Abstract
Individuals with Mild Cognitive Impairment (MCI) currently have few treatment options against memory loss. Solutions for caring for the elderly both efficacious and cost-effective are given by Ambient Assisted Living (AAL) architecture, promising the improvement of the Quality of Life (QoL) of patients. QoL factors that are important for the MCI patients include mood, pleasant engagements, physical mobility and health, and the ability to perform activities of daily living. In this paper, we propose a daily activity reasoner that monitors, measures and analyses in real time several everyday events for building habits diary and detecting abnormal behavior of the user, part of an effective AAL system. The proposed solution is based on a combination of mean shift clustering algorithm. The reasoner offers two primary functionalities: habits building and duration and frequency of events. The reasoner can predict the behavior and detect (slow or fast) changes that might indicate modification in the health status of the user.
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References
Hahn, E.: Daily Experiences of Older Adults with Mild Cognitive Impairment. Graduate Theses and Dissertation (2012). http://scholarcommons.usf.edu/etd/4060
Irish, M., Lawlor, B., Coen, R., O’Mara, S.: Everyday episodic memory in amnestic mild cognitive impairment: a preliminary investigation. BMC Neurosci. 12, 80 (2011)
Johansson, M.: Cognitive impairment and its consequences in everyday life, Linköping University Medical Dissertation No. 1452 (2015)
Logsdon, R.G., McCurry, S.M., Teri, L.: Evidence-based interventions to improve quality of life for individuals with dementia. Alzheimers Care Today 8(4), 309–318 (2007)
Greenaway, M., Hanna, S., Lepore, S., Smith, G.: A behavioral rehabilitation intervention for amnestic Mild Cognitive Impairment. Am. J. Alzheimers Dis. Other Demen. 23(5), 451–461 (2008)
Universal Open Platform for AAL. http://www.universaal.org/
Ewall for Active Long Living project. http://ewallproject.eu
Aggarwal, C., Reddy, C.: Data Clustering: Algorithms and Applications. CRC Press, Boca Raton (2016)
Comaniciu, D., Meer, P.: Mean shift: a robust approach toward feature space analysis. IEEE Trans. Pattern Anal. Mach. Intell. 24, 603–619 (2002)
Acknowledgments
This work was supported in part by the Grant Agreement No: 610658, eWALL for Active Long Living” of the EU Seventh Framework Programme. The authors wish to thank the invaluable help received from all the consortium members.
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Tonchev, K., Velchev, Y., Koleva, P., Manolova, A., Balabanov, G., Poulkov, V. (2018). Implementation of Daily Functioning and Habits Building Reasoner Part of AAL Architecture. In: Oliver, N., Serino, S., Matic, A., Cipresso, P., Filipovic, N., Gavrilovska, L. (eds) Pervasive Computing Paradigms for Mental Health. FABULOUS MindCare IIOT 2016 2016 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 207. Springer, Cham. https://doi.org/10.1007/978-3-319-74935-8_16
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DOI: https://doi.org/10.1007/978-3-319-74935-8_16
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