A decision support system for preventing falls in elderly people

Abstract

Preventing falls in older people is a real challenge for Pub-lic Health. This paper addresses this issue by designing a decision support system which provides a fall risk index. The proposed approach is based on three selected tests (the Timed up and go (TUG), the 30s sit-To-stand and the 4-stage balance tests), which are widely used in the medical sector for assessing mobility and balance of the elderly. Dur-ing the tests, a video records the older person performing the test and thanks to an image processing algorithm, kinemat-ics and biomechanics parameters are extracted. Based on fuzzy logic, a decision support system fuses all these data and estimates a fall risk index according to the senior's age and gender. It can also assist the Health Professional in making improved medical diagnosis relied on targeted mea-surements. Simulation results drawing on experimental data of 12 older persons performing the TUG test illustrate the feasibility and the effectiveness of the proposed approach. Objectively assessing the senior's motor functions and the fall risk is possible in less than 10 minutes, at low cost and in an easy and non invasive way.