Evidence map›Paper›PMID 34832180›Full record

ArticleMaterials (Basel, Switzerland)2021

The Influence of Electro-Conductive Compression Knits Wearing Conditions on Heating Characteristics.

Md Reazuddin Repon, Ginta Laureckiene, Daiva Mikucioniene

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 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

3 authors.

Md Reazuddin ReponDepartment of Production Engineering, Faculty of Mechanical Engineering and Design, Kaunas University of Technology, Studentų 56, LT-51424 Kaunas, Lithuania.ORCID 0000-0002-9984-7732
Ginta LaureckieneDepartment of Production Engineering, Faculty of Mechanical Engineering and Design, Kaunas University of Technology, Studentų 56, LT-51424 Kaunas, Lithuania.
Daiva MikucionieneDepartment of Production Engineering, Faculty of Mechanical Engineering and Design, Kaunas University of Technology, Studentų 56, LT-51424 Kaunas, Lithuania.ORCID 0000-0002-2219-2643

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Textile-based heaters have opened new opportunities for next-generation smart heating devices. This experiment presents electrically conductive textiles for heat generation in orthopaedic compression supports. The main goal was to investigate the influence of frequent washing and stretching on heat generation durability of constructed compression knitted structures. The silver coated polyamide yarns were used to knit a half-Milano rib structure containing elastomeric inlay-yarn. Dimensional stability of the knitted fabric and morphological changes of the silver coated electro-conductive yarns were investigated during every wash cycle. The results revealed that temperature becomes stable within two minutes for all investigated fabrics. The heat generation was found to be dependent on the stretching, mostly due to the changing surface area; and it should be considered during the development of heated compression knits. Washing negatively influences the heat-generating capacity on the fabric due to the surface damage caused by the mechanical and chemical interaction during washing. The higher number of silver-coated filaments in the electro-conductive yarn and the knitted structure, protecting the electro-conductive yarn from mechanical abrasion, may ensure higher durability of heating characteristics.

Indexed as

compressionconductive textilesheat generationorthopaedic supportstretchwashing

Identifiers

PMID34832180
PMCPMC8622006

What OpenQuestion holds

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LicenceCC BY
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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.