A Novel Spike Detection Algorithm Based on Multi-Channel of BECT EEG Signals

Benign childhood epilepsy with centro-temporal spikes (BECT) is one of the most common epilepsy syndromes in childhood which is typically characterized by localized discharges in the central and temporal regions. Traditionally, the recognition of spikes requires visual assessment of long-term EEG recordings which is time consuming and subjective because it depends on the knowledge and experience of the doctor. Therefore, a novel multi-step spike detection algorithm based on average reference (AV) channel and bipolar (BP) channel BECT EEG is proposed, including candidate spike detection algorithm, false positive spike (FPS) elimination, spike feature extraction and random forest (RF) classification. The proposed method is evaluated using 7 routine EEG recordings. This brief shows that the sensitivity (Sen), specificity (Spe), selectivity (Sel) and accuracy (AC) obtained by the proposed method are 97.4%, 96.5%, 96.6% and 96.9%, respectively. Experimental results show that the proposed method is capable of detecting BECT spikes efficiently.

[1]  Stefano Di Gennaro,et al.  CLASSIFICATION OF EEG SIGNALS FOR DETECTION OF EPILEPTIC SEIZURES BASED ON WAVELETS AND STATISTICAL PATTERN RECOGNITION , 2014 .

[2]  Martha Feucht,et al.  Speech and school performance in children with benign partial epilepsy with centro-temporal spikes (BCECTS) , 2009, Seizure.

[3]  Saleh A. Alshebeili,et al.  Epileptic MEG Spikes Detection Using Amplitude Thresholding and Dynamic Time Warping , 2017, IEEE Access.

[4]  Boualem Boashash,et al.  A Multistage System for Automatic Detection of Epileptic Spikes , 2018, REV Journal on Electronics and Communications.

[5]  Jing Wang,et al.  A spike detection method in EEG based on improved morphological filter , 2007, Comput. Biol. Medicine.

[6]  O. Gonen,et al.  Neuropsychological aspects of benign childhood epilepsy with centrotemporal spikes , 2010, Seizure.

[7]  Kazuyuki Aihara,et al.  Development and Applications of Biomimetic Neuronal Networks Toward BrainMorphic Artificial Intelligence , 2018, IEEE Transactions on Circuits and Systems II: Express Briefs.

[8]  Patrick Van Bogaert,et al.  Cluster-based spike detection algorithm adapts to interpatient and intrapatient variation in spike morphology , 2012, Journal of Neuroscience Methods.

[9]  Yao Ding,et al.  Automatic Epileptic Seizures Joint Detection Algorithm Based on Improved Multi-Domain Feature of cEEG and Spike Feature of aEEG , 2019, IEEE Access.

[10]  C. Binnie,et al.  A glossary of terms most commonly used by clinical electroencephalographers. , 1974, Electroencephalography and clinical neurophysiology.

[11]  Ulrich Büttner,et al.  Fractal dimension analysis for spike detection in low SNR extracellular signals , 2016, Journal of neural engineering.

[12]  J. Stevens,et al.  Seizure occurrence and interspike interval. Telemetered electroencephalogram studies. , 1972, Archives of neurology.

[13]  Z. Jane Wang,et al.  Removing Muscle Artifacts From EEG Data via Underdetermined Joint Blind Source Separation: A Simulation Study , 2020, IEEE Transactions on Circuits and Systems II: Express Briefs.

[14]  István Ulbert,et al.  Spike detection and sorting with deep learning , 2020, Journal of neural engineering.

[15]  Weifeng Xu,et al.  Epileptic Seizure Detection System Based on Multi-Domain Feature and Spike Feature of EEG , 2019, Int. J. Humanoid Robotics.

[16]  Tim Oates,et al.  A Flexible Multichannel EEG Feature Extractor and Classifier for Seizure Detection , 2015, IEEE Transactions on Circuits and Systems II: Express Briefs.

[17]  Nguyen Linh-Trung,et al.  New Feature Selection Method for Multi-channel EEG Epileptic Spike Detection System , 2019, VNU Journal of Science: Computer Science and Communication Engineering.

[18]  S Nishida,et al.  Signal separation of background EEG and spike by using morphological filter. , 1999, Medical engineering & physics.

[19]  Xingyu Wang,et al.  An Automatic Spike Detection System Based on Elimination of False Positives Using the Large-Area Context in the Scalp EEG , 2011, IEEE Transactions on Biomedical Engineering.

[20]  Karim Abed-Meraim,et al.  Multi-channel EEG epileptic spike detection by a new method of tensor decomposition , 2020, Journal of neural engineering.