Technological pervasive platform for fall detection, fall risk assessment and prevention



The worldwide population aged over 65 is rapidly growing and the consequences are simultaneously social, health-related and economic. The process of aging impacts mobility, muscle strength and balance control which contributes to the increase of falls occurrence in this population. Currently, there are a variety of solutions to address only specific stages of the fall management lifecycle: assessing multiple fall risk factors, detecting falls automatically, and providing strategies for falls prevention that focuses on attenuating specific fall risk factors. However, most technological solutions do not allow to close the falls management loop by simultaneously addressing fall detection (FD), fall risk assessment (FRA) and fall prevention (FP).



The solution proposed by FRADE is composed of a bundle of components (wearable sensor, desktop application, Android application and backend server with web interface) to perform FD, FRA, and FP. The elder will use the wearable sensor to monitor falls and to provide a continuous estimation of fall risk, based on movement analysis. It sends an alarm to the backend server and an SMS to a caregiver whenever a fall is detected (if outside, the location will also be sent). The wearable device will also be used to monitor the elder’s movements and communicate with the desktop and Android application while he/she performs FRA tests and FP exergames. All the monitored data is stored in the backend server and can be accessed through its web interface, by a caregiver.



A system for fall management composed of a wearable device and a bundle of applications. The system can be used to i) pervasively detect falls and assess fall risk factors in daily life; ii) monitor movements during fall risk assessment tests to estimate a risk of falling using a desktop application, with the supervision of a healthcare provider; iii) monitor movements during the performance of fall prevention exercises using a tablet application. The trials conducted will allow us to evaluate the performance of the FD, and to screen part of the elderly population in the North region of Portugal. The FD, FRA will provide insights on the effectiveness of the fall prevention exercises.


Project Partner: Escola Superior de Enfermagem do Porto (ESEP)

Local EIT Health RIS hub: University of Porto (UP)

Funding Agency: EIT Health InnoStars

Mentor dedicated by InnoStars: Timothy M.McGloughlin, PhD / Emeritus Professor, Biomedical Engineering, University of Limerick

Funding Program: EIT Health RIS

Call Identifier: EIT Health RIS Innovation Call 2020

Project ID: RIS-1001-8273


Funded by:

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