Evidence map›Paper›PMID 37637479›Full record

ArticleIEEE sensors letters2022

Lullaby: A Novel Algorithm to Extract Fetal QRS in Real Time Using Periodic Trend Feature.

Daniel Jilani, Tai Le, Tim Etchells, Michael P H Lau, Hung Cao

Abstract read
In one paragraph

Article in IEEE sensors letters, 2022. 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
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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

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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

5 authors.

Daniel JilaniDepartment of Electrical Engineering, University of California Irvine, Irvine, CA 92697, USA.
Tai LeDepartment of Biomedical Engineering, University of California Irvine, Irvine, CA 92697, USA.
Tim EtchellsSensoriis, Inc., Edmonds, WA 98026, USA.
Michael P H LauSensoriis, Inc., Edmonds, WA 98026, USA.
Hung CaoDepartment of Electrical Engineering, University of California Irvine, Irvine, CA 92697, USA.

Funding

Cloud-based High-throughput Acquisition and Analytics of Zebrafish Electrocardiogram for Cardiac Studies and Drug DevelopmentR44OD024874 · OD · SENSORIIS, INC. · PI CAO, HUNG, LAU, MICHAEL P.H. · 2020 to 2021
$1.5M
NIH HHS R44 OD024874
6 · The paper itself

Abstract

Fetal heart rate (fHR) is an important indicator for monitoring of fetal cardiac health and development. The widely-used method based on ultrasound, however, is not continuous and often requires an expert to perform; thus, it is mostly used in clinics during checkups. The advances in wearable technology have paved the way for home assessment of fHR via the extraction of the mother's abdominal electrocardiogram (ECG) acquired by novel patches. Several methods have been developed for such; however, the computation is either too slow for real-time monitoring or too heavy to be performed in a wearable. In this work, we develop and validate the Lullaby algorithm - a novel method for fetal QRS extraction from aECG. The results showed that Lullaby is almost 7 times faster than existing methods with a better F1-score of 0.815, holding promise to transform perinatal monitoring.

Indexed as

abdominal ECG (aECG)biosignalsfetal heart rate (fHR)fetal QRS (fQRS)periodic trend feature (PTF)real-timeSignal processing

Identifiers

PMID37637479
PMCPMC10456990

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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.