Risk Assessment System of Fall in the Elderly Using Artificial Intelligence and Cloud Computing

Abstract

This paper presents a Cloud-based online tool for helping health professionals to predict the risk of falling in the elderly by using the well-known Tinetti’s Test. This tool implements a Deep Learning-based method for allowing several Tinetti scale’s items to be automatically estimated, simply using a conventional camera or a recorded video. From these sources of information, patients’ skeleton is recognized and their movements analyzed by applying some geometric calculations, which provide an objective risk assessment. Results are represented as a set of plots easily interpretable by experts. Several tests, in a controlled environment, have been carried out to validate the accuracy and reliability of the system. Moreover, some tests have been also made with real elderly patients, whose results have been evaluated by therapists. The benefits of using such remote tool for assessing (objective) fall risk, from a usability point of view, are also highlighted.