Evidence map›Paper›PMID 41294134›Full record

ArticleAdvanced healthcare materials2026

Highly Sensitive Oxidation-Resistant Degradable Janus Piezoresistive Electronic Skin for Sustainable Wearable Electronics.

Joon Kim, Mohammad Zarei, Deristisya Zahra, Yuhan Lee, Daegun Kim, Seung Goo Lee

Abstract read
In one paragraph

Article in Advanced healthcare materials, 2026. 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

6 authors.

Joon KimDepartment of Chemistry, University of Ulsan, Ulsan, Republic of Korea.
Mohammad ZareiDepartment of Chemistry, University of Ulsan, Ulsan, Republic of Korea.ORCID https://orcid.org/0000-0002-6351-5058
Deristisya ZahraDepartment of Chemistry, University of Ulsan, Ulsan, Republic of Korea.
Yuhan LeeDepartment of Anesthesiology, Perioperative and Pain Medicine, Center for Accelerated Medical Innovation, Center for Nanomedicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Daegun KimSchool of Chemical, Biological and Battery Engineering, Gachon University, Seongnam, Republic of Korea.ORCID https://orcid.org/0009-0006-1552-2663
Seung Goo LeeDepartment of Chemistry, University of Ulsan, Ulsan, Republic of Korea.ORCID https://orcid.org/0000-0002-6504-996X

Funding

Korea Electrotechnology Research Institute 23A01023Ministry of Education 2025-RISE-07-001Ministry of Education RS-2021-NR060113Ministry of Science and ICT, South Korea RS-2024-00456141Ministry of Science and ICT, South Korea RS-2025-25413074Ministry of Trade, Industry and Energy RS-2025-02413656
6 · The paper itself

Abstract

Wearable sensors enable fast and accurate monitoring of physiological signals, with broad applications in electronic skin (e-skin), biomedical engineering, and human-machine interfaces. However, their proliferation raises concerns about electronic waste. To mitigate this waste, biodegradable polymers have been used to develop eco-friendly sensors. However, various challenges persist, including low conductivity, limited sensitivity, and poor stability. We introduce a degradable cellulose paper e-skin coated with Ti

Indexed as

Wearable Electronic DevicesBridged Bicyclo Compounds, HeterocyclicCelluloseHumansOxidation-ReductionPolymersPolystyrenesSkinThiophenesTitaniumBridged Bicyclo Compounds, HeterocyclicCellulosepoly(3,4-ethylene dioxythiophene)poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate)PolymersPolystyrenesThiophenesTitaniumdegradabilityelectronic skinMXenePEDOT:PSSwearable electronics

Identifiers

PMID41294134
PMCPMC13015777

What OpenQuestion holds

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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.