Journal of Brain Research

Department of Paediatrics, University of Lagos, Lagos, Nigeria

Publications

• Research   
  Wavelet Time Scattering Based Classification of Interictal and Preictal EEG Signals
  Author(s): Afreda A. Susu*, H.A. Agboola, C. Solebo, F.E.A. Lesi and D.S. Aribike
  
  If it were possible to reliably identify the preictal brain state from dynamical changes in EEG data of epilepsy patients, then the age long problem of actualizing a fully automated closed-loop seizure – warning or seizure-prevention system that is clinically deployable would have been resolved. Accordingly, through feature engineering, a great deal of effort has been invested over the discovery of EEG features or measures that are always indicative of the preictal brain state. However, this has proven to be difficult, time consuming and apparently unsuccessful. Therefore, lately, attention has shifted to feature learning-methods that automatically learn and extracts useful discriminatory features from raw data. This paper studies the efficacy of wavelet time scattering learned EEG features for interictal and preictal EEG classification. Wavelet time scattering ne.. Read More»
  DOI: 10.37421/2684-4583.2020.3.115

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