A Sensor-Based mHealth Platform for Remote Monitoring and Intervention of Frailty Patients at Home

Jorge Calvillo-Arbizu, David Naranjo-Hernández, Gerardo Barbarov-Rostán, Alejandro Talaminos-Barroso, Laura M. Roa-Romero and Javier Reina-Tosina
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Jorge Calvillo-Arbizu: Biomedical Engineering Group, University of Seville, 41092 Seville, Spain
David Naranjo-Hernández: Biomedical Engineering Group, University of Seville, 41092 Seville, Spain
Gerardo Barbarov-Rostán: Biomedical Engineering Group, University of Seville, 41092 Seville, Spain
Alejandro Talaminos-Barroso: Biomedical Engineering Group, University of Seville, 41092 Seville, Spain
Laura M. Roa-Romero: Biomedical Engineering Group, University of Seville, 41092 Seville, Spain
Javier Reina-Tosina: Biomedical Engineering Group, University of Seville, 41092 Seville, Spain

IJERPH, 2021, vol. 18, issue 21, 1-18

Abstract: Frailty syndrome is an independent risk factor for serious health episodes, disability, hospitalization, falls, loss of mobility, and cardiovascular disease. Its high reversibility demands personalized interventions among which exercise programs are highly efficient to contribute to its delay. Information technology-based solutions to support frailty have been recently approached, but most of them are focused on assessment and not on intervention. This paper describes a sensor-based mHealth platform integrated in a service-based architecture inside the FRAIL project towards the remote monitoring and intervention of pre-frail and frail patients at home. The aim of this platform is constituting an efficient and scalable system for reducing both the impact of aging and the advance of frailty syndrome. Among the results of this work are: (1) the development of elderly-focused sensors and platform; (2) a technical validation process of the sensor devices and the mHealth platform with young adults; and (3) an assessment of usability and acceptability of the devices with a set of pre-frail and frail patients. After the promising results obtained, future steps of this work involve performing a clinical validation in order to quantify the impact of the platform on health outcomes of frail patients.

Keywords: mHealth; frailty; health information technology; sensors; fall detection; activity recognition (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
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