Evidence map›Paper›PMID 34886459›Full record

SynthesisInternational journal of environmental research and public health2021

Gait Assessment Using Wearable Sensor-Based Devices in People Living with Dementia: A Systematic Review.

Yehuda Weizman, Oren Tirosh, Jeanie Beh, Franz Konstantin Fuss, Sonja Pedell

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 3 pooled it
4.9field-weighted citation impact, top 5% 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

11 citing papers in PubMed, 3 syntheses or guidelines pooled it, 22 citations in OpenAlex.

  1. Pooled it
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  6. Review
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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

5 authors at 2 institutions in 2 countries.

Yehuda WeizmanDepartment of Health and Medical Science, School of Health Science, Swinburne University of Technology, Hawthorn, VIC 3122, Australia.ORCID 0000-0001-9736-8300
Oren TiroshDepartment of Health and Medical Science, School of Health Science, Swinburne University of Technology, Hawthorn, VIC 3122, Australia.ORCID 0000-0002-2281-6399
Jeanie BehCentre for Design Innovation, Swinburne University of Technology, Hawthorn, VIC 3122, Australia.
Franz Konstantin FussChair of Biomechanics, Faculty of Engineering Science, University of Bayreuth, D-95440 Bayreuth, Germany.
Sonja PedellCentre for Design Innovation, Swinburne University of Technology, Hawthorn, VIC 3122, Australia.
Swinburne University of Technology · AUUniversity of Bayreuth · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ability of people living with dementia to walk independently is a key contributor to their overall well-being and autonomy. For this reason, understanding the relationship between dementia and gait is significant. With rapidly emerging developments in technology, wearable devices offer a portable and affordable alternative for healthcare experts to objectively estimate kinematic parameters with great accuracy. This systematic review aims to provide an updated overview and explore the opportunities in the current research on wearable sensors for gait analysis in adults over 60 living with dementia. A systematic search was conducted in the following scientific databases: PubMed, Cochrane Library, and IEEE Xplore. The targeted search identified 1992 articles that were potentially eligible for inclusion, but, following title, abstract, and full-text review, only 6 articles were deemed to meet the inclusion criteria. Most studies performed adequately on measures of reporting, in and out of a laboratory environment, and found that sensor-derived data are successful in their respective objectives and goals. Nevertheless, we believe that additional studies utilizing standardized protocols should be conducted in the future to explore the impact and usefulness of wearable devices in gait-related characteristics such as fall prognosis and early diagnosis in people living with dementia.

Indexed as

DementiaWearable Electronic DevicesAdultGaitGait AnalysisHumansWalkingdementiafallsgaitgait assessmentinertial measurement unitsensorswearable devices

Identifiers

PMID34886459
PMCPMC8656771
OpenAlexW3217301049

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.