Abstract
Neonatal seizures are a common emergency in the neonatal intensive care unit (NICU). There are many questions yet to be answered regarding the temporal/spatial characteristics of seizures from different pathologies, response to medication, effects on neurodevelopment and optimal detection. The dataset presented in this descriptor contains EEG recordings from human neonates, the visual interpretation of the EEG by the human experts, supporting clinical data and codes to assist access. Multi-channel EEG was recorded from 79 term neonates admitted to the NICU at the Helsinki University Hospital. The median recording duration was 74 min (IQR: 64 to 96 min). The presence of seizures in the EEGs was annotated independently by three experts. An average of 460 seizures were annotated per expert in the dataset; 39 neonates had seizures and 22 were seizure free, by consensus. The dataset can be used as a reference set of neonatal seizures, in studies of inter-observer agreement and for the development of automated methods of seizure detection and other EEG analyses.
Highlights
Background & SummaryNeonatal seizures are regularly seen in infants in the neonatal intensive care unit (NICU)
While there is a lack of evidence on the causal link between neonatal seizures and neurodevelopmental outcome in a range of aetiologies in the human neonate, they are aggressively treated with a sequence of anti-epileptic medications[1,2,3,4]
Cohort EEGs were selected from an archive of neonatal EEG recordings that were recorded on request from the clinical team due to suspicion of seizures
Summary
Neonatal seizures are regularly seen in infants in the neonatal intensive care unit (NICU). Further development of these algorithms is stymied by 1) a lack of openly accessible datasets to evaluate and compare competing algorithms and 2) insufficient methods of assessing algorithm performance due to methodological flaws that do not take into account inter-observer variability of the EEG annotations (e.g. the use of sensitivity and specificity as metrics or a lack of annotations from multiple experts) This data descriptor outlines a dataset of multi-channel EEG recordings that have been annotated for neonatal seizures by three independent experts. Our dataset can be used as training data for neonatal seizure detection algorithms or as a validation set to compare existing methods It is the only publicly available dataset of neonatal EEG recordings with annotations of seizures from multiple experts. Our present dataset is useful as a reference dataset for various studies on normal and abnormal EEG patterns commonly seen in the NICU, as well as for studies of inter-observer agreement in visual EEG interpretation
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