1,000 adults fall in Israel every day. A third of which result in injuries, loss of independence, and even death.

Falls and injuries will most likely rise as the population ages.

Fortunately, exercise programs are effective in reducing the rate of falls among home dwelling elderly. Early and effective detection and prevention will: Reduce suffering, improve quality of life, Reduce the socio-economic ramifications on society.

Existing fall risk assessments protocols and preventive exercise programs are designed as face-to-face (FTF) procedures. Those are less accessible to individuals who live in suburban areas or are challenged by accessibility issues. Indeed, the difficulties in obtaining FTF healthcare services, manifested very strongly during the recent COVID pandemic. One line of solution, which has accelerated recently, is remote healthcare (or telehealth). Furthermore, although there are several valid and reliable fall risk screening tools, there is no one single gold standard.

This data collection project is a collaboration between physiotherapists from the clinical field and academia, with computer and data science engineers. The main objective of this project is the acquisition of a rigorous and comprehensive dataset that includes a multitude of balance testing results of various kinds, as well as recorded 2D and 3D data of individuals performing these tests. The database serves to advance studies to develop measures for efficient and adaptive balance evaluation from afar or in face-to-face assessments.