Evidence map›Paper›PMID 29498689›Full record

ArticleMaterials (Basel, Switzerland)2018

Novel Wearable Electrodes Based on Conductive Chitosan Fabrics and Their Application in Smart Garments.

Haiming Qin, Junrong Li, Beihai He, Jingbo Sun, Lingrui Li, Liying Qian

Open access · goldAbstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

7 citing papers in PubMed, 48 citations in OpenAlex.

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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

6 authors at 1 institution in 1 country.

Haiming QinState Key Laboratory of Pulp and Paper Engineering, South China University of Technology, Guangzhou 510640, China. qinhm1994@163.com.
Junrong LiState Key Laboratory of Pulp and Paper Engineering, South China University of Technology, Guangzhou 510640, China. lljrr@scut.edu.cn.
Beihai HeState Key Laboratory of Pulp and Paper Engineering, South China University of Technology, Guangzhou 510640, China. ppebhhe@scut.edu.cn.
Jingbo SunA Mu (Shenzhen) New Technology Co., Ltd., Shenzhen 518109, China. jbsun123@163.com.
Lingrui LiA Mu (Shenzhen) New Technology Co., Ltd., Shenzhen 518109, China. lingruili70@163.com.
Liying QianState Key Laboratory of Pulp and Paper Engineering, South China University of Technology, Guangzhou 510640, China. lyqian@scut.edu.cn.ORCID 0000-0003-4383-1122
South China University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Smart garments, which can capture electrocardiogram signals at any time or location, can alert others to the risk of heart attacks and prevent sudden cardiac death when people are sleeping, walking, or running. Novel wearable electrodes for smart garments based on conductive chitosan fabrics were fabricated by electroless plating of silver nanoparticles onto the surfaces of the fibers. The electrical resistance, which is related to the silver content of the composite fabrics, can be as low as 0.0332 ± 0.0041 Ω/sq due to the strong reactivity between amine groups and silver ions. After washing these fabrics eight times, the electrical resistance remained below 1 Ω/sq. The conductive chitosan fabrics were applied to smart garments as wearable electrodes to capture electrocardiogram signals of the human body in static state, jogging state, and running state, which showed good data acquisition ability and sensitivity.

Indexed as

chitosanelectroless platingsilver nanoparticlessmart garmentswearable electrodes

Identifiers

PMID29498689
PMCPMC5872949
OpenAlexW2790334639

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.