Abstract
In this study, we reported a smart sensing system for detecting Human Emotion and Behaviour Recognition. The inhabitant emotions are sensed based on information from the physiological sensors as happiness, sadness, stressed and neutral. Also, we defined two new wellness functions to determine the regularity of house-hold activities and foresee changes in the domestic activity behaviour. Developed intelligent program was tested at different elderly houses living alone and the results are encouraging. The developed system is less cost, reliable and robust in realizing functional condition of the inhabitant both emotionally and physically.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Figner, B., Murphy, R.O.: Using skin conductance in judgment and decision making research. In: Schulte-Mecklenbeck, M., Kuehberger, A., Ranyard, R. (eds.) A Handbook of Process Tracing Methods for Decision Research. Psychology Press, New York
Zhongna, Z., Wenqing, D., Eggert, J., Giger, J.T., Keller, J., Rantz, M., He, Z.: A real-time system for in-home activity monitoring of elders. In: Proceedings of the Annual International Conference of IEEE Engineering in Medicine and Biology Society, EMBC 2009, September 3-6, pp. 6115–6118 (2009)
George, P., George, X., George, P.: Monitoring and Modeling Simple Everyday Activities of the Elderly at Home. In: Proceedings of the 7th IEEE Consumer Communications and Networking Conference, CCNC 2010, vol. 007(01), pp. 1–5 (January 2010)
Jian, K.W., Liang, D., Wendong, X.: Real-time Physical Activity classification and tracking using wearable sensors. In: Proceedings of the 6th International Conference on Information, Communications & Signal Processing, pp. 1–6 (December 2007)
Yu-Jin, H., Ig-Jae, K., Sang, C.A., Hyoung-Gon, K.: Activity Recognition using Wearable Sensors for Elder Care. In: Proceedings of the 2nd International Conference on Future Generation Communication and Networking, FGCN 2008, December 13-15, vol. 2, pp. 302–305 (2008)
Hung, K.P., Tao, G., Wenwei, X., Palmes, P.P., Jian, Z., Long Ng, W., Chee, W.T., Nguyen, H.C.: Context-aware middleware for pervasive elderly homecare. IEEE Journal on Selected Areas in Communications 27(4), 510–524 (2009)
Moshaddique, A.A., Kyung-sup, K.: Social Issues in Wireless Sensor Networks with Healthcare Perspective. The International Arab Journal of Information Technology 8(1), 34–39 (2011)
Seon-Woo, L., Yong-Joong, K., Gi-Sup, L., Byung-Ok, C., Nam-Ha, L.: A Remote Behavioral Monitoring System for Elders Living Alone. In: Proceedings of the International Conference on Control, Automation and Systems, ICCAS 2007, pp. 2725–2730 (2007)
Lymberopoulos, D., Bamis, A., Eixeira, T., Savvides, A.: BehaviorScope: Real-Time Remote Human Monitoring Using Sensor Networks. In: Proceedings of the International Conference on Information Processing in Sensor Networks, IPSN 2008, pp. 533–534 (April 2008)
Medjahed, H., Istrate, D., Boudy, J., Dorizzi, B.: Human activities of daily living recognition using fuzzy logic for elderly home monitoring. In: Proceedings of the IEEE International Conference on Fuzzy Systems, pp. 2001–2006 (2009)
Nazerfard, E., Rashidi, P., Cook, D.J.: Discovering Temporal Features and Relations of Activity Patterns. In: IEEE International Conference on Data Mining Workshops (ICDMW), pp. 1069–1075 (2010)
Murugappan, M., Rizon, M., Nagarajan, R., Yaacob, S., Zunaidi, I., Hazry, D.: EEG Feature Extraction for Classifying Emotions using FCM and FKM. International Journal of Computers and Communications 1(2), 21–25 (2007)
Witten, H.I., Frank, E.: Data Mining: Practical machine Learning tools and techniques. Morgan Kaufmann Pub. (2005)
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA Data Mining Software: An Update. SIGKDD Explorations 11(1) (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Suryadevara, N.K., Quazi, T., Mukhopadhyay, S.C. (2012). Smart Sensing System for Human Emotion and Behaviour Recognition. In: Kundu, M.K., Mitra, S., Mazumdar, D., Pal, S.K. (eds) Perception and Machine Intelligence. PerMIn 2012. Lecture Notes in Computer Science, vol 7143. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27387-2_2
Download citation
DOI: https://doi.org/10.1007/978-3-642-27387-2_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27386-5
Online ISBN: 978-3-642-27387-2
eBook Packages: Computer ScienceComputer Science (R0)