Evidence map›Paper›PMID 41471419›Full record

ArticleSensors (Basel, Switzerland)2025

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

Omar Flor-Unda, Rafael Arcos-Reina, Cristina Estrella-Caicedo, Carlos Toapanta, Freddy Villao, Héctor Palacios-Cabrera, Susana Nunez-Nagy, Bernardo Alarcos

Abstract readComparative StudyScoping Review
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Omar Flor-UndaIngeniería Industrial, Facultad de Ingeniería y Ciencias Aplicadas, Universidad de las Américas, Quito 170125, Ecuador.ORCID 0000-0002-3455-5982
Rafael Arcos-ReinaEscuela de Fisioterapia, Facultad de Ciencias de la Salud, Universidad de Las Américas, Quito 170125, Ecuador.ORCID 0009-0001-8686-9668
Cristina Estrella-CaicedoIngeniería en Telecomunicaciones, Departamento de Eléctrica, Electrónica y Telecomunicaciones, Universidad de las Fuerzas Armadas, Sangolquí 171103, Ecuador.
Carlos ToapantaFacultad de Ciencias Sociales y la Salud, Universidad Estatal Península de Santa Elena, La Libertad 240204, Ecuador.
Freddy VillaoFacultad de Ciencias Sociales y la Salud, Universidad Estatal Península de Santa Elena, La Libertad 240204, Ecuador.ORCID 0000-0002-9114-9606
Héctor Palacios-CabreraFacultad de Ciencias de la Salud, Universidad Espíritu Santo, Samborondón 092301, Ecuador.ORCID 0000-0003-2179-8499
Susana Nunez-NagyPhysiotherapy Unit, Department of Nursing and Physiotherapy, Faculty of Medicine and Health Sciences, University of Alcalá, 28805 Alcalá de Henares, Spain.ORCID 0000-0001-9206-6725
Bernardo AlarcosPolytechnic School, University of Alcalá, 28805 Alcalá de Henares, Spain.ORCID 0000-0002-4455-5716

Funding

Universidad de las Américas 504.A.XIV.24
6 · The paper itself

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

Indexed as

Accidental FallsMonitoring, AmbulatoryAccelerometryAgedAged, 80 and overAlgorithmsArtificial IntelligenceHumansMachine LearningMiddle AgedQuality of Lifeartificial intelligenceelderlyfall detectioninertial measurement unitsmachine learningwearable sensors

Identifiers

PMID41471419
PMCPMC12737185

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.