A Comparative Overview of Technological Advances in Fall Detection Systems for Elderly People

Population ageing is a growing global trend. It was estimated that by 2050, people over 60 years of age will represent 35% of the population in industrialised countries. This context demands strategies that incorporate technologies, such as fall detection systems, to facilitate remote monitoring and the automatic activation of risk alarms, thus improving quality of life. This article presents a scoping review of the leading technological solutions developed over the last decade for detecting falls in older adults, describing their principles of operation, effectiveness, advantages, limitations, and future trends in their development. The review was conducted under the PRISMA<sup>®</sup> methodology, including articles indexed in SCOPUS, ScienceDirect, Web of Science, PubMed, IEEE Xplore and Taylor & Francis. There is a predominance in the use of inertial systems that use accelerometers and gyroscopes, valued for their low cost and wide availability. However, those approaches that combine image analysis with artificial intelligence and machine learning algorithms show superiority in terms of accuracy and robustness. Similarly, progress has been made in the development of multisensory solutions based on IoT technologies, capable of integrating information from various sources, which optimises decision-making in real time.

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Publication Details

Journal
Sensors
Published
2025-12-05
DOI
https://doi.org/10.3390/s25247423
Primary Topic
Context-Aware Activity Recognition Systems
Type
article
Field-Weighted Citation Impact
0.00

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A Comparative Overview of Technological Advances in Fall Detection Systems for Elderly People

Sensors
Context-Aware Activity Recognition Systems
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A Comparative Overview of Technological Advances in Fall Detection Systems for Elderly People

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Abstract

Population ageing is a growing global trend. It was estimated that by 2050, people over 60 years of age will represent 35% of the population in industrialised countries. This context demands strategies that incorporate technologies, such as fall detection systems, to facilitate remote monitoring and the automatic activation of risk alarms, thus improving quality of life. This article presents a scoping review of the leading technological solutions developed over the last decade for detecting falls in older adults, describing their principles of operation, effectiveness, advantages, limitations, and future trends in their development. The review was conducted under the PRISMA<sup>®</sup> methodology, including articles indexed in SCOPUS, ScienceDirect, Web of Science, PubMed, IEEE Xplore and Taylor & Francis. There is a predominance in the use of inertial systems that use accelerometers and gyroscopes, valued for their low cost and wide availability. However, those approaches that combine image analysis with artificial intelligence and machine learning algorithms show superiority in terms of accuracy and robustness. Similarly, progress has been made in the development of multisensory solutions based on IoT technologies, capable of integrating information from various sources, which optimises decision-making in real time.

SensorsVol. 25(24)
Andrews University (US), Universidad de las Fuerzas Armadas ESPE (EC), Universidad de Alcalá (ES), Universidad Espíritu Santo (EC), Universidad Estatal Península de Santa Elena (EC), Universidad de Las Américas (EC), Servicio de Salud de Castilla La Mancha (ES), University of Castilla-La Mancha (ES)
Universidad de Especialidades Espíritu Santo, Universidad de Alcalá
Openalex Percentile: Top 40%
Context-Aware Activity Recognition Systems
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A Comparative Overview of Technological Advances in Fall Detection Systems for Elderly People · Sensors (2025) | TGRS Research Map | TGRS