PRECISE
On average will 30% of people aged 65 or older experience one fall a year, making this a huge burden for healthcare systems and society. Due to the inactivity in most elderly people, they have poor muscle strength and balance, resulting in falls. Early detection and personalised interventions are needed to ease the burden on the healthcare system. PRECISE aims to build an effective decision support system by using Artificial Intelligence-Machine Learning (AI-ML) to analyse extensive data from screenings by DigiRehab and local data from Poland, Italy, Norway, the Netherlands, and Denmark to help formal and informal caregivers to assess the risk of falling of the elderly and using tailored exercise programs to regain muscle strength. During the project, there will be multiple pilots at all partners with end-users, both because the homecare structure is different in the partner countries and to evaluate the DSS predictions in terms of accuracy in a real-life setting and user interface.