Modeling elderly behavioral patterns in single-person households

نویسندگان

چکیده

Abstract This paper proposes and describes an unsupervised computational model that monitors elderly person who lives alone issues alarms when a risk to the person’s well-being is identified. based on data extracted exclusively from passive infrared motion sensors connected ZigBee wireless network. The proposed monitoring system non-intrusive, does not capture any images, require interaction with monitored person. Thus, it more likely be adopted by members of population might reject other intrusive or complex types technology. developed for activity discovery employs kernel estimator local outlier factor calculation, which are reliable have low cost. was tested collected over period 25 days two volunteers live fairly different routines. results demonstrate model’s ability learn relevant behaviors, as well identify issue atypical activities can suggestive health problems. low-cost, minimalistic sensor network approach especially suited reality underdeveloped (and developing) countries where assisted living communities available cost ease use paramount.

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ژورنال

عنوان ژورنال: Multimedia Tools and Applications

سال: 2021

ISSN: ['1380-7501', '1573-7721']

DOI: https://doi.org/10.1007/s11042-021-10635-3