Andriy Temko;William Peter Marnane;Geraldine Bernadette Boylan;Stephen Daniel Faul;Gordon Lightbody
发明人:
Stephen Daniel Faul,Andriy Temko,William Peter Marnane,Gordon Lightbody,Geraldine Bernadette Boylan
申请号：
US13262891
公开号：
US10433752B2
申请日:
2010.04.07
申请国别(地区):
US
年份:
2019
代理人:
摘要：
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.
