Evidence map›Paper›PMID 39580572›Full record

ArticleScientific reports2024

A flexible-spoke non-pneumatic tyre for manual wheelchairs.

Otis Wyatt, Panagiotis Chatzistergos, Nachiappan Chockalingam, Evangelia Ganniari-Papageorgiou

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Otis WyattCentre for Biomechanics and Rehabilitation Technologies, Staffordshire University, Stoke-On-Trent, UK.
Panagiotis ChatzistergosSchool of Science and Engineering, University of Dundee, Nethergate, Dundee, DD1 4HN, Scotland. pchatzistergos@gmail.com.
Nachiappan ChockalingamCentre for Biomechanics and Rehabilitation Technologies, Staffordshire University, Stoke-On-Trent, UK.
Evangelia Ganniari-PapageorgiouWarwick Manufacturing Group, University of Warwick, Coventry, UK.

Funding

Engineering and Physical Sciences Research Council EP/W00717/1
6 · The paper itself

Abstract

This study combines laboratory testing with computer modelling to demonstrate, for the first time, the applicability of flexible-spoke non-pneumatic tyre (FS-NPT) technology in wheelchairs. Like existing solid non-pneumatic tyres, FS-NPTs are puncture-proof and will reduce the burden of tyre maintenance. Unlike existing solid tyres, FS-NPT performance is based on the properties of flexible structures (spokes), such as honeycombs, which can deform to offer superior cushioning and return to their original shape upon unloading. The results presented here indicate that the geometry of these spokes can be tuned to replicate the vertical stiffness of existing pneumatic tyres commonly used in wheelchairs while achieving higher rotational stiffness and reduced mass. Vertical stiffness is directly linked to user comfort while increased rotational stiffness is associated with increased wheeling efficiency. Results also indicate that FS-NPTs can change their stiffness to become softer under increased loading. This unique characteristic could enable the development of tyres that are relatively stiff during wheeling (for better wheeling efficiency), and softer during impact loads for better cushioning (e.g. during pavement dismount). The demonstrated capacity for stiffness tuning could enable personalising wheelchair tyres to meet the specific needs of individual users.

Indexed as

Equipment DesignWheelchairsComputer SimulationHumansFinite element analysisHoneycombManual wheelchairsNon-pneumatic tyres

Identifiers

PMID39580572
PMCPMC11585612

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.