Automatic Neonatal Seizure Detection by EEG
نویسندگان
چکیده
منابع مشابه
A Novel Automatic Neonatal Seizure Detection System
A novel neonatal seizure detection system is proposed including work in the areas of Independent Component Analysis, feature extraction, probability and classification networks. The system comprises of a preprocessing stage to reduce the effect of EEG artifacts and incorporate multichannel analysis and data reduction. A feature extraction stage examines the EEG using techniques from various sig...
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OBJECTIVE To determine the interobserver agreement (IOA) of neonatal seizure detection using the gold standard of conventional, multichannel EEG. METHODS A cohort of full-term neonates at risk of acute encephalopathy was included in this prospective study. The EEG recordings of these neonates were independently reviewed for seizures by three international experts. The IOA was estimated using ...
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OBJECTIVE The study presents a multi-channel patient-independent neonatal seizure detection system based on the Support Vector Machine (SVM) classifier. METHODS A machine learning algorithm (SVM) is used as a classifier to discriminate between seizure and non-seizure EEG epochs. Two post-processing steps are proposed to increase both the temporal precision and the robustness of the system. Th...
متن کاملAutomatic Detection of Seizure Onset in Pediatric Eeg
This paper proposes a method for automatic detection of seizure onset. Two statistical features: skewness and kurtosis with a wavelet based feature: normalized coefficient of variation (NCOV) were extracted from the data. The classification between normal and seizure EEGs was performed using simple linear classifier. The performance of the algorithm was tested on the 10 patient’s data of CHB-MI...
متن کاملAutomatic seizure detection using a two-dimensional EEG feature space
ii Abstract (in Finnish) iiiin Finnish) iii
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ژورنال
عنوان ژورنال: Pediatric Neurology Briefs
سال: 1997
ISSN: 2166-6482,1043-3155
DOI: 10.15844/pedneurbriefs-11-10-11