Evidence map›Paper›PMID 32384664›Full record

ArticleSensors (Basel, Switzerland)2020

A Subject-Specific Approach to Detect Fatigue-Related Changes in Spine Motion Using Wearable Sensors.

Victor C H Chan, Shawn M Beaudette, Kenneth B Smale, Kristen H E Beange, Ryan B Graham

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 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.

Victor C H ChanSchool of Human Kinetics, University of Ottawa, 200 Lees Avenue, Ottawa, ON K1S 5L5, Canada.ORCID 0000-0002-7166-5822
Shawn M BeaudetteSchool of Human Kinetics, University of Ottawa, 200 Lees Avenue, Ottawa, ON K1S 5L5, Canada.ORCID 0000-0002-8427-3959
Kenneth B SmaleSchool of Human Kinetics, University of Ottawa, 200 Lees Avenue, Ottawa, ON K1S 5L5, Canada.
Kristen H E BeangeSchool of Human Kinetics, University of Ottawa, 200 Lees Avenue, Ottawa, ON K1S 5L5, Canada.
Ryan B GrahamSchool of Human Kinetics, University of Ottawa, 200 Lees Avenue, Ottawa, ON K1S 5L5, Canada.ORCID 0000-0001-7502-8065

Funding

Natural Sciences and Engineering Research Council of Canada RGPIN-2014-05560Ontario Early Researcher Award ER17-13-007
6 · The paper itself

Abstract

An objective method to detect muscle fatigue-related kinematic changes may reduce workplace injuries. However, heterogeneous responses to muscle fatigue suggest that subject-specific analyses are necessary. The objectives of this study were to: (1) determine if wearable inertial measurement units (IMUs) could be used in conjunction with a spine motion composite index (SMCI) to quantify subject-specific changes in spine kinematics during a repetitive spine flexion-extension (FE) task; and (2) determine if the SMCI was correlated with measures of global trunk muscle fatigue. Spine kinematics were measured using wearable IMUs in 10 healthy adults during a baseline set followed by 10 sets of 50 spine FE repetitions. After each set, two fatigue measures were collected: perceived level of fatigue using a visual analogue scale (VAS), and maximal lift strength. SMCIs incorporating 10 kinematic variables from 2 IMUs (pelvis and T8 vertebrae) were calculated and used to quantify subject-specific changes in movement. A main effect of set was observed (

Indexed as

FatigueSpineWearable Electronic DevicesAdultBiomechanical PhenomenaFemaleHumansMaleMuscle FatigueRange of Motion, Articularcomposite indexinertial measurement unitsmuscle fatiguespinesubject-specific

Identifiers

PMID32384664
PMCPMC7249110

What OpenQuestion holds

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LicenceCC BY
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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.