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Towards accurate search for neonatal heartbeat: weighted algorithm for reliable ECG analysis of premature infants

  • Jessica Rahman*
  • , Aida Brankovic
  • , Mark Tracy
  • , Robert Halliday
  • , Sankalp Khanna
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

Abstract

Accurate identification of the QRS complex is critical to analyse heart rate variability (HRV), which is linked to various adverse outcomes in premature infants. Reliable and accurate extraction of HRV characteristics at a large scale in the neonatal context remains a challenge. In this paper, we investigate the capabilities of 15 state-of-the-art QRS complex detection implementations using two real-world preterm neonatal datasets. As an attempt to improve the accuracy and reliability, we introduce a weighted ensemble-based method as an alternative. Obtained results indicate the superiority of the proposed method over the state of the art on both datasets with an F1-score of 0.966 (95% CI 0.962-0.97) and 0.893 (95% CI 0.892-0.894). This motivates the deployment of ensemble-based methods for any HRV-based analysis to ensure robust and accurate QRS complex detection.

Original languageEnglish
Title of host publicationMEDINFO 2023 - The Future is Accessible
Subtitle of host publicationProceedings of the 19th World Congress on Medical and Health Informatics
EditorsJen Bichel-Findlay, Paula Otero, Philip Scott, Elaine Huesing
Place of PublicationAmsterdam
PublisherIOS Press
Pages224-228
Number of pages5
ISBN (Electronic)9781643684574
ISBN (Print)9781643684567
DOIs
Publication statusPublished - 25 Jan 2024
Externally publishedYes
Event19th World Congress on Medical and Health Informatics, MedInfo 2023 - Sydney, Australia
Duration: 8 Jul 2023 → 12 Jul 2023

Publication series

NameStudies in Health Technology and Informatics
PublisherIOS Press
Volume310
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Conference

Conference19th World Congress on Medical and Health Informatics, MedInfo 2023
Country/TerritoryAustralia
CitySydney
Period8/07/23 → 12/07/23

Bibliographical note

Copyright © 2024 International Medical Informatics Association (IMIA) and IOS Press. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

  • artificial intelligence
  • Electrocardiogram
  • ensemble model
  • premature infant
  • R wave detection

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