Absence Seizure Detection Using Ramanujan Filter Banks

Absence seizures are a type of generalized seizures characterized by a 3 Hz periodic spike and wave discharge pattern in the Electroencephalogram (EEG). The most common way to diagnose them is by detecting such periodic patterns in a patient’s EEG. Recently, a new method known as Ramanujan Filter Bank (RFB) was proposed for identifying, estimating and localizing periodicities in data. The RFB was shown to offer important advantages over traditional period estimation techniques in DSP. In this work, we demonstrate that the RFB offers very useful diagnostic information when applied to EEG signals from absence-seizure patients.

[1]  Erika E. Fanselow,et al.  Reduction of Pentylenetetrazole-Induced Seizure Activity in Awake Rats by Seizure-Triggered Trigeminal Nerve Stimulation , 2000, The Journal of Neuroscience.

[2]  Chang-Chia Liu,et al.  A Novel Wavelet Based Algorithm for Spike and Wave Detection in Absence Epilepsy , 2010, 2010 IEEE International Conference on BioInformatics and BioEngineering.

[3]  P. P. Vaidyanathan.  Ramanujan Sums in the Context of Signal Processing—Part II: FIR Representations and Applications , 2014, IEEE Transactions on Signal Processing.

[4]  P. P. Vaidyanathan,et al.  Detecting tandem repeats in DNA using Ramanujan Filter Bank , 2016, 2016 IEEE International Symposium on Circuits and Systems (ISCAS).

[5]  H. Adeli,et al.  Analysis of EEG records in an epileptic patient using wavelet transform , 2003, Journal of Neuroscience Methods.

[6]  Manolis Tsiknakis,et al.  Absence seizure epilepsy detection using linear and nonlinear eeg analysis methods , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[7]  I Lemahieu,et al.  Detection of spike and wave discharges in the cortical EEG of genetic absence epilepsy rats from Strasbourg. , 2003, Physics in medicine and biology.

[8]  F. Gibbs,et al.  THE ELECTRO-ENCEPHALOGRAM IN EPILEPSY AND IN CONDITIONS OF IMPAIRED CONSCIOUSNESS , 1935 .

[9]  P. P. Vaidyanathan,et al.  Nested Periodic Matrices and Dictionaries: New Signal Representations for Period Estimation , 2015, IEEE Transactions on Signal Processing.

[10]  P. P. Vaidyanathan,et al.  Ramanujan Sums in the Context of Signal Processing—Part I: Fundamentals , 2014, IEEE Transactions on Signal Processing.

[11]  P. P. Vaidyanathan,et al.  Ramanujan filter banks for estimation and tracking of periodicities , 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[12]  P. P. Vaidyanathan,et al.  Properties of Ramanujan filter banks , 2015, 2015 23rd European Signal Processing Conference (EUSIPCO).

[13]  P. P. Vaidyanathan,et al.  Detection of protein repeats using the Ramanujan Filter Bank , 2016, 2016 50th Asilomar Conference on Signals, Systems and Computers.