Evidence map›Paper›PMID 37992071›Full record

ArticlePloS one2023

Remote assessment of pelvic kinematics during single leg squat using smartphone sensors: Between-day reliability and identification of acute changes in motor performance.

Valter Devecchi, Michelle Saunders, Sajni Galaiya, Millie Shaw, Alessio Gallina

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 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

5 authors.

Valter DevecchiSchool of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom.
Michelle SaundersSchool of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom.
Sajni GalaiyaSchool of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom.
Millie ShawSchool of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom.
Alessio GallinaSchool of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom.ORCID 0000-0003-1945-5518

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The biomechanical assessment of pelvic kinematics during a single leg squat (SLS) commonly relies on expensive equipment, which precludes its wider implementation in ecological settings. Smartphone sensors could represent an effective solution to objectively quantify pelvic kinematics remotely, but their measure properties need to be evaluated before advocating their use in practice. This study aimed to assess whether measures of pelvic kinematics collected remotely using smartphones during SLS are repeatable between days, and if changes in pelvic kinematics can be identified during an endurance task. Thirty-three healthy young adults were tested remotely on two different days using their own smartphones placed on the lumbosacral region. Pelvic orientation and acceleration were collected during three sets of seven SLS and an endurance task of twenty consecutive SLS. The intersession reliability was assessed using Intraclass Correlation Coefficient (ICC2,k), Standard Error of Measurement, and Minimal Detectable Change. T-tests were used to identify pelvic kinematics changes during the endurance task and to assess between-day bias. Measures of pelvic orientation and frequency features of the acceleration signals showed good to excellent reliability (multiple ICC2,k ≥ 0.79), and a shift of the power spectrum to lower frequencies on the second day (multiple p<0.05). The endurance task resulted in larger contralateral pelvic drop and rotation (multiple p<0.05) and increased spectral entropy (multiple p<0.05). Our findings demonstrate that reliable measures of pelvic kinematics can be obtained remotely using participants' smartphones during SLS. Smartphone sensors can also identify changes in motor control, such as contralateral pelvic drop during an endurance task.

Indexed as

LegSmartphoneBiomechanical PhenomenaHumansPostureReproducibility of ResultsYoung Adult

Identifiers

PMID37992071
PMCPMC10664960

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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.