Evidence map›Paper›PMID 33918394›Full record

ArticleSensors (Basel, Switzerland)2021

Automatically Determining Lumbar Load during Physically Demanding Work: A Validation Study.

Charlotte Christina Roossien, Christian Theodoor Maria Baten, Mitchel Willem Pieter van der Waard, Michiel Felix Reneman, Gijsbertus Jacob Verkerke

Abstract read
In one paragraph

Article 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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
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.

Charlotte Christina RoossienDepartment of Rehabilitation Medicine, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands.ORCID 0000-0001-6489-6967
Christian Theodoor Maria BatenDepartment Rehabilitation Technology, Roessingh Research and Development, Roessinghsbleekweg 33b, 7522 AH Enschede, The Netherlands.
Mitchel Willem Pieter van der WaardDepartment Rehabilitation Technology, Roessingh Research and Development, Roessinghsbleekweg 33b, 7522 AH Enschede, The Netherlands.
Michiel Felix RenemanDepartment of Rehabilitation Medicine, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands.
Gijsbertus Jacob VerkerkeDepartment of Rehabilitation Medicine, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands.ORCID 0000-0003-3533-2446

Funding

European Regional Development Fund T-306, 2013
6 · The paper itself

Abstract

A sensor-based system using inertial magnetic measurement units and surface electromyography is suitable for objectively and automatically monitoring the lumbar load during physically demanding work. The validity and usability of this system in the uncontrolled real-life working environment of physically active workers are still unknown. The objective of this study was to test the discriminant validity of an artificial neural network-based method for load assessment during actual work. Nine physically active workers performed work-related tasks while wearing the sensor system. The main measure representing lumbar load was the net moment around the L5/S1 intervertebral body, estimated using a method that was based on artificial neural network and perceived workload. The mean differences (MDs) were tested using a paired

Indexed as

Lumbar VertebraeElectromyographyHumansinertial motion unitslow back painphysically active workers

Identifiers

PMID33918394
PMCPMC8038224

What OpenQuestion holds

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Registered trials

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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.