Conference Proceedings
Correlation analysis of seizure detection features
L Kuhlmann, MJ Cook, K Fuller, DB Grayden, AN Burkitt, IMY Mareels
Issnip 2008 Proceedings of the 2008 International Conference on Intelligent Sensors Sensor Networks and Information Processing | IEEE | Published : 2008
Abstract
Automated seizure detection is important for speeding up epilepsy diagnosis or for controlling an implantable brain stimulator to avert seizures. Various features calculated from the electroencephalogram (EEG) can be used to detect seizures, and combining features can give superior detection performance. This paper investigates the correlation between seizure detection features in order to determine which ones should be combined for the purposes of seizure detection. Combinations of three features involving relative average amplitude, relative scale energy, coefficient of variation of amplitude, relative power, relative gradient and bounded variation tended to show the lowest correlations. ©..
View full abstractGrants
Awarded by Australian Research Council Linkage Grant
Awarded by Australian Research Council
Funding Acknowledgements
This work was supported by an Australian Research Council Linkage Grant (LP0560684), The Bionic Ear Institute and St. Vincents Hospital Melbourne. We are grateful for the EEG data provided by the patients, and to the St Vincents Hospital Melbourne Neurophysiology Clinic for collecting the data. EEG data collection was approved by the St. Vincents Hospital Melbourne Ethics Committee.