Evidence map›Paper›PMID 34696131›Full record

ReviewSensors (Basel, Switzerland)2021

Detecting Fall Risk and Frailty in Elders with Inertial Motion Sensors: A Survey of Significant Gait Parameters.

Luisa Ruiz-Ruiz, Antonio R Jimenez, Guillermo Garcia-Villamil, Fernando Seco

Open access · goldAbstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 4 pooled it
18.4field-weighted citation impact, top 1% of its field
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

45 citing papers in PubMed, 4 syntheses or guidelines pooled it, 74 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

Luisa Ruiz-RuizCentre for Automation and Robotics (CAR), Consejo Superior de Investigaciones Científicas (CSIC)-UPM, Ctra. Campo Real km 0.2, La Poveda, Arganda del Rey, 28500 Madrid, Spain.ORCID 0000-0003-0316-7781
Antonio R JimenezCentre for Automation and Robotics (CAR), Consejo Superior de Investigaciones Científicas (CSIC)-UPM, Ctra. Campo Real km 0.2, La Poveda, Arganda del Rey, 28500 Madrid, Spain.ORCID 0000-0001-9771-1930
Guillermo Garcia-VillamilCentre for Automation and Robotics (CAR), Consejo Superior de Investigaciones Científicas (CSIC)-UPM, Ctra. Campo Real km 0.2, La Poveda, Arganda del Rey, 28500 Madrid, Spain.ORCID 0000-0002-3869-4410
Fernando SecoCentre for Automation and Robotics (CAR), Consejo Superior de Investigaciones Científicas (CSIC)-UPM, Ctra. Campo Real km 0.2, La Poveda, Arganda del Rey, 28500 Madrid, Spain.ORCID 0000-0002-2922-2710
Consejo Superior de Investigaciones Científicas · ES

Funding

European Union ECSEL-2019-2-RIASpanish Ministry of Science MICROCEBUS RTE2018-095168-B-C55
6 · The paper itself

Abstract

In the elderly, geriatric problems such as the risk of fall or frailty are a challenge for society. Patients with frailty present difficulties in walking and higher fall risk. The use of sensors for gait analysis allows the detection of objective parameters related to these pathologies and to make an early diagnosis. Inertial Measurement Units (IMUs) are wearables that, due to their accuracy, portability, and low price, are an excellent option to analyze human gait parameters in health-monitoring applications. Many relevant gait parameters (e.g., step time, walking speed) are used to assess motor, or even cognitive, health problems in the elderly, but we perceived that there is not a full consensus on which parameters are the most significant to estimate the risk of fall and the frailty state. In this work, we analyzed the different IMU-based gait parameters proposed in the literature to assess frailty state (robust, prefrail, or frail) or fall risk. The aim was to collect the most significant gait parameters, measured from inertial sensors, able to discriminate between patient groups and to highlight those parameters that are not relevant or for which there is controversy among the examined works. For this purpose, a literature review of the studies published in recent years was carried out; apart from 10 previous relevant reviews using inertial and other sensing technologies, a total of 22 specific studies giving statistical significance values were analyzed. The results showed that the most significant parameters are double-support time, gait speed, stride time, step time, and the number of steps/day or walking percentage/day, for frailty diagnosis. In the case of fall risk detection, parameters related to trunk stability or movements are the most relevant. Although these results are important, the total number of works found was limited and most of them performed the significance statistics on subsets of all possible gait parameters; this fact highlights the need for new frailty studies using a more complete set of gait parameters.

Indexed as

FrailtyAgedGaitGeriatric AssessmentHumansWalkingWalking Speedfrailtygait analysisinertial sensor

Identifiers

PMID34696131
PMCPMC8538337
OpenAlexW3206418279

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.