Evidence map›Paper›PMID 37993504›Full record

ArticleScientific reports2023

Validation of a modified visual analogue scale to measure user-perceived comfort of a lower-limb exoskeleton.

Mohammed Mohammed El Husaini, Axl Maberry, Anne E Martin

Abstract read
In one paragraph

Article in Scientific reports, 2023. 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

3 authors.

Mohammed Mohammed El HusainiDepartment of Mechanical Engineering, Pennsylvania State University, University Park, PA, 16802, USA.
Axl MaberryDepartment of Mechanical Engineering, Pennsylvania State University, University Park, PA, 16802, USA.
Anne E MartinDepartment of Mechanical Engineering, Pennsylvania State University, University Park, PA, 16802, USA. aem34@psu.edu.

Funding

National Science Foundation 1930430
6 · The paper itself

Abstract

User perceived exoskeleton comfort is likely important for device acceptance, but there is currently no validated instrument to measure it. The Visual Analogue Scale (VAS) is an existing tool to measure subjective human feedback by asking the user to mark a point on a line with each end of the line representing an opposing anchor statement. It can be modified to show the previous response, allowing the subject to directly indicate if the current condition is better or worse than the previous one. The goal of this study was to determine how well the modified VAS could measure user-perceived comfort as the exoskeleton control parameters were varied. To validate the survey, 14 healthy subjects walked in a pair of ankle exoskeletons with approximately ten distinct sets of control parameters tested in a prescribed order. Each set of control parameters was tested twice. After each trial, user-perceived comfort was measured using a two-question VAS survey. The repeatability coefficient was approximately 40 mm, similar to the total range of responses. The results were also inconsistent, with relative rankings between consecutive pairs of conditions matching for approximately 50% of comparisons. Thus, as tested, the VAS was not repeatable or consistent. It is possible that subject adaptation within the trial and over the course of the experiment may have impacted the results. Additional work is needed to develop a repeatable method to measure comfort and to determine how perceived comfort varies as subjects' gain exoskeleton experience.

Indexed as

Exoskeleton DeviceAnkleHumansLower ExtremityVisual Analog ScaleWalking

Identifiers

PMID37993504
PMCPMC10665473

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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.