Video-based Fall Risk Detection System for the Elderly
Hiroaki Kingetsu, Takeshi Konno, Shuji Awai, Daisuke Fukuda, Toshihiro Sonoda · 2019 IEEE 1st Global Conference on Life Sciences and Technologies (LifeTech) · 2019
The use of high frequencies is essential in detecting deterioration in a physical function, but expert evaluation is expensive, and there are various other problems such as the need for many measurement devices. The aim of this study was to automate the evaluation of fall risk by video recording the gaits of elderly people using a general camera. We took videos of 12 subjects performing a 5-m walking test in a nursing home. In this paper, we evaluate (1) the use of the feature extraction method on walking behavior obtained from video recordings and (2) the accuracy of fall prediction using machine learning.