The platform intends to analyze the status of the elderly person, both physically and mentally, in terms of fragility, and then assign individualized physical and mental exercises to avoid the risk of possible falls, using an accessible and affordable solution that combines videos for exercises and serious games to both train and detect physical or cognitive fragility.
Deep Learning techniques will be applied in order to help the frAAgiLe system learn about the fragility history of each individual end-user and customize the training plan according to his/her evolution.
What frAAgiLe plans to do: analyse the status of the person, physically and mentally, in terms of fraility, and offer physical and mental exercises to avoid the risk of possible falls using an accessible and affordable solution that combines videos for exercises and serious games to both train and detect physical or cognitive fraility. In this project, we involve 3 different end-users organizations to co-create the platform with them.
The system will also focus on being as cheap and less intrusive as possible, using only tablets and wearables.
For patients at home
It would offer support in preventing falls, greater independence and better quality of life. Improved health outcomes avoiding hospitalizations related to frailty are also expected.
For Health and Care Systems
FrAAgiLe will reduce costs related to the treatment of frail individuals as risk situations will be detected before they occur, allowing healthcare organizations to take action on time.
For end-user oganisations
We would also validate the benefits for those end-user organisations, in terms of positive changes in the state of their patients, but also in the impact in their own processes and workers and the marketing it could give them.
Potential new market
The project will also try to analyse the existence of a potential new market for early frailty detection across Europe.