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Neonatal EEG graded for severity of background abnormalities in hypoxic-ischaemic encephalopathy

2022-06-09 · John M O'Toole, Sean R Mathieson, Sumit A Raurale, Fabio Magarelli, William P Marnane, Gordon Lightbody, Geraldine B Boylan

This report describes a set of neonatal electroencephalogram (EEG) recordings graded according to the severity of abnormalities in the background pattern. The dataset consists of 169 hours of multichannel EEG from 53 neonates recorded in a neonatal intensive care unit. All neonates received a diagnosis of hypoxic-ischaemic encephalopathy (HIE), the most common cause of brain injury in full term infants. For each neonate, multiple 1-hour epochs of good quality EEG were selected and then graded for background abnormalities. The grading system assesses EEG attributes such as amplitude and frequency, continuity, sleep--wake cycling, symmetry and synchrony, and abnormal waveforms. Background severity was then categorised into 4 grades: normal or mildly abnormal EEG, moderately abnormal EEG, severely abnormal EEG, and inactive EEG. The data can be used as a reference set of multi-channel EEG for neonates with HIE, for EEG training purposes, or for developing and evaluating automated grading algorithms.

📄 PDF Abstract BibTeX arXiv:2206.04420

Code (1)

otoolej/downsample_open_eeg 공식 구현

Tasks

EEGElectroencephalogram (EEG)

Machine-learning competition to grade EEG background patterns in newborns with hypoxic-ischaemic encephalopathy

2025-08-27 · Fabio Magarelli, Geraldine B. Boylan, Saeed Montazeri, Feargal O'Sullivan 외 arxiv

Machine learning (ML) has the potential to support and improve expert performance in monitoring the brain function of at-risk newborns. Developing accurate and reliable ML models depends on access to high-quality, annota…

A simple EEG-based decision tool for neonatal therapeutic hypothermia in hypoxic-ischemic encephalopathy

2024-03-29 · Marc Fiammante, Anne-Isabelle Vermersch, Marie Vidailhet, Mario Chavez

Accurate identification of hypoxic-ischemic brain injury in the early neonatal period is essential for initiating therapeutic hypothermia (TH) within 6 hours of birth to optimize neurodevelopmental outcomes. We aimed to …

EEG Electroencephalogram (EEG)

BOston Neonatal Brain Injury Data for Hypoxic Ischemic Encephalopathy (BONBID-HIE): II. 2-year Neurocognitive Outcome and NICU Outcome

2024-11-05 · Rina Bao, Yangming Ou

Hypoxic Ischemic Encephalopathy (HIE) affects approximately 1-5/1000 newborns globally and leads to adverse neurocognitive outcomes in 30% to 50% of cases by two years of age. Despite therapeutic advances with Therapeuti…

Prognosis

Tracé alternant detector for grading hypoxic-ischemic encephalopathy in neonatal EEG

2021-05-31 · Sumit A. Raurale, Geraldine B. Boylan, Sean R. Mathieson, William P. Marnane 외

Electroencephalography (EEG) is an important clinical tool to capture sleep-wake cycling. It can also be used for grading injury, known as hypoxic-ischaemic encephalopathy(HIE), caused by lack of oxygen or blood to the b…

EEG Electroencephalogram (EEG)

Neonatal Hypoxic-ischaemic Encephalopathy Classification from the EEG and HRV Signals Using a Conformer based Masked Autoencoder

2026-07-26 · Shuwen Yu, William P Marnane, Geraldine B. Boylan, Gordon Lightbody arxiv

In this paper, we propose the MAEConformer, a novel self-supervised learning framework that combines the Conformer architecture with the Masked Autoencoder (MAE) paradigm for large-scale representation learning from unla…

Self-Supervised Learning Representation Learning