Evidence map›Paper›PMID 40218570›Full record

ArticleSensors (Basel, Switzerland)2025

Development of a Body-Worn Textile-Based Strain Sensor: Application to Diabetic Foot Assessment.

Rory P Turnbull, Jenny Corser, Giorgio Orlando, Prabhuraj D Venkatraman, Irantzu Yoldi, Kathrine Bradbury, Neil D Reeves, Peter Culmer

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. 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

8 authors.

Rory P TurnbullSchool of Mechanical Engineering, Faculty of Engineering and Physical Sciences, University of Leeds, Leeds LS2 9JT, UK.ORCID 0000-0001-7334-0880
Jenny CorserCentre for Clinical and Community Applications of Health Psychology, Shakleton Building, Highfield Campus, University of Southampton, Southampton SO17 1BJ, UK.ORCID 0000-0003-1491-1801
Giorgio OrlandoDepartment of Sport and Exercise Sciences, Institute of Sport, Faculty of Science and Engineering, Manchester Metropolitan University, Manchester M15 6BX, UK.ORCID 0000-0001-6721-8248
Prabhuraj D VenkatramanManchester Fashion Institute, Faculty of Arts and Humanities, Manchester Metropolitan University, Manchester M15 6BH, UK.ORCID 0000-0003-4290-4510
Irantzu YoldiSchool of Health Sport And Bioscience, University of East London, London E16 2RD, UK.ORCID 0000-0001-8349-6272
Kathrine BradburyCentre for Clinical and Community Applications of Health Psychology, Shakleton Building, Highfield Campus, University of Southampton, Southampton SO17 1BJ, UK.ORCID 0000-0001-5513-7571
Neil D ReevesMedical School, Faculty of Health and Medicine, Lancaster University, Lancaster LA1 4YW, UK.ORCID 0000-0001-9213-4580
Peter CulmerSchool of Mechanical Engineering, Faculty of Engineering and Physical Sciences, University of Leeds, Leeds LS2 9JT, UK.ORCID 0000-0003-2867-0420

Funding

EPSRC EP/X001059/1, Digital Health: 'Socksess' 583 - Smart Sensing Socks For Monitoring Diabetic Feet And Preventing Ulceration
6 · The paper itself

Abstract

Diabetic Foot Ulcers (DFUs) are a significant health and economic burden, potentially leading to limb amputation, with a severe impact on a person's quality of life. During active movements like gait, the monitoring of shear has been suggested as an important factor for effective prevention of DFUs. It is proposed that, in textiles, strain can be measured as a proxy for shear stress at the skin. This paper presents the conceptualisation and development of a novel strain-sensing approach that can be unobtrusively integrated within sock textiles and worn within the shoe. Working with close clinical and patient engagement, a sensor specification was identified, and 12 load-sensing approaches for the prevention of DFU were evaluated. A lead concept using a conductive adhesive was selected for further development. The method was developed using a Lycra sample, before being translated onto a knitted 'sock' substrate. The resultant strain sensor can be integrated within mass-produced textiles fabricated using industrial knitting machines. A case-study was used to demonstrate a proof-of-concept version of the strain sensor, which changes resistance with applied mechanical strain. A range of static and dynamic laboratory testing was used to assess the sensor's performance, which demonstrated a resolution of 0.013 Ω across a range of 0-430 Ω and a range of interest of 0-20 Ω. In cyclic testing, the sensor exhibited a cyclic strain threshold of 6% and a sensitivity gradient of 0.3 ± 0.02, with a low dynamic drift of 0.039 to 0.045% of the total range. Overall, this work demonstrates a viable textile-based strain sensor capable of integration within worn knitted structures. It provides a promising first step towards developing a sock-based strain sensor for the prevention of DFU formation.

Indexed as

Biosensing TechniquesDiabetic FootTextilesWearable Electronic DevicesHumansShoesStress, Mechanicaldiabetic foot ulcersensorsshearwearables

Identifiers

PMID40218570
PMCPMC11990948

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LicenceCC BY
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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.