Reducing fall incidence in community elders by telecare using predictive systems

Abstract

Sensors have been developed to measure the relevant parameters that are associated with falls of the elderly living in the community; these include mobility, transfer rate, weight and impact history. The sensor outputs are fed into a computer system together with other biomedical factors such as age, sex, eye-sight and medication. A predictive algorithm is described which determines the likelihood of a fall; this predictive system may form the basis of a practical telecare method to enable early intervention and reduce the number of falls.