Evidence map›Paper›PMID 37482538›Full record

ArticleErgonomics2024

Evaluating adaptiveness of an active back exosuit for dynamic lifting and maximum range of motion.

D Adam Quirk, Jinwon Chung, Megan Applegate, Jason M Cherin, Diane M Dalton, Lou N Awad, Conor J Walsh

Abstract read
In one paragraph

Article in Ergonomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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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

7 authors.

D Adam QuirkJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Boston, MA, USA.
Jinwon ChungJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Boston, MA, USA.
Megan ApplegateJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Boston, MA, USA.
Jason M CherinJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Boston, MA, USA.
Diane M DaltonCollege of Health & Rehabilitation Sciences: Sargent College, Boston University, Boston, MA, USA.
Lou N AwadCollege of Health & Rehabilitation Sciences: Sargent College, Boston University, Boston, MA, USA.
Conor J WalshJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Boston, MA, USA.

Funding

Development, Evaluation and Translation of Robotic Apparel for Alleviating Low Back PainUH3AR076731 · NIAMS · HARVARD UNIVERSITY · PI WALSH, CONOR · 2021 to 2021
$2.1M
Development, Evaluation and Translation of Robotic Apparel for Alleviating Low Back PainUH2AR076731 · NIAMS · HARVARD UNIVERSITY · PI WALSH, CONOR · 2019 to 2019
$1.1M
NIAMS NIH HHS UH2 AR076731NIAMS NIH HHS UH3 AR076731
6 · The paper itself

Abstract

Back exosuits deliver mechanical assistance to reduce the risk of back injury, however, minimising restriction is critical for adoption. We developed the adaptive impedance controller to minimise restriction while maintaining assistance by modulating impedance based on the user's movement direction and nonlinear sine curves. The objective of this study was to compare active assistance, delivered by a back exosuit via our adaptive impedance controller, to three levels of assistance from passive elastics. Fifteen participants completed five experimental blocks (4 exosuits and 1 no-suit) consisting of a maximum flexion and a constrained lifting task. While a higher stiffness elastic reduced back extensor muscle activity by 13%, it restricted maximum range of motion (RoM) by 13°. The adaptive impedance approach did not restrict RoM while reducing back extensor muscle activity by 15%, when lifting. This study highlights an adaptive impedance approach might improve usability by circumventing the assistance-restriction trade-off inherent to passive approaches.

Indexed as

Exoskeleton DeviceRoboticsBiomechanical PhenomenaHumansLiftingMuscle, SkeletalRange of Motion, ArticularbiomechanicselectromyographyexosuitLow back painwearable robotics

Identifiers

PMID37482538
PMCPMC10803634

What OpenQuestion holds

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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.