AI Article Synopsis

  • There is an increase in elderly individuals living alone due to advancements in medicine and technology, but challenges like crowded hospitals and expensive caretakers make home monitoring more appealing.
  • The study introduces an anonymous monitoring system using a smartphone app to track daily activities and potential risks for the elderly, focusing on tasks like sleep, medication, and food intake.
  • Results show that the proposed system identified 75.2% of risks, outperformed other methods in responsiveness (176.46 min), and had a quicker reporting interface time (28 s).

Article Abstract

There has been a subsequent increase in the number of elderly people living alone, with contribution from advancement in medicine and technology. However, hospitals and nursing homes are crowded, expensive, and uncomfortable, while personal caretakers are expensive and few in number. Home monitoring technologies are therefore on the rise. In this study, we propose an anonymous elderly monitoring system to track potential risks in everyday activities such as sleep, medication, shower, and food intake using a smartphone application. We design and implement an activity visualization and notification strategy method to identify risks easily and quickly. For evaluation, we added risky situations in an activity dataset from a real-life experiment with the elderly and conducted a user study using the proposed method and two other methods varying in visualization and notification techniques. With our proposed method, 75.2% of the risks were successfully identified, while 68.5% and 65.8% were identified with other methods. The average time taken to respond to notification was 176.46 min with the proposed method, compared to 201.42 and 176.9 min with other methods. Moreover, the interface analyzing and reporting time was also lower (28 s) in the proposed method compared to 38 and 54 s in other methods.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9504654PMC
http://dx.doi.org/10.3390/s22186965DOI Listing

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