07-005 – A mobile application with automatic fall detection for assistance in elderly health care and well-being

Chanduví G.D.A.; Quinde Li Say Tan M.; Hidalgo Hidalgo N.E.; Alamo Figallo V.S.; Vargas Sánchez G.A. · Proceedings from the International Congress on Project Management and Engineering (2025)

Resumen

Elderly adults tend to suffer from physical and cognitive limitations, which diminish their ability to perform daily activities independently, even impacting their social lives. This research proposes a mobile application that supports elderly adults with physical and cognitive limitations in improving their quality of life. Their primary needs and those of their carers were analysed to define the proposal’s requirements. The research aims to develop a comprehensive technological tool (mobile application) to assist the elderly in critical activities, such as appointments and medication intake automatic reminders. The solution includes a fall detection component based on a supervised learning algorithm (Random Forest), triggering timely alerts as part of a communication component among older adults and their carers. The proposal also implements a recommendation section for older adults’ health care and well-being. The research followed a user-centric methodology that included stakeholders (older adults and carers) to guarantee its acceptance. The validation with 12 potential users was based on the Technology Acceptance Model, showing promising results.

Instituciones: Universidad de Piura