Evidence map›Paper›PMID 33762793›Full record

ArticleInternational journal of industrial ergonomics2020

A Narrative Review on Contemporary and Emerging Uses of Inertial Sensing in Occupational Ergonomics.

Sol Lim, Clive D'Souza

Abstract read
In one paragraph

Article in International journal of industrial ergonomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 4 pooled it
–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

32 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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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

2 authors.

Sol LimDepartment of Systems and Industrial Engineering, University of Arizona, Tucson, Arizona.
Clive D'SouzaCenter for Ergonomics, Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan.

Funding

ACL HHS 90IF0094
6 · The paper itself

Abstract

Accurate, reliable, and cost-effective quantification of real-time biomechanical exposures in occupational settings remains an enduring pursuit in ergonomics. Miniaturized, wireless, body-worn inertial sensors offer opportunities to directly measure vast and personalized kinematics data in both laboratory and applied settings. This review investigated the contemporary and emerging uses of wearable inertial sensing technology in occupational ergonomics research related to biomechanical exposure assessment in physical work. A review and narrative synthesis of 78 peer-reviewed studies was conducted. A conceptual framework was used for scoping and synthesizing the reviewed scientific literature. Review findings help to contextualize contributions of this emerging technology to the broader goals of reducing work-relevant musculoskeletal trauma disorders. The review made evident that despite the growing interest in wearable inertial sensing technologies for ergonomics research, its use in applied settings still lags. The review also identified differences in sensor attachment locations and methods and measures for calibration and validation, and inconsistent criteria for reporting and assessing biomechanical exposures even across studies with similar objectives. Emerging applications include combining inertial sensing with predictive modeling for obtaining cumulative exposure data, and providing real-time feedback about biomechanical work demands. The manuscript concludes with research directions for enabling inertial sensing technologies as a tool for online biomechanical exposure assessment and feedback, which has particular appeal in non-repetitive work settings.

Indexed as

accelerometersergonomicsexposure assessmentinertial sensorswearable sensors

Identifiers

PMID33762793
PMCPMC7985982

What OpenQuestion holds

Textmetadata
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.