Evidence map›Paper›PMID 29596396›Full record

ArticleBiosensors2018

Smart Garment Fabrics to Enable Non-Contact Opto-Physiological Monitoring.

Dmitry Iakovlev, Sijung Hu, Harnani Hassan, Vincent Dwyer, Roya Ashayer-Soltani, Chris Hunt, Jinsong Shen

Abstract read
In one paragraph

Article in Biosensors, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
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

7 authors.

Dmitry IakovlevWolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough LE11 3TU, UK. D.Iakovlev@lboro.ac.uk.ORCID 0000-0002-1271-0849
Sijung HuWolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough LE11 3TU, UK. S.Hu@lboro.ac.uk.ORCID 0000-0002-9637-4730
Harnani HassanWolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough LE11 3TU, UK. H.Hassan@lboro.ac.uk.
Vincent DwyerWolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough LE11 3TU, UK. V.M.Dwyer@lboro.ac.uk.
Roya Ashayer-SoltaniNational Physical Laboratory, Hampton Road, Teddington TW11 0LW, UK. ashayerroya@gmail.com.
Chris HuntNational Physical Laboratory, Hampton Road, Teddington TW11 0LW, UK. chris.hunt@pireta.co.uk.ORCID 0000-0002-3395-2441
Jinsong ShenTextile Engineering and Materials Research Group, School of Design, De Montfort University, Leicester LE1 9BH, UK. jshen@dmu.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Imaging photoplethysmography (iPPG) is an emerging technology used to assess microcirculation and cardiovascular signs by collecting backscattered light from illuminated tissue using optical imaging sensors. The aim of this study was to study how effective smart garment fabrics could be capturing physiological signs in a non-contact mode. The present work demonstrates a feasible approach of, instead of using conventional high-power illumination sources, integrating a grid of surface-mounted light emitting diodes (LEDs) into cotton fabric to spotlight the region of interest (ROI). The green and the red LEDs (525 and 660 nm) placed on a small cotton substrate were used to locally illuminate palm skin in a dual-wavelength iPPG setup, where the backscattered light is transmitted to a remote image sensor through the garment fabric. The results show that the illuminations from both wavelength LEDs can be used to extract heart rate (HR) reaching an accuracy of 90% compared to a contact PPG probe. Stretching the fabric over the skin surface alters the morphology of iPPG signals, demonstrating a significantly higher pulsatile amplitude in both channels of green and red illuminations. The skin compression by the fabric could be potentially utilised to enhance the penetration of illumination into cutaneous microvascular beds. The outcome could lead a new avenue of non-contact opto-physiological monitoring and assessment with functional garment fabrics.

Indexed as

ClothingHumansImage Processing, Computer-AssistedMonitoring, PhysiologicSkin Physiological Phenomenaheart rate measurementimaging photoplethysmography (iPPG)light emitting diode (LED)motion artefactssignal processingsmart garment fabric

Identifiers

PMID29596396
PMCPMC6022879

What OpenQuestion holds

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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.