The present invention relates to a method for the real-time identification of seizures in an Electroencephalogram (EEG) signal. The method provides for patient-independent seizure identification by use of a multi-patient trained generic Support Vector Machine (SVM) classifier. The SVM classifier is operates on a large feature vector combining features from a wide variety of signal processing and analysis techniques. The method operates sufficiently accurately to be suitable for use in a clinical environment. The method may also be combined with additional classifiers, such a Gaussian Mixture Model (GMM) classifier, for improved robustness, and one or more dynamic classifiers such as an SVM using sequential kernels for improved temporal analysis of the EEG signal.
申请公布号
DK2416703(T3)
申请公布日期
2016.12.19
申请号
DK20100718103T
申请日期
2010.04.07
申请人
National University Of Ireland, Cork
发明人
FAUL, Stephen Daniel;TEMKO, Andriy;MARNANE, William, Peter;LIGHTBODY, Gordon;BOYLAN, Geraldine Bernadette