Evidence map›Paper›PMID 30925752›Full record

ArticleSensors (Basel, Switzerland)2019

Design of a Wearable 12-Lead Noncontact Electrocardiogram Monitoring System.

Chien-Chin Hsu, Bor-Shing Lin, Ke-Yi He, Bor-Shyh Lin

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
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  6. Robustness of electrocardiogram signal quality indices.Journal of the Royal Society, Interface · 2022
    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

4 authors.

Chien-Chin HsuDepartment of Emergency Medicine, Chi Mei Medical Center, Tainan 710, Taiwan. nych2525@gmail.com.
Bor-Shing LinDepartment of Computer Science and Information Engineering, National Taipei University, New Taipei 23741, Taiwan. bslin@mail.ntpu.edu.tw.ORCID 0000-0003-0498-3190
Ke-Yi HeInstitute of Imaging and Biomedical Photonics, National Chiao Tung University, Tainan 711, Taiwan. nctukeyiho@gmail.com.
Bor-Shyh LinInstitute of Imaging and Biomedical Photonics, National Chiao Tung University, Tainan 711, Taiwan. borshyhlin@gmail.com.ORCID 0000-0002-8653-2571

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A standard 12-lead electrocardiogram (ECG) is an important tool in the diagnosis of heart diseases. Here, Ag/AgCl electrodes with conductive gels are usually used in a 12-lead ECG system to access biopotentials. However, using Ag/AgCl electrodes with conductive gels might be inconvenient in a prehospital setting. In previous studies, several dry electrodes have been developed to improve this issue. However, these dry electrodes have contact with the skin directly, and they might be still unsuitable for patients with wounds. In this study, a wearable 12-lead electrocardiogram monitoring system was proposed to improve the above issue. Here, novel noncontact electrodes were also designed to access biopotentials without contact with the skin directly. Moreover, by using the mechanical design, this system allows the user to easily wear and take off the device and to adjust the locations of the noncontact electrodes. The experimental results showed that the proposed system could exactly provide a good ECG signal quality even while walking and could detect the ECG features of the patients with myocardial ischemia, installation pacemaker, and ventricular premature contraction.

Indexed as

Wearable Electronic DevicesElectrocardiographyElectrodesEquipment DesignHeart RateHumansWalkingWireless Technologyconductive gelselectrocardiogrammyocardial ischemianoncontact electrodepacemakerventricular premature contraction

Identifiers

PMID30925752
PMCPMC6480574

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Registered trials

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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.