Evidence map›Paper›PMID 41053194›Full record

ArticleScientific reports2025

A scalable, and tunable braided yarn for micro and macro physiological sensing.

Md Abdullah Al Rumon, Jim Owens, Vignesh Ravichandran, Dhaval Solanki, Kunal Mankodiya

Abstract read
In one paragraph

Article in Scientific reports, 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

5 authors.

Md Abdullah Al RumonDepartment of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, USA. mrumon@uri.edu.
Jim OwensNautilus Defense, Pawtucket, RI, USA.
Vignesh RavichandranDepartment of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, USA.
Dhaval SolankiDepartment of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, USA.
Kunal MankodiyaDepartment of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, USA.

Funding

National Science Foundation 2139724Rhode Island Commerce Corporation Innovation Voucher
6 · The paper itself

Abstract

Future wearables envision a fully integrated sensing system capable of monitoring vital signs and biomechanics in daily environments. Currently, achieving a balance between imperceptible sensing and seamless integration poses a significant challenge to developing durable and personalized wearable solutions. In this article, we report an ultra-thin, miniaturized, capacitive braided composite yarn (CBCY) that is scalable and tunable for both micro and macro sensing applications. By leveraging advanced braiding and winding techniques, we created a sensor that is conformable, robust, and can be seamlessly integrated into the flexible surface. To elucidate the sensor, we characterized its capabilities and provided comprehensive guidelines for diverse use cases. Additionally, to evaluate the sensor performance, two wearable applications are designed to monitor human respiration (micro-sensing) and elbow movements (macro-sensing). Our braided yarn offers a new array of features for wearable designers, ensuring imperceptible comfort and the unification of sensors and electronics for future smart textile applications.

Indexed as

Wearable Electronic DevicesEquipment DesignHumansMonitoring, PhysiologicTextiles

Identifiers

PMID41053194
PMCPMC12500989

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.