Abstract
In this study, we focus on emotion recognition for service robots in the living space based on Electrocardiogram (ECG). An emotional state is important information that allows a robot system to provide appropriate services in way that are more in tune with users’ needs and preferences. Moreover, the users’ emotional state can be feedbacks to evaluate user’s level of satisfaction in the services. We apply a diagnosis method that uses both inter-beat and within-beat features of ECG. The post hoc tests in Analysis of Variance (ANOVA) showed that our approach satisfies more confidence level of difference between emotions than conventional methods. Our system design was based on wireless and wearable biological sensor for mobility and convenience of users’ daily lifestyle.
Chapter PDF
Similar content being viewed by others
References
Paul Ekman, R.W.L., Friesen, W.V.: Automomic Nervous System Activity Distingquishes among Emotions. Science, New Series 221(4616), 1208–1220 (1983)
Chun-Han Yang, K.-L.L.Y.-H.K., Wang, J.-L., Cheng, K.-S.: Negative Emotion Detection Using the Heart Rate Recovery and Time for Twelve-Beats Heart Rate Decay After Exercise Stress Test. In: International Joint Conference on Neural Networks (IJCNN), pp. 1–6. IEEE, Los Alamitos (2010)
Thayer, J., Siegle, G.: Neurovisceral integration in cardiac and emotional regulation. IEEE Engineering in Medicine and Biology Magazine 21(4), 24–29 (2002)
Wu, W., Lee, J.: Improvement of HRV Methodology for Positive/Negative Emotion Assessment. In: 5th International Conference on Collabarative Computing:Networking, Application and Worksharing, Collaborate-Com 2009, pp. 1–6. IEEE, Los Alamitos (2009)
Lee, C., Yoo, S.: ECG-based Biofeedback Chair for Selfemotion Management at Home. In: International Conference on Consumer Electronics, ICCE 2008. Digest of Technical Papers, pp. 1–2. IEEE, Los Alamitos (2008)
Rodriguez, J.D., Santos, L.: Comparative Analysis Using the 80-Lead Body Surface Map and 12-Lead ECG With Exercise Stress Echocardiograms. Journal of Diagnostic Medical Sonography 22(5), 308–316 (2006)
Vrana, B.N.C.S.R., Lang, P.J.: Fear Imagery and text processing. The International Journal of the Society for Psychophysiological Research (Psychophysiology) 23(3), 247–253 (2007)
Barbara, C.B., Fredrickson, L., Mancuso, R.A., Tugade, M.M.: The Undoing Effectof Positvie Emotion. Motivation and Emotion 24(4), 237–258 (2000)
Christie, I.C.: Multivariate Discrimination of Emotion-Specific Autonomic Nervous System Activity. Master’s thesis, Virginia Polytechnic Institute and State University (2002)
Lee, C.K.: Using Neural Network to Recognize Human Emotions from Heart Rate Variability and Skin Resistance. In: International Conference of the IEEE-Engineering in Medicine and Biology Society (IEEE-EMBS), pp. 5523–5525. IEEE, Los Alamitos (2005)
Kim, J., Andre, E.: Emotion Recognition Based on Physiological Changes in Music Listening. IEEE Transactions on Pattern Analysis and Machine Intelligence 30(12), 2067–2083 (2008)
Pedro Montoya, J.J.C., Schandry, R.: See red? Turn pale? Unveiling Emotions Cardiovascular and Hemodynamic Change. Spanish Journal of Psychology 8(001), 79–85 (2005)
KanlayaW, L.D., M., M.: Virtual Object for Evaluating Adaptable K-Nearest Neighbor Method Solving Various Conditions of Object Recognition. In: ICROS-SICE International Joint Conference 2009 (ICCAS-SICE 2009), p. 4338. IEEE, Los Alamitos (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rattanyu, K., Mizukawa, M. (2011). Emotion Recognition Using Biological Signal in Intelligent Space. In: Jacko, J.A. (eds) Human-Computer Interaction. Towards Mobile and Intelligent Interaction Environments. HCI 2011. Lecture Notes in Computer Science, vol 6763. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21616-9_66
Download citation
DOI: https://doi.org/10.1007/978-3-642-21616-9_66
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21615-2
Online ISBN: 978-3-642-21616-9
eBook Packages: Computer ScienceComputer Science (R0)