|Department: Human Movement Sciences||Section: Neuromechanics|
|Research area/-theme: fall detection, elderly, fall prevention
|Researchers: Kim van Schooten, Sietse Rispens||Supervisors: Jaap van Dieën, Mirjam Pijnappels|
|In collaboration with: McRoberts, Verklizan, Puur Zuid
One in three people over 65 falls once a year. In the coming decades the population will grow older and the burden on the healthcare system will increase. By reducing the number of falls and injuries in older people they will be independent for longer, live independently while maintaining quality of life, and medical costs will be reduced. To inform healthcare providers, such as GPs and homecare organizations, at an early stage about the risk of falling, it is necessary to accurately determine the risk of falling.
In this research a system is developed to support the prevention of falls among the elderly. This system is based on small motion monitors (Move Monitor) worn on the body by the participants in the study. The system can record movements up to a week. With the information collected, methods have been developed and tested by which an estimate can be made of the risk of a fall. This information can ultimately be made available to health care providers to support the prevention of falls.
In the future we also hope to provide fast and adequate care with automated systems to enable direct emergency personnel when a fall has occurred. We strive for real-time detection of unstability, for example by fatigue, allowing the wearer of the system to be alerted immediately when there is a greater risk of falling.