Evidence map›Paper›PMID 35783456›Full record

ReviewAPL bioengineering2022

Recent progress in electrospun nanomaterials for wearables.

Riddha Das, Wenxin Zeng, Cihan Asci, Ruben Del-Rio-Ruiz, Sameer Sonkusale

Abstract readReview
In one paragraph

Review in APL bioengineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
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  4. Review
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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

5 authors.

Riddha DasDepartment of Electrical and Computer Engineering, Tufts University, 200 Boston Avenue, Medford, Massachusetts 02155, USA.
Wenxin ZengDepartment of Electrical and Computer Engineering, Tufts University, 200 Boston Avenue, Medford, Massachusetts 02155, USA.
Cihan AsciDepartment of Electrical and Computer Engineering, Tufts University, 200 Boston Avenue, Medford, Massachusetts 02155, USA.
Ruben Del-Rio-RuizDepartment of Electrical and Computer Engineering, Tufts University, 200 Boston Avenue, Medford, Massachusetts 02155, USA.
Sameer SonkusaleDepartment of Electrical and Computer Engineering, Tufts University, 200 Boston Avenue, Medford, Massachusetts 02155, USA.ORCID https://orcid.org/0000-0003-3579-910X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wearables have garnered significant attention in recent years not only as consumer electronics for entertainment, communications, and commerce but also for real-time continuous health monitoring. This has been spurred by advances in flexible sensors, transistors, energy storage, and harvesting devices to replace the traditional, bulky, and rigid electronic devices. However, engineering smart wearables that can seamlessly integrate with the human body is a daunting task. Some of the key material attributes that are challenging to meet are skin conformability, breathability, and biocompatibility while providing tunability of its mechanical, electrical, and chemical properties. Electrospinning has emerged as a versatile platform that can potentially address these challenges by fabricating nanofibers with tunable properties from a polymer base. In this article, we review advances in wearable electronic devices and systems that are developed using electrospinning. We cover various applications in multiple fields including healthcare, biomedicine, and energy. We review the ability to tune the electrical, physiochemical, and mechanical properties of the nanofibers underlying these applications and illustrate strategies that enable integration of these nanofibers with human skin.

Identifiers

PMID35783456
PMCPMC9249212

What OpenQuestion holds

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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.