Neonatal seizure detection from raw multi-channel EEG using a fully convolutional architecture
A deep learning classifier for detecting seizures in neonates is proposed. This architecture is
designed to detect seizure events from raw electroencephalogram (EEG) signals as …
designed to detect seizure events from raw electroencephalogram (EEG) signals as …
Amplitude-integrated electroencephalography in neonates
Conventional electroencephalography (EEG) has been used for decades in the neonatal
intensive care unit for formulating neurologic prognoses, demonstrating brain functional …
intensive care unit for formulating neurologic prognoses, demonstrating brain functional …
[HTML][HTML] EEG-based neonatal seizure detection with support vector machines
OBJECTIVE: The study presents a multi-channel patient-independent neonatal seizure
detection system based on the Support Vector Machine (SVM) classifier. METHODS: A …
detection system based on the Support Vector Machine (SVM) classifier. METHODS: A …
Technical recommendations and interpretation guidelines for electroencephalography for premature and full-term newborns
G Malfilâtre, L Mony, D Hasaerts… - Neurophysiologie …, 2021 - Elsevier
Electroencephalography (EEG) of neonatal patients is amongst the most valuable diagnostic
and prognostic tool. EEG recordings, acquired at the bedside of infants, evaluate brain …
and prognostic tool. EEG recordings, acquired at the bedside of infants, evaluate brain …
Detecting epileptic seizures in long-term human EEG: a new approach to automatic online and real-time detection and classification of polymorphic seizure patterns
R Meier, H Dittrich, A Schulze-Bonhage… - Journal of clinical …, 2008 - journals.lww.com
Epileptic seizures can cause a variety of temporary changes in perception and behavior. In
the human EEG they are reflected by multiple ictal patterns, where epileptic seizures …
the human EEG they are reflected by multiple ictal patterns, where epileptic seizures …
A comparison of quantitative EEG features for neonatal seizure detection
OBJECTIVE: This study was undertaken to identify the best performing quantitative EEG
features for neonatal seizures detection from a test set of 21. METHODS: Each feature was …
features for neonatal seizures detection from a test set of 21. METHODS: Each feature was …
Automated neonatal seizure detection mimicking a human observer reading EEG
OBJECTIVE: The description and evaluation of a novel patient-independent seizure
detection for the EEG of the newborn term infant. METHODS: We identified characteristics of …
detection for the EEG of the newborn term infant. METHODS: We identified characteristics of …
Deep learning for EEG seizure detection in preterm infants
EEG is the gold standard for seizure detection in the newborn infant, but EEG interpretation
in the preterm group is particularly challenging; trained experts are scarce and the task of …
in the preterm group is particularly challenging; trained experts are scarce and the task of …
Automated neonatal seizure detection: a multistage classification system through feature selection based on relevance and redundancy analysis
OBJECTIVE: Automatic seizure detection obtains valuable information concerning duration
and timing of seizures. Commonly used methods for EEG seizure detection in adults are …
and timing of seizures. Commonly used methods for EEG seizure detection in adults are …
[HTML][HTML] Performance assessment for EEG-based neonatal seizure detectors
OBJECTIVE: This study discusses an appropriate framework to measure system
performance for the task of neonatal seizure detection using EEG. The framework is used to …
performance for the task of neonatal seizure detection using EEG. The framework is used to …