Abstract
With today's technology, elderly can be supported in living independently in their own homes for a prolonged period of time. Monitoring and analyzing their behavior in order to find possible unusual situation helps to provide the elderly with health warnings at the proper time. Current studies are focusing on the elderly daily activity and the detection of anomalous behaviors aiming to provide the older people with remote support. To this aim, we propose a real-time solution which models the user daily routine using a task model specification and detects relevant contextual events occurred in their life through a context manager. In addition, by a systematic validation through a system that automatically generates wrong sequences of tasks, we show that our algorithm is able to find behavioral deviations from the expected behavior at different times by considering the extended classification of the possible deviations with good accuracy.
- James F Allen. 1983. Maintaining knowledge about temporal intervals. Commun. ACM 26, 11 (1983), 832--843. Google Scholar
Digital Library
- James F Allen and George Ferguson. 1994. Actions and events in interval temporal logic. Journal of logic and computation 4, 5 (1994), 531--579.Google Scholar
Cross Ref
- Oya Aran, Dairazalia Sanchez-Cortes, Minh-Tri Do, and Daniel Gatica-Perez. 2016. Anomaly detection in elderly daily behavior in ambient sensing environments. In International Workshop on Human Behavior Understanding. Springer, 51--67.Google Scholar
Cross Ref
- UABUA Bakar, Hemant Ghayvat, SF Hasanm, and SC Mukhopadhyay. 2016. Activity and anomaly detection in smart home: A survey. In Next Generation Sensors and Systems. Springer, 191--220.Google Scholar
- Matthew L Bolton and Ellen J Bass. 2013. Generating erroneous human behavior from strategic knowledge in task models and evaluating its impact on system safety with model checking. IEEE Transactions on Systems, Man, and Cybernetics: Systems 43, 6 (2013), 1314--1327.Google Scholar
Cross Ref
- Matthew L Bolton, Radu I Siminiceanu, and Ellen J Bass. 2011. A systematic approach to model checking human-- automation interaction using task analytic models. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans 41, 5 (2011), 961--976. Google Scholar
Digital Library
- Zoraida Callejas and Ramón López-Cózar. 2009. Designing smart home interfaces for the elderly. ACM SIGACCESS Accessibility and Computing 95 (2009), 10--16. Google Scholar
Digital Library
- José Creissac Campos, Camille Fayollas, Marcelo Gonçalves, Célia Martinie, David Navarre, Philippe Palanque, and Miguel Pinto. 2017. A More Intelligent Test Case Generation Approach through Task Models Manipulation. Proceedings of the ACM on Human-Computer Interaction 1, 1 (2017), 9. Google Scholar
Digital Library
- Céline Franco, Jacques Demongeot, Christophe Villemazet, and Nicolas Vuillerme. 2010. Behavioral telemonitoring of the elderly at home: Detection of nycthemeral rhythms drifts from location data. In Advanced Information Networking and Applications Workshops (WAINA), 2010 IEEE 24th International Conference on. IEEE, 759--766. Google Scholar
Digital Library
- Giuseppe Ghiani, Marco Manca, Fabio Paternò, and Carmen Santoro. 2017. Personalization of context-dependent applications through trigger-action rules. ACM Transactions on Computer-Human Interaction (TOCHI) 24, 2 (2017), 14. Google Scholar
Digital Library
- Matthias Giese, Tomasz Mistrzyk, Andreas Pfau, Gerd Szwillus, and Michael Von Detten. 2008. AMBOSS: a task modeling approach for safety-critical systems. In Engineering Interactive Systems. Springer, 98--109. Google Scholar
Digital Library
- M Helander. 1988. Towards a practical GOMS model methodology for user interface design. In Handbook of humancomputer interaction. North-Holland, 135--158.Google Scholar
- Erik Hollnagel. 1993. The phenotype of erroneous actions. International Journal of Man-Machine Studies 39, 1 (1993), 1--32. Google Scholar
Digital Library
- Vikramaditya Jakkula, Diane J Cook, et al. 2008. Anomaly detection using temporal data mining in a smart home environment. Methods of information in medicine 47, 1 (2008), 70--75.Google Scholar
- Barry Kirwan and Les K Ainsworth. 1992. A guide to task analysis: the task analysis working group. CRC press.Google Scholar
- Linda Lankewicz and Mark Benard. 1991. Real-time anomaly detection using a nonparametric pattern recognition approach. In Computer Security Applications Conference, 1991. Proceedings., Seventh Annual. IEEE, 80--89.Google Scholar
Cross Ref
- Ahmad Lotfi, Caroline Langensiepen, Sawsan M Mahmoud, and Mohammad Javad Akhlaghinia. 2012. Smart homes for the elderly dementia sufferers: identification and prediction of abnormal behaviour. Journal of ambient intelligence and humanized computing 3, 3 (2012), 205--218.Google Scholar
Cross Ref
- Marco Manca, Parvaneh Parvin, Fabio Paternò, and Carmen Santoro. 2017. Detecting anomalous elderly behaviour in ambient assisted living. In Proceedings of the ACM SIGCHI Symposium on Engineering Interactive Computing Systems. ACM, 63--68. Google Scholar
Digital Library
- Célia Martinie, Philippe Palanque, David Navarre, Marco Winckler, and Erwann Poupart. 2011. Model-based training: an approach supporting operability of critical interactive systems. In Proceedings of the 3rd ACM SIGCHI symposium on Engineering interactive computing systems. ACM, 53--62. Google Scholar
Digital Library
- Célia Martinie, Philippe Palanque, and Marco Winckler. 2011. Structuring and composition mechanisms to address scalability issues in task models. In IFIP Conference on Human-Computer Interaction. Springer, 589--609. Google Scholar
Digital Library
- Lei Meng, Chunyan Miao, and Cyril Leung. 2017. Towards online and personalized daily activity recognition, habit modeling, and anomaly detection for the solitary elderly through unobtrusive sensing. Multimedia Tools and Applications 76, 8 (01 Apr 2017), 10779--10799. Google Scholar
Digital Library
- Susan Michie, Maartje M van Stralen, and Robert West. 2011. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implementation science 6, 1 (2011), 42.Google Scholar
- Dorothy N Monekosso and Paolo Remagnino. 2010. Behavior analysis for assisted living. IEEE Transactions on Automation science and Engineering 7, 4 (2010), 879--886.Google Scholar
Cross Ref
- Giulio Mori, Fabio Paternò, and Carmen Santoro. 2002. CTTE: support for developing and analyzing task models for interactive system design. IEEE Transactions on software engineering 28, 8 (2002), 797--813. Google Scholar
Digital Library
- Laila Paganelli and Fabio Paternò. 2003. Tools for remote usability evaluation of Web applications through browser logs and task models. Behavior Research Methods 35, 3 (2003), 369--378.Google Scholar
- Fabio Paternò, Cristiano Mancini, and Silvia Meniconi. 1997. ConcurTaskTrees: A diagrammatic notation for specifying task models. In Human-Computer Interaction INTERACT'97. Springer, 362--369. Google Scholar
Digital Library
- François Portet, Michel Vacher, Caroline Golanski, Camille Roux, and Brigitte Meillon. 2013. Design and evaluation of a smart home voice interface for the elderly: acceptability and objection aspects. Personal and Ubiquitous Computing 17, 1 (2013), 127--144. Google Scholar
Digital Library
- James Reason. 1990. Human error. Cambridge university press.Google Scholar
- Janine L Wiles, Annette Leibing, Nancy Guberman, Jeanne Reeve, and Ruth ES Allen. 2012. The meaning of 'aging in place' to older people. The gerontologist 52, 3 (2012), 357--366.Google Scholar
- Weilie Yi and Dana H Ballard. 2006. Behavior recognition in human object interactions with a task model. In Video and Signal Based Surveillance, 2006. AVSS'06. IEEE International Conference on. IEEE, 64--64. Google Scholar
Digital Library
- Anna Zisberg, Nurit Gur-Yaish, and Tamar Shochat. 2010. Contribution of routine to sleep quality in community elderly. Sleep 33, 4 (2010), 509--514.Google Scholar
Cross Ref
Index Terms
Real-Time Anomaly Detection in Elderly Behavior with the Support of Task Models
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