research-article

Fall Detection Application for the Elderly in the Family Heroes System

Authors:

Moustafa Fayad,

Ahmed Mostefaoui,

Salima BenbernouAuthors Info & Claims

MobiWac '19: Proceedings of the 17th ACM International Symposium on Mobility Management and Wireless Access

Pages 17 - 23

https://doi.org/10.1145/3345770.3356738

Published: 25 November 2019 Publication History

Abstract

Population aging is a considerable challenge for a global society. Indeed, it raises several concerns and gives more or fewer alarmist projections of social-economic problems, that it could engender. Technological solutions to address the issue of aging are now a necessity. Systems based on these solutions combine wearable and ambient sensors, processing software, and user interfaces. Their objective is to monitor dependent and frail elderly people in institutions and/or home. The healthcare monitoring for elderly people is a growing application axis thanks to the massive technology development. Family Heroes is a new concept of an automatic healthcare monitoring system based on the Internet of things. In this paper, we will present the global architecture of our system and the preliminary results of the fall detection using only the Kinect V2. The results show the system, in the first stage of validation, detect 70% of falls using a novel approach threshold-based on the variation of angels of the upper body during the movement cycle.

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Cited By

Fayad MHachani MGhoumid KMostefaoui AChouali SPicaud FHerlem GLajoie IYahiaoui R(2023)Fall Detection Approaches for Monitoring Elderly HealthCare Using Kinect Technology: A SurveyApplied Sciences10.3390/app13181035213:18(10352)Online publication date: 15-Sep-2023
https://doi.org/10.3390/app131810352
Guamán-Egas JCastro-Martin A(2023)Fall Detection with Artificial Intelligence and IoT Health Monitoring System2023 IEEE Seventh Ecuador Technical Chapters Meeting (ECTM)10.1109/ETCM58927.2023.10308997(1-6)Online publication date: 10-Oct-2023
https://doi.org/10.1109/ETCM58927.2023.10308997
Matayong SJetwanna KChoksuchat CChoosawang STrakulmaykee NLimsuwan SInthanuchit K(2023)IoT-based systems and applications for elderly healthcare: a systematic reviewUniversal Access in the Information Society10.1007/s10209-023-01055-1Online publication date: 2-Nov-2023
https://doi.org/10.1007/s10209-023-01055-1
Show More Cited By

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Fall Detection Application for the Elderly in the Family Heroes System

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cover image ACM Conferences

MobiWac '19: Proceedings of the 17th ACM International Symposium on Mobility Management and Wireless Access

November 2019

125 pages

ISBN:9781450369053

DOI:10.1145/3345770

Program Chairs:
Frank Y. Li
Universitat Politècnica de Catalunya, Spain
,
Rodolfo W. L. Coutinho
University of Ottawa, Canada

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 25 November 2019

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MSWiM '19: 22nd Int'l ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

November 25 - 29, 2019

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Overall Acceptance Rate 83 of 272 submissions, 31%

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Cited By

Fayad MHachani MGhoumid KMostefaoui AChouali SPicaud FHerlem GLajoie IYahiaoui R(2023)Fall Detection Approaches for Monitoring Elderly HealthCare Using Kinect Technology: A SurveyApplied Sciences10.3390/app13181035213:18(10352)Online publication date: 15-Sep-2023
https://doi.org/10.3390/app131810352
Guamán-Egas JCastro-Martin A(2023)Fall Detection with Artificial Intelligence and IoT Health Monitoring System2023 IEEE Seventh Ecuador Technical Chapters Meeting (ECTM)10.1109/ETCM58927.2023.10308997(1-6)Online publication date: 10-Oct-2023
https://doi.org/10.1109/ETCM58927.2023.10308997
Matayong SJetwanna KChoksuchat CChoosawang STrakulmaykee NLimsuwan SInthanuchit K(2023)IoT-based systems and applications for elderly healthcare: a systematic reviewUniversal Access in the Information Society10.1007/s10209-023-01055-1Online publication date: 2-Nov-2023
https://doi.org/10.1007/s10209-023-01055-1
Fayad MHachani MMostefaoui AChouali SYahiaoui RLi FCoutinho R(2022)Elderly Fall Detection: A Lightweight Kinect Based Deep Learning ApproachProceedings of the 20th ACM International Symposium on Mobility Management and Wireless Access10.1145/3551660.3560911(89-95)Online publication date: 24-Oct-2022
https://dl.acm.org/doi/10.1145/3551660.3560911
Fayad MMostefaoui AChouali SBenbernou S(2022)Toward a design model-oriented methodology to ensure QoS of a cyber-physical healthcare systemComputing10.1007/s00607-022-01058-5104:7(1615-1641)Online publication date: 23-Feb-2022
https://doi.org/10.1007/s00607-022-01058-5
Fayad MMostefaoui AChouali SBenbernou SLi CMostefaoui A(2020)Model-Oriented Methodology for Developing a Social Based Healthcare SystemProceedings of the 16th ACM Symposium on QoS and Security for Wireless and Mobile Networks10.1145/3416013.3426452(101-107)Online publication date: 16-Nov-2020
https://dl.acm.org/doi/10.1145/3416013.3426452
Stevanoska SDavcev DJovanovska EMitreski KLi FZomaya ACoutinho R(2020)IoT--Based System for Real-time Monitoring and Insect Detection in VineyardsProceedings of the 18th ACM Symposium on Mobility Management and Wireless Access10.1145/3416012.3424634(133-136)Online publication date: 16-Nov-2020
https://dl.acm.org/doi/10.1145/3416012.3424634
Finandhita A(2020)Development of Software Quality Assessment Model for Mobile-based Elderly Fall Detection SoftwareIOP Conference Series: Materials Science and Engineering10.1088/1757-899X/879/1/012088879(012088)Online publication date: 7-Aug-2020
https://doi.org/10.1088/1757-899X/879/1/012088

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