Neonatal EEG graded for severity of background abnormalities in hypoxic-ischaemic encephalopathy
Abstract 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...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-03-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-023-02002-8 |
| _version_ | 1827985192028995584 |
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| author | John M. O’Toole Sean R. Mathieson Sumit A. Raurale Fabio Magarelli William P. Marnane Gordon Lightbody Geraldine B. Boylan |
| author_facet | John M. O’Toole Sean R. Mathieson Sumit A. Raurale Fabio Magarelli William P. Marnane Gordon Lightbody Geraldine B. Boylan |
| author_sort | John M. O’Toole |
| collection | DOAJ |
| description | Abstract 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, 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, majorly 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. |
| first_indexed | 2024-04-09T23:10:58Z |
| format | Article |
| id | doaj.art-9934f42db3474807abd601b063e7c474 |
| institution | Directory Open Access Journal |
| issn | 2052-4463 |
| language | English |
| last_indexed | 2024-04-09T23:10:58Z |
| publishDate | 2023-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj.art-9934f42db3474807abd601b063e7c4742023-03-22T10:23:10ZengNature PortfolioScientific Data2052-44632023-03-011011810.1038/s41597-023-02002-8Neonatal EEG graded for severity of background abnormalities in hypoxic-ischaemic encephalopathyJohn M. O’Toole0Sean R. Mathieson1Sumit A. Raurale2Fabio Magarelli3William P. Marnane4Gordon Lightbody5Geraldine B. Boylan6INFANT Research Centre, University College CorkINFANT Research Centre, University College CorkINFANT Research Centre, University College CorkINFANT Research Centre, University College CorkINFANT Research Centre, University College CorkINFANT Research Centre, University College CorkINFANT Research Centre, University College CorkAbstract 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, 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, majorly 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.https://doi.org/10.1038/s41597-023-02002-8 |
| spellingShingle | John M. O’Toole Sean R. Mathieson Sumit A. Raurale Fabio Magarelli William P. Marnane Gordon Lightbody Geraldine B. Boylan Neonatal EEG graded for severity of background abnormalities in hypoxic-ischaemic encephalopathy Scientific Data |
| title | Neonatal EEG graded for severity of background abnormalities in hypoxic-ischaemic encephalopathy |
| title_full | Neonatal EEG graded for severity of background abnormalities in hypoxic-ischaemic encephalopathy |
| title_fullStr | Neonatal EEG graded for severity of background abnormalities in hypoxic-ischaemic encephalopathy |
| title_full_unstemmed | Neonatal EEG graded for severity of background abnormalities in hypoxic-ischaemic encephalopathy |
| title_short | Neonatal EEG graded for severity of background abnormalities in hypoxic-ischaemic encephalopathy |
| title_sort | neonatal eeg graded for severity of background abnormalities in hypoxic ischaemic encephalopathy |
| url | https://doi.org/10.1038/s41597-023-02002-8 |
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