Authors:
Alexander Gerka
1
;
Christian Lins
1
;
Max Pfingsthorn
1
;
Marco Eichelberg
1
;
Sebastian Müller
2
;
Christian Stolle
2
and
Andreas Hein
2
Affiliations:
1
OFFIS - Institute for Information Technology, Escherweg 2, Oldenburg and Germany
;
2
Department for Health Services Research, Carl-von-Ossietzky University, Oldenburg and Germany
Keyword(s):
Behavior Modeling, Assisted Living, Dementia, Activities of Daily Living, Clustering, χ2-statistic.
Related
Ontology
Subjects/Areas/Topics:
Applications and Uses
;
Home Monitoring and Assisted Living Applications
;
Sensor Networks
Abstract:
The modeling of behavior by monitoring activities of daily living allows caregivers to recognize early stages of dementia. Therefore, many monitoring systems were presented in recent years. In this work, we present a behavior modeling system that is based only on two adjustable parameters and provides a single standardized output statistic. Therefore, this system enhances the comparison of recent and future activity monitoring systems. The approach is comprised of three parts: First, the clustering of power plug data to detect time windows in which appliances are used regularly. Second, the calculation of a comparison Matrix. Third the test of change using the χ2-statistic. We tested this approach successfully in a seven-month field study with two healthy subjects. We showed that the χ2-statistic reflected how regular activities were performed and that one to two months, depending on the regularity of the performed activities, provide the necessary amount of reference data for our ap
proach to work.
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