NDLI: An approach for detecting deviations in daily routine for long-term behavior analysis

Content Provider	IEEE Xplore Digital Library
Author	Elbert, D. Storf, H. Eisenbarth, M. Unalan, O. Schmitt, M.
Copyright Year	2011
Description	Author affiliation: Fraunhofer IESE, Kaiserslautern, Germany (Storf, H.; Eisenbarth, M.; Unalan, O.; Schmitt, M.) \|\| Hochschule Mannheim, Mannheim, Germany (Elbert, D.)
Abstract	Rendering and offering adequate reminder services in a situation-aware, proactive manner and providing information for diagnosis support is a major issue for Ambient Assisted Living systems when it comes to dealing with persons suffering from mild dementia. One great challenge therefore is to reliably recognize and assess the long-term behavior of assisted persons. In the context of diagnosis support for caregivers or practitioners, deviations in the daily routine of a person with mild dementia might be an indicator of a deterioration of the affected person's cognitive condition. Based on this information, adequate help can be provided. We developed an approach to processing information regarding the modeling of daily routines and a comparison to previous days. Our solution can be seen as a combination of three approaches: a cosinor analysis based on the theory of circadian rhythms as a special representative of regression analysis, a histogram-based approach based on movement data, and a probabilistic model of behavior (PMB) based on the person's activities of daily living (ADL).
Starting Page	426
Ending Page	433
File Size	984425
Page Count	8
File Format	PDF
ISBN	9781612847672
e-ISBN	9781936968152
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-05-23
Publisher Place	Ireland
Access Restriction	Subscribed
Rights Holder	ICST
Subject Keyword	Calculators Behavior Monitoring Senior citizens Probabilistic logic Ambient Assisted Living Circadian rhythm Circadian Rhythm Biomedical monitoring Monitoring Dementia
Content Type	Text
Resource Type	Article

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