Risk situation detector for elderly people based on time series analysis

• Maicon Diogo Much Duos Technology Solutions / PUCRS
• Cesar Augusto Missio Marcon PUCRS

DOI: https://doi.org/10.5753/sbcas_estendido.2025.7027

Abstract

Elderly people are more exposed to risk situations such as falls, sudden changes in vital signs and fainting. These situations become more common at this stage of life due to the natural decrease in the body's ability to coordinate movements adequately. Numerous studies have proposed health monitoring systems for this population group, but the use of these systems in real situations has shown that this approach is still insufficient to accurately differentiate a risk situation from person's daily activities. This project proposes the development of an effective and reliable health monitoring system for the elderly, through the continuous collection of time series extracted from movement sensors associated with vital signs. For this evaluation, an environment composed of a wearable device simulator, a mobile application simulator and a cloud system simulator was created, very close to the real scenario. This system, in its final model, presented an overall accuracy of 97%, showing that sensor fusion in a continuous data analysis architecture contributes to increasing the elderly risk detection capacity.

References

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