Evidence map›Paper›PMID 35884277›Full record

ArticleBiosensors2022

Wearable Fetal ECG Monitoring System from Abdominal Electrocardiography Recording.

Yuwei Zhang, Aihua Gu, Zhijun Xiao, Yantao Xing, Chenxi Yang, Jianqing Li, Chengyu Liu

Abstract read
In one paragraph

Article in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 3 pooled it
–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

11 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  6. 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

7 authors.

Yuwei ZhangThe State Key Laboratory of Bioelectronics, School of Biological Sciences and Medical Engineering, Southeast University, Nanjing 210096, China.
Aihua GuThe State Key Laboratory of Bioelectronics, School of Biological Sciences and Medical Engineering, Southeast University, Nanjing 210096, China.
Zhijun XiaoThe State Key Laboratory of Bioelectronics, School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China.
Yantao XingThe State Key Laboratory of Bioelectronics, School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China.ORCID 0000-0002-4951-3451
Chenxi YangThe State Key Laboratory of Bioelectronics, School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China.ORCID 0000-0003-0180-4126
Jianqing LiThe State Key Laboratory of Bioelectronics, School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China.
Chengyu LiuThe State Key Laboratory of Bioelectronics, School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China.ORCID 0000-0003-1965-3020

Funding

National Key Research and Development Program of China 2019YFE0113800National Natural Science Foundation of China 62001111National Natural Science Foundation of China 62071241National Natural Science Foundation of China 62171123National Natural Science Foundation of China 81871444Natural Science Foundation of Jiangsu Province of China BK20190014Natural Science Foundation of Jiangsu Province of China BK20192004Natural Science Foundation of Jiangsu Province of China BK20200364
6 · The paper itself

Abstract

Fetal electrocardiography (ECG) monitoring during pregnancy can provide crucial information for assessing the fetus's health status and making timely decisions. This paper proposes a portable ECG monitoring system to record the abdominal ECG (AECG) of the pregnant woman, comprising both maternal ECG (MECG) and fetal ECG (FECG), which could be applied to fetal heart rate (FHR) monitoring at the home setting. The ECG monitoring system is based on data acquisition circuits, data transmission module, and signal analysis platform, which consists of low input-referred noise, high input impedance, and high resolution. The combination of the adaptive dual threshold (ADT) and the independent component analysis (ICA) algorithm is employed to extract the FECG from the AECG signals. To validate the performance of the proposed system, AECG is recorded and analyzed of pregnant women in three different postures (supine, seated, and standing). The result shows that the proposed system can record the AECG in different postures with good signal quality and high accuracy in fetal ECG and heart rate information. Sensitivity (

Indexed as

Signal Processing, Computer-AssistedWearable Electronic DevicesAlgorithmsElectrocardiographyFemaleFetal MonitoringFetusHumansPregnancyelectrocardiography (ECG)fetalfetal heart rate (FHR)health statusmonitoring system

Identifiers

PMID35884277
PMCPMC9313261

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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.