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 app roach to work.
@conference{Gerka2019clustering,
author={Alexander Gerka and Christian Lins and Max Pfingsthorn and Marco Eichelberg and Sebastian Müller and Christian Stolle and Andreas Hein},
title={A Clustering-based Approach to Determine a Standardized Statistic for Daily Activities of Elderly Living Alone},
booktitle={Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF,},
year={2019},
pages={264-271},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007369302640271},
isbn={978-989-758-353-7},
}