Fall Detection System for Elderly based on 2D LiDAR: A Preliminary Study of Fall Incident and Activities of Daily Living (ADL) Detection

Abstract

FDS (Fall Detection System) is a technology that is very essential for the elderly, in order to immediately get help when the fall incident happens. This paper aims to build a FDS dedicated to the elderly. We propose 2D LiDAR as the main sensor in FDS. In this case, 2D LiDAR has the duty to obtain information data in a room. FDS is demanded to be able to distinguish between fall incidents and ADL (Activities of Daily Living). This paper presents trials on various positions of the human body that can be detected as fall incidents or ADL. The trials aim to produce a dataset that will later be processed using K-NN and RF as a fall detection algorithm. From the results of the trials, 2D LiDAR sensor data can describe two information as detection points. RF produces accuracy up to 94% and K-NN produces maximum accuracy of 100%.