Evidence map›Paper›PMID 37835987›Full record

ArticlePolymers2023

Advancing Smart Textiles: Structural Evolution of Knitted Piezoresistive Strain Sensors for Enabling Precise Motion Capture.

Mareen N Warncke, Carola H Böhmer, Carmen Sachse, Susanne Fischer, Eric Häntzsche, Andreas Nocke, Johannes Mersch, Chokri Cherif

Open access · goldAbstract read
In one paragraph

Article in Polymers, 2023. 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
1.2field-weighted citation impact, top 23% of its field
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, 11 citations in OpenAlex.

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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

8 authors at 1 institution in 1 country.

Mareen N WarnckeInstitute of Textile Machinery and High Performance Material Technology, TUD Dresden University of Technology, 01069 Dresden, Germany.ORCID 0000-0002-0100-5685
Carola H BöhmerInstitute of Textile Machinery and High Performance Material Technology, TUD Dresden University of Technology, 01069 Dresden, Germany.
Carmen SachseInstitute of Textile Machinery and High Performance Material Technology, TUD Dresden University of Technology, 01069 Dresden, Germany.
Susanne FischerInstitute of Textile Machinery and High Performance Material Technology, TUD Dresden University of Technology, 01069 Dresden, Germany.
Eric HäntzscheInstitute of Textile Machinery and High Performance Material Technology, TUD Dresden University of Technology, 01069 Dresden, Germany.ORCID 0000-0002-5906-8670
Andreas NockeInstitute of Textile Machinery and High Performance Material Technology, TUD Dresden University of Technology, 01069 Dresden, Germany.ORCID 0000-0001-7698-9095
Johannes MerschInstitute of Textile Machinery and High Performance Material Technology, TUD Dresden University of Technology, 01069 Dresden, Germany.ORCID 0000-0003-1058-4030
Chokri CherifInstitute of Textile Machinery and High Performance Material Technology, TUD Dresden University of Technology, 01069 Dresden, Germany.
Technische Universität Dresden · DE

Funding

Deutsche Forschungsgemeinschaft 390696704
6 · The paper itself

Abstract

Recently, there has been remarkable progress in the development of smart textiles, especially knitted strain sensors, to achieve reliable sensor signals. Stable and reliable electro-mechanical properties of sensors are essential for using textile-based sensors in medical applications. However, the challenges associated with significant hysteresis and low gauge factor (GF) values remain for using strain sensors for motion capture. To evaluate these issues, a comprehensive investigation of the cyclic electro-mechanical properties of weft-knitted strain sensors was conducted in the present study to develop a drift-free elastic strain sensor with a robust sensor signal for motion capture for medical devices. Several variables are considered in the study, including the variation of the basic knit pattern, the incorporation of the electrically conductive yarn, and the size of the strain sensor. The effectiveness and feasibility of the developed knitted strain sensors are demonstrated through an experimental evaluation, by determining the gauge factor, its nonlinearity, hysteresis, and drift. The developed knitted piezoresistive strain sensors have a GF of 2.4, a calculated drift of 50%, 12.5% hysteresis, and 0.3% nonlinearity in parts.

Indexed as

medical applicationsmotion monitoringsmart textilestextile strain sensorwearables

Identifiers

PMID37835987
PMCPMC10574850
OpenAlexW4387170311

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.