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Adaptive probabilistic modelling of the EEG background is proposed for seizure detection in neonates with hypoxic ischemic encephalopathy. The decision is made based on temporal derivative of the seizure probability with respect to the adaptively modeled level of background activity. The robustness of the system to long duration, seizure-like artifacts (in particular those due to respiration) is improved...
To evaluate 3 published automated algorithms for detecting seizures in neonatal EEG.One-minute, artifact-free EEG segments consisting of either EEG seizure activity or non-seizure EEG activity were extracted from EEG recordings of 13 neonates. Three published neonatal seizure detection algorithms were tested on each EEG recording. In an attempt to obtain improved detection rates, threshold values...
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