Dual tree complex wavelet transform based analysis of epileptiform discharges
Diagnosis of epileptic seizures entails visual inspection of complex seizure patterns which is a tedious task. Development of automated systems for analysing brain activity would significantly minimise the epilepsy treatment gap by providing assistance to neurophysiologists. Present research work is intended to provide insight to the epileptiform discharges during the seizures using dual tree complex wavelet transform. Algorithm is developed using publically available data from Bonn University. Statistical and nonlinear features, selected on the basis of Bhattacharyya distance, are extracted from EEG segments to demarcate the seizure and nonseizure EEG boundaries. Quadratic classification of EEG features followed by k-fold cross validation with varying train to test ratios is employed to develop a generalised robust model. Performance of classifier is accessed in terms of statistical parameters.
KeywordsClassification Dual tree complex wavelet transform EEG K-fold cross validation Seizure detection
The authors would like to thank Prof. Nick Kingsbury (University of Cambridge, UK) for providing the DTCWT toolbox and Professor Ralph G. Andrzejak (University of Bonn, Germany) for making the database publically available.
- 1.WHO (2010) Epilepsy in the WHO Eastern Mediterranean Region: bridging the gap. Regional Office for the Eastern Mediterranean. http://apps.who.int/iris/handle/10665/119905. Accessed 12 Feb 2017
- 2.WHO (2017). Epilepsy fact sheet. http://www.who.int/mediacentre/factsheets/fs999/en/. Accessed 28 Feb 2017
- 5.Rafi N, Khan YU, Farooq O (2014) Epileptic seizure detection: reformation of the traditional method on scalp recorded electroencephalogram. In: International conference on emerging trends in electrical engineeringGoogle Scholar
- 7.Das AB, Bhuiyan MIH, Alam SS (2014) A statistical method for automatic detection of seizure and epilepsy in the dual tree complex wavelet transform domain. In: 3rd International conference on informatics, electronics & visionGoogle Scholar
- 9.Farooq O, Khan YU (2010) Automatic seizure detection using higher order moments. In: International conference on recent trends in information, telecommunication and computingGoogle Scholar
- 18.Khan AT, Husain I, Khan YU (2015) Seizure onset patterns in EEG and their detection using statistical measures. In: 12th IEEE India international conference (INDICON) on electronics, energy, environment, communication, computer, controlGoogle Scholar