Seizure onset patterns in EEG and their detection using statistical measures

Diagnosis and treatment of epileptic seizures requires analysis of neuronal activity of the brain for detection of seizures at the onset. Present work for seizure onset includes extraction of various statistical and nonlinear features including a newly proposed statistical feature i.e. Modified Semi variance. Bhattacharyya distance as a separability measure for seizure and non-seizure activity gives fair justification for the new feature when compared with other traditional features. Selected features are then classified using a quadratic classifier. K-fold cross validation technique is used to validate the algorithm. Satisfactory results are obtained with average sensitivity and latency of 96.59% and 2.75 seconds respectively.

[1]  Alaa A. Kharbouch,et al.  Automatic detection of epileptic seizure onset and termination using intracranial EEG , 2012 .

[2]  Ali H. Shoeb,et al.  Application of Machine Learning To Epileptic Seizure Detection , 2010, ICML.

[3]  J. Echauz,et al.  Feature parameter optimization for seizure detection/prediction , 2001, 2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[4]  H. Jasper,et al.  The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology. , 1999, Electroencephalography and clinical neurophysiology. Supplement.

[5]  Hannes Perko,et al.  Automatic detection of the seizure onset zone based on ictal EEG , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[6]  J. Gotman,et al.  Wavelet based automatic seizure detection in intracerebral electroencephalogram , 2003, Clinical Neurophysiology.

[7]  J. Gotman.  Automatic recognition of epileptic seizures in the EEG. , 1982, Electroencephalography and clinical neurophysiology.

[8]  T. A. Betts.  Epilepsy at the millennium , 1999, Seizure.

[9]  Abdulhamit Subasi,et al.  EEG signal classification using wavelet feature extraction and a mixture of expert model , 2007, Expert Syst. Appl..

[10]  O. Farooq,et al.  Automated seizure detection in scalp EEG using multiple wavelet scales , 2012, 2012 IEEE International Conference on Signal Processing, Computing and Control.

[11]  Ali H. Shoeb,et al.  Patient-specific seizure onset detection , 2004, Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[12]  Thasneem Fathima,et al.  Detection of Epileptic Seizure Event and Onset Using EEG , 2014, BioMed research international.

[13]  Ron Kohavi,et al.  A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection , 1995, IJCAI.

[14]  Abdulhamit Subasi,et al.  Epileptic seizure detection using dynamic wavelet network , 2005, Expert Syst. Appl..

[15]  A. Bachelor.  GLOSSARY OF TERMS GLOSSARY OF TERMS , 2010 .