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An intelligent video-monitoring system to detect falls: a proof of concept

Nolwenn Lapierre (Université de Montréal, Montreal, Canada)
Jean Meunier (Université de Montréal, Montreal, Canada)
Alain St-Arnaud (CIUSSS de l’Est-de-l’Île-de-Montréal, Montreal, Canada)
Jacqueline Rousseau (Université de Montréal, Montreal, Canada)

Journal of Enabling Technologies

ISSN: 2398-6263

Article publication date: 7 November 2018

Issue publication date: 28 November 2018

129

Abstract

Purpose

To face the challenges raised by the high incidence of falls among older adults, the intelligent video-monitoring system (IVS), a fall detection system that respects privacy, was developed. Most fall detection systems are tested only in laboratories. The purpose of this paper is to test the IVS in a simulation context (apartment-laboratory), then at home.

Design/methodology/approach

This study is a proof of concept including two phases: a simulation study to test the IVS in an apartment-laboratory (29 scenarios of activities including falls); and a 28-day pre-test at home with two young occupants. The IVS’s sensitivity (Se), specificity (Sp), accuracy (A) and error rate (E) in the apartment-laboratory were calculated, and functioning at home was documented in a logbook.

Findings

For phase 1, results are: Se =91.67 per cent, Sp =99.02 per cent, A=98.25 per cent, E=1.75. For phase 2, the IVS triggered four false alarms and some technical dysfunctions appeared (e.g. computer screen never turning off) that are easily overcome.

Practical implications

Results show the IVS’s efficacy at automatically detecting falls at home. Potential issues related to future installation in older adults’ homes were identified. This proof of concept led to recommendations about the installation and calibration of a camera-based fall detection system.

Originality/value

This paper highlights the potentialities of a camera-based fall detection system in real-world contexts and supports the use of the IVS to help older adults age in place.

Keywords

Acknowledgements

This project was funded by the Research Centre of the Institut universitaire de gériatrie de Montréal (CRIUGM) #2017–18 and the Fonds de Recherche du Québec Société et Culture (FRQSC) #SE-2018-205874. The first author (Doctoral Candidate) received scholarships from the Faculté des études supérieures et postdoctorales of the Université de Montréal and the Research Centre of the Institut universitaire de gériatrie de Montréal (CRIUGM) in partnership with the research network AGE-WELL.

Citation

Lapierre, N., Meunier, J., St-Arnaud, A. and Rousseau, J. (2018), "An intelligent video-monitoring system to detect falls: a proof of concept", Journal of Enabling Technologies, Vol. 12 No. 4, pp. 155-168. https://doi.org/10.1108/JET-04-2018-0022

Publisher

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Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited

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