A statistical framework for EEG channel selection and seizure prediction on mobile
- 23 January 2019
- journal article
- research article
- Published by Springer Nature in International Journal of Speech Technology
- Vol. 22 (1) , 191-203
Abstract
No abstract availableKeywords
This publication has 25 references indexed in Scilit:
- An Amplitude-Preserved Time–Frequency Peak Filtering Based on Empirical Mode Decomposition for Seismic Random Noise ReductionIEEE Geoscience and Remote Sensing Letters, 2013
- Seizure prediction in patients with mesial temporal lobe epilepsy using EEG measures of state similarityClinical Neurophysiology, 2013
- Predicting Epileptic Seizures in Scalp EEG Based on a Variational Bayesian Gaussian Mixture Model of Zero-Crossing IntervalsIEEE Transactions on Biomedical Engineering, 2013
- Design of first-order differentiator utilising FIR and IIR sub-filtersInternational Journal of Reasoning-based Intelligent Systems, 2013
- Seizure prediction using EEG spatiotemporal correlation structureEpilepsy & Behavior, 2012
- A rule-based seizure prediction method for focal neocortical epilepsyClinical Neurophysiology, 2012
- A High-Performance Lossless Compression Scheme for EEG Signals Using Wavelet Transform and Neural Network PredictorsInternational Journal of Telemedicine and Applications, 2012
- Lossless Compression Schemes for ECG Signals Using Neural Network PredictorsEURASIP Journal on Advances in Signal Processing, 2007
- Weighted median filters: a tutorialIEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, 1996
- Über das Elektrenkephalogramm des MenschenEuropean Archives of Psychiatry and Clinical Neuroscience, 1929