Evidence map›Paper›PMID 35424805›Full record

ReviewRSC advances2022

Wearable microfluidic-based e-skin sweat sensors.

Humairah Tabasum, Nikita Gill, Rahul Mishra, Saifullah Lone

Open access · goldAbstract readReview
In one paragraph

Review in RSC advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
5.1field-weighted citation impact, top 3% 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

19 citing papers in PubMed, 65 citations in OpenAlex.

  1. Review
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  4. Article
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  7. 3D printing of micro-nano devices and their applications.Microsystems & nanoengineering · 2025
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  11. 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

4 authors at 1 institution in 1 country.

Humairah TabasumDepartment of Chemistry, National Institute of Technology (NIT) Srinagar J&K India 190006 saifullah.lone@nitsri.net +91-60005221589.
Nikita GillDepartment of Chemistry, National Institute of Technology (NIT) Srinagar J&K India 190006 saifullah.lone@nitsri.net +91-60005221589.
Rahul MishraDepartment of Chemistry, National Institute of Technology (NIT) Srinagar J&K India 190006 saifullah.lone@nitsri.net +91-60005221589.
Saifullah LoneDepartment of Chemistry, National Institute of Technology (NIT) Srinagar J&K India 190006 saifullah.lone@nitsri.net +91-60005221589.ORCID https://orcid.org/0000-0003-1026-7748
National Institute of Technology Srinagar · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electronic skins (e-skins) are soft (deformable and stretchable) state-of-the-art wearable devices that emulate the attributes of human skin and act as a Human-Machine Interface (HMI). Recent advances in e-skin for real-time detection of medical signals such as pulse, temperature, electromyogram (EMG), electroencephalogram (EEG), electrooculogram (EOG), electrocardiogram (ECG), and other bioelectric signals laid down an intelligent foundation for early prediction and diagnosis of diseases with a motive of reducing the risk of the ailment reaching to the end stage. In particular, sweat testing has been employed in diverse applications ranging from medical diagnosis of diabetes, cystic fibrosis, tuberculosis, blood pressure, and autonomic neuropathy to evaluating fluid and electrolyte balance in athletes. Typically, sweat testing techniques are done by trained experts and require off-body measurements, which prevent individuals from de-coding health issues quickly and independently. With the onset of soft electronics, wearable sweat sensors overcome this disadvantage

Identifiers

PMID35424805
PMCPMC8985157
OpenAlexW4223981716

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.