FallSensing – Technological solution for fall risk screening and falls prevention
Falls are one of the most common health related problems in the elderly population, representing more than 50% of the hospitalizations due to injuries, in this age group. They are also considered one of the main causes for institutionalization and loss of independence. In order to provide a solution to this growing concern, a consortium including Fraunhofer AICOS, Sensing Future Technologies and ESTeSC Coimbra Health School has proposed a new system, the FallSensing.
The FallSensing project enables the evaluation of multiple fall risk factors and the implementation of fall prevention exercise plans, while providing biofeedback during the execution of the exercises. The data collected during fall risk evaluations or performance of falls prevention exercises are stored in a medical record platform, so that the healthcare professionals and caregivers may follow the evolution of the user and define personalized exercise plans. These customized exercise plans may also be automatically recommended by the system promoting a continuous adaptation of the intervention plans according to the evolution of the user.
The FallSensing system is intended to be a new technological solution to enable screening and monitoring of the risk of falling and the implementation of falls prevention programs in the elderly population. The system will be simple, adapted to different use cases, portable and with low operation costs, so that everyone in risk of falling may have the possibility to reduce this risk and prevent falls.
Co-funded by Portugal 2020, the three-year project (2015-2018) is being co-developed by Sensing Future Technologies (coordenator), Fraunhofer AICOS, and ESTeSC Coimbra Health School. With a global investment of over one million euros, the aim of the FallSensing project is to become a marketable solution.
Fraunhofer AICOS will contribute with the integration of fall risk assessment algorithms based on inertial sensors, games and algorithms to detect movements. Furthermore, the research team will analyze the results from the field trials and create automatic recommendations of falls prevention plans according to the risk of falling of each person.
The main outcome will be a fall risk screening, assessing and falls prevention solution based on technology which will be validated by physiotherapists from ESTeSC Coimbra Health School in different settings: clinics, nursing homes, community health facilities and municipalities.
Falls have a multifactorial origin, however most of the fall risk factors are amendable by implementing prevention programs based on improving strength and balance and by modifying behaviors. Even though, fall risk screenings and the implementation of such falls prevention programs are rarely part of the elder’s routine.
The FallSensing represents another opportunity for Fraunhofer AICOS to transfer to the market, the knowledge and solutions created in the Fall Competence Center.