@inproceedings{915eca13273446f9852d85ef0f5ceca7,
title = "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%.",
keywords = "2D LiDAR, Elderly, Fall Detection System, K-Nearest Neighbor, Random Forest",
author = "Herti Miawarni and Sardjono, {Tri Arief} and Eko Setijadi and Wijayanti and Dwi Arraziqi and Gumelar, {Agustinus Bimo} and Purnomo, {Mauridhi Hery}",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2020 ; Conference date: 17-11-2020 Through 18-11-2020",
year = "2020",
month = nov,
day = "17",
doi = "10.1109/CENIM51130.2020.9298000",
language = "English",
series = "CENIM 2020 - Proceeding: International Conference on Computer Engineering, Network, and Intelligent Multimedia 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--5",
booktitle = "CENIM 2020 - Proceeding",
address = "United States",
}