Evidence map›Paper›PMID 37280388›Full record

ArticleScientific reports2023

Assessing falls in the elderly population using G-STRIDE foot-mounted inertial sensor.

Marta Neira Álvarez, Antonio R Jiménez Ruiz, Guillermo García-Villamil Neira, Elisabet Huertas-Hoyas, Maria Teresa Espinoza Cerda, Laura Pérez Delgado, Elena Reina Robles, Antonio J Del-Ama, Luisa Ruiz-Ruiz, Sara García-de-Villa and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

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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

11 authors.

Marta Neira Álvarez *Department of Geriatrics, Foundation for Research and Biomedical Innovation of the Infanta Sofía Hospital (HUIS), Madrid, 28702, Spain.
Antonio R Jiménez Ruiz *Spanish National Research Council, Centre for Automation and Robotics (CAR), CSIC-UPM, Arganda del Rey, 28500, Spain.
Guillermo García-Villamil Neira *Spanish National Research Council, Centre for Automation and Robotics (CAR), CSIC-UPM, Arganda del Rey, 28500, Spain.
Elisabet Huertas-Hoyas *Physical Therapy, Occupational Therapy, Rehabilitation and Physical Medicine Department, Rey Juan Carlos University, Mostoles, 28933, Spain.
Maria Teresa Espinoza CerdaGeriatrics's Department, Hospital Universitario de Getafe, Getafe, 28905, Spain.
Laura Pérez DelgadoPhysiotherapy Department, R. Gascon Baquero, Alcobendas, 28108, Spain.
Elena Reina RoblesPhysiotherapy Department, R. Torrelaguna, Torrelaguna, 28180, Spain.
Antonio J Del-Ama *School of Experimental Sciences and Technology, Rey Juan Carlos University, Mostoles, 28933, Spain.
Luisa Ruiz-Ruiz *Spanish National Research Council, Centre for Automation and Robotics (CAR), CSIC-UPM, Arganda del Rey, 28500, Spain.
Sara García-de-Villa *Spanish National Research Council, Centre for Automation and Robotics (CAR), CSIC-UPM, Arganda del Rey, 28500, Spain.
Cristina Rodriguez-Sanchez *School of Experimental Sciences and Technology, Rey Juan Carlos University, Mostoles, 28933, Spain. cristina.rodriguez.sanchez@urjc.es.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Falls are one of the main concerns in the elderly population due to their high prevalence and associated consequences. Guidelines for the management of the elder with falls are comprised of multidimensional assessments, especially gait and balance. Daily clinical practice needs for timely, effortless, and precise tools to assess gait. This work presents the clinical validation of the G-STRIDE system, a 6-axis inertial measurement unit (IMU) with onboard processing algorithms, that allows the calculation of walking-related metrics correlated with clinical markers of fall risk. A cross-sectional case-control study was conducted with 163 participants (falls and non-falls groups). All volunteers were assessed with clinical scales and conducted a 15-min walking test at a self-selected pace while wearing the G-STRIDE. G-STRIDE is a low-cost solution to facilitate the transfer to society and clinical evaluations. It is open hardware and flexible and, thus, has the advantage of providing runtime data processing. Walking descriptors were derived from the device, and a correlation analysis was conducted between walking and clinical variables. G-STRIDE allowed measuring walking parameters in non-restricted walking conditions (e.g. hallway). Walking parameters statistically discriminate between falls and non-falls groups. We found good/excellent estimation accuracy (ICC = 0.885; [Formula: see text]) for walking speed, showing good/excellent correlation between gait speed and several clinical variables. G-STRIDE can calculate walking-related metrics that allow for discrimination between falls and non-falls groups, which correlates with clinical indicators of fall risk. A preliminary fall-risk assessment based on the walking parameters was found to improve the Timed Up and Go test in the identification of fallers.

Indexed as

GaitPostural BalanceAgedCase-Control StudiesCross-Sectional StudiesHumansTime and Motion StudiesWalking

Identifiers

PMID37280388
PMCPMC10244449

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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.