Evidence map›Paper›PMID 38329662›Full record

ArticlePhysical and engineering sciences in medicine2024

Fetal QRS extraction from single-channel abdominal ECG using adaptive improved permutation entropy.

Nastaran Mansourian, Sadaf Sarafan, Farah Torkamani-Azar, Tadesse Ghirmai, Hung Cao

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Article in Physical and engineering sciences in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Nastaran MansourianFaculty of Electrical Engineering, University of Shahid Beheshti, Tehran, Iran.
Sadaf SarafanDepartment of Electrical Engineering and Computer Science, University of California, Irvine, CA, 92697, USA.
Farah Torkamani-AzarFaculty of Electrical Engineering, University of Shahid Beheshti, Tehran, Iran. f-torkamani@sbu.ac.ir.ORCID http://orcid.org/0000-0002-6503-1073
Tadesse GhirmaiDivision of Engineering and Mathematics, University of Washington, Bothell Campus, Bothell, WA, 98011, USA.
Hung CaoDepartment of Electrical Engineering and Computer Science, University of California, Irvine, CA, 92697, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fetal electrocardiogram (fECG) monitoring is crucial for assessing fetal condition during pregnancy. However, current fECG extraction algorithms are not suitable for wearable devices due to their high computational cost and multi-channel signal requirement. The paper introduces a novel and efficient algorithm called Adaptive Improved Permutation Entropy (AIPE), which can extract fetal QRS from a single-channel abdominal ECG (aECG). The proposed algorithm is robust and computationally efficient, making it a reliable and effective solution for wearable devices. To evaluate the performance of the proposed algorithm, we utilized our clinical data obtained from a pilot study with 10 subjects, each recording lasting 20 min. Additionally, data from the PhysioNet 2013 Challenge bank with labeled QRS complex annotations were simulated. The proposed methodology demonstrates an average positive predictive value (

Indexed as

AbdomenAlgorithmsElectrocardiographyEntropySignal Processing, Computer-AssistedFemaleFetal MonitoringFetusHumansPregnancyAdaptive improved permutation entropy (AIPE)Fetal monitoringFetal QRS extractionSignal processing

Identifiers

PMID38329662

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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.