Predicting elderly falls days in advance
A team from the University of Missouri College of Engineering has teamed up with the Sinclair School of Nursing to develop a system that predicts an increased risk of falling among the elderly in their homes up to 3 weeks in advance. It uses Microsoft's Kinect sensors to analyse gait speed and stride length of people at home to predict their likeliness of falling. In case of alert, caretakers are immediately informed by email to intervene before a fall takes place.
This system is in line with the current trend of prediction technologies and behavioural analysis and the innovations of support for the elderly (Do-Pill connected pill box, Caresquare digital companion, etc.). With this support, seniors could live independently much longer, but insurers might make this type of tool mandatory.
Spotted in 2018
- United States