Title :
On-line Detection of Patient Specific Neonatal Seizures using Support Vector Machines and Half-Wave Attribute Histograms
Author :
Runarsson, Thomas Iceland ; Sigurdsson, Sven
Author_Institution :
Sci. Inst., Iceland Univ., Reykjavik
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 online using a simple heuristic known as chunking. The case study presented illustrates the performance of the method on typical neonatal seizures
Keywords :
electroencephalography; medical signal processing; patient diagnosis; support vector machines; EEG half-wave attribute histogram; chunking; online detection; patient specific neonatal seizures; support vector machine; Autocorrelation; Computer science; Detectors; Digital filters; Electroencephalography; Histograms; Kernel; Pediatrics; Spectral analysis; Support vector machines;
Conference_Titel :
Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-7695-2504-0
DOI :
10.1109/CIMCA.2005.1631546
