth.] M. Tokoro and L. Steels. Emotion in Education. San Diego : Academic Press, 2007, pp. 13-36.
 Chaffar, S. and Frasson, C. The Emotional Conditions of Learning. 2005, American Association for Artificial Intelligence.
 Craig, S. D., et al. Affect and learning: an exploratory look into the role of affect in learning with AutoTutor. October 2004, Journal of Educational Media.
 D'Mello, S., et al. AutoTutor Detects and Responds to Learners Affective and Cognitive States. Montreal, Canada : s.n., 2008. Workshop on Emotional and Cognitive Issues at the International Conference of Intelligent Tutoring Systems.
 Mota, Selene and Picard, Rosalind. Automated Posture Analysis for Detecting Learner's Interest Level. Computer Vision and Patten Recognition Workshop, 2003
 Boekaerts, M. and Corno, L. Self-Regulation in the Classroom: A Perspective on Assessment and Intervention. University of Leiden, The Netherlands : Applied Psychology: An Internatinal Review, 2005.
 Lekkala, J., Salpavaara, T. and K├ñrki, S. EMFI - Vesatile Material for Monitoring of Human Functions. Rio de Janeiro : s.n., 2006. XVIII Imeko World Congress.
 Alamets├ñ, J., et al. The Potential of EMFi Sensors in Heart Activity Monitoring. Berlin, Germany : s.n., 2004. 2nd OpenECG Workshop "Integration of the ECG into the EHR & Interoperability of ECG Device Systems".
 Koivistoinen, T., Junnila, S. and V├ñrri, A. An EMFi-film Sensor based Ballistocardiographic Chair: Performance and Cycle Extraction Method. 2005. IEEE Workshop on Signal Processing Systems Design and Implementation. pp. 373-377.
 Koivistoinen, T., et al. A New Method for Measuring the Ballistocardiogram using EMFi Sensors in a normal chair. San Francisco, CA : s.n., 2004. Proceedings of the 26th Annual International Conference of the IEEE EMBS.
 K├ñrki, S., K├ñ├ñri├ñinen, M. and Lekkala, J. Measurement of heart sounds with EMFi transducer. Lyon, France : s.n., 2007. Proceedings of the 29th Annual International Conference of the IEEE EMBS.
 Anttonen, J. Using the EMFi chair to measure the user's emotion-related heart rate responses. Department of Computer Sciences, University of Tampere. 2005. Master's Thesis.
 Vyzas, E. Recognition of Emotional and Cognitive States Using Pshysiological Data. Department of Mechanical Engineering, Massachusetts Institute of Technology. Massachusetts : s.n., 1999. Bachelor Thesis.
 Kamiya, K., et al. Sitting Posture Analysis by Pressure Sensors. 2008. ICPR08. pp. 1-4.
 Graesser, A. C., et al. Detection of Emotions During Learning with AutoTutor. Vancouver, Canada : s.n., 2006. Proceedings of the 28th Annual Meeting of the Cognitive Science Society. pp. 285-290.
 Paquette, G. An Ontology and a Software Framework for Competency Modeling and Management Competency in an Instructional Engineering Method ( MISA ). 2007. Educational Technology & Society, 10, pp. 1- 21.
 Anderson, J. R., Bothell, D., Byrne, M. D., Douglass, S., Lebiere C., Qin, Y., et al. (2004). An Integrated Theory of the Mind. Psychological Review, 111, (4), 1036-1060. Retrieved from http://actr. psy.cmu.edu/publications/pubinfo.php?id=526
 Newell, A. Unified Theories of Cognition. MA: Harvard University Press 1994.
 Ramirez, C., & Cooley, R. . A Theory of the Acquisition of Episodic Memory. In Proceeding of the ECML-97: Case-Based Reasoning Workshop. Prague,. Czech Republic.: Springer-Verlag. 1997a, p48-55
 Wang, Y. The Theoretical Framework and Cognitive Process of Learning. In D. Zhang, Y. Wang, & W. Kinsner, Proc. 6th IEEE Int. Conf. on Cognitive Informatics (ICCI'07) 2007 pp. 470-479.
 Ramirez, C., Valdes, B. "A general knowledge representation model for the acquisition of skills and concepts," coginf, pp.412-417, 2009 8th IEEE International Conference on Cognitive Informatics, 2009
 Torres, J., Dodero, J. M., Ramirez, C., Valdes, B., & Lugo, A.. Adaptive Learning Scenarios Based on Student Profile. In U. A. de Yucat├ín, Recursos Digitales para el Aprendizaje. 2009 pp. 348-349.
 Torres, J., Ju├írez, E., Dodero, J. M., & Aedo, I. Advanced Transactional Models for Complex Learning Processes. In Recursos Digitales para el Aprendizaje. Merida: U A. de Yucatan. . 2009