Evaluation of Fall Data Generated by Adversarial Generative Networks

Abstract

In Japan, where the population is aging, falls are a serious cause of bed-ridden and death among the elderly, and falls need to be detected. However, it is very difficult to collect fall data to train a model to detect falls. The purpose of this study is to generate fall data using a Generative Adversarial Network and to evaluate whether falls can be detected using this data.