Conference Publication Details
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Nagaraj S.;Stevenson N.;Marnane W.;Boylan G.;Lightbody G.
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
Robustness of time frequency distribution based features for automated neonatal EEG seizure detection
Scopus: 4 ()
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2014 IEEE. In this paper we examined the robustness of a feature-set based on time-frequency distributions (TFDs) for neonatal EEG seizure detection. This feature-set was originally proposed in literature for neonatal seizure detection using a support vector machine (SVM). We tested the performance of this feature-set with a smoothed Wigner-Ville distribution and modified B distribution as the underlying TFDs. The seizure detection system using time-frequency signal and image processing features from the TFD of the EEG signal using modified B distribution was able to achieve a median receiver operator characteristic area of 0.96 (IQR 0.91-0.98) tested on a large clinical dataset of 826 h of EEG data from 18 full-term newborns with 1389 seizures. The mean AUC was 0.93.
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