On-line Detection of Patient Specific Neonatal Seizures using Support Vector Machines and Half-Wave Attribute Histograms

Authors:
Thomas Philip Runarsson;Sven Sigurdsson
Affiliations:
University of Iceland;University of Iceland
Venue:
CIMCA '05 Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce Vol-2 (CIMCA-IAWTIC'06) - Volume 02
Year:
2005

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A system for epileptic seizure focus detection based on EEG analysis

UCAmI'12 Proceedings of the 6th international conference on Ubiquitous Computing and Ambient Intelligence

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Abstract

An efficient and effective Support Vector Machine for online seizures detection is presented. The kernel designed is based on features generated from bivariate histograms of EEG half-wave attributes. The training is on-line using a simple heuristic known as chunking. The case study presented illustrates the performance of the method on typical neonatal seizures.