Three Channel Wavelet Filter Banks With Minimal Time Frequency Spread for Classification of Seizure-Free and Seizure EEG Signals

Three Channel Wavelet Filter Banks With Minimal Time Frequency Spread for Classification of Seizure-Free and Seizure EEG Signals

Dinesh Bhati, Akruti Raikwar, Ram Bilas Pachori, Vikram M. Gadre
Copyright: © 2020 |Pages: 17
DOI: 10.4018/978-1-7998-2120-5.ch012
OnDemand:
(Individual Chapters)
Available
$37.50
Current Special Offers
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

The authors compute the classification accuracy of minimal time-frequency spread wavelet filter bank with three channels in discriminating seizure-free and seizure electroencephalogram (EEG) signals. Wavelet filter bank with three channels generates two wavelet functions and one scaling function at the first level of wavelet decomposition. A time-frequency localized filter bank can be generated by minimizing the time spread and frequency spread of any one or all the functions simultaneously. The minimal time-frequency spread wavelet filter bank with three channels of regularity order, one designed with several different time-frequency optimality criteria and length six, are chosen, and the effect of each optimality criterion on the discrimination of seizure-free and seizure EEG signals is computed. The classification accuracy for five different optimality criteria are computed. Time-frequency localized three-band filter bank of length six classifies, the seizure-free and seizure EEG signals of Bonn University EEG database, with 98.25% of accuracy.
Chapter Preview
Top

Introduction

Epilepsy is an electrical disturbance of the neuron signals that causes neurological disorders in the brain (Andrzejak, Schindler, & Rummel, 2012). For clinical assessments, the neuron activity of the brain is generally captured as electroencephalogram (EEG) (Andrzejak, Schindler, & Rummel, 2012). It is used for recording the electrical state of the brain neurons to detect the common brain disorders called seizures. Many times, it is required to record EEG signals for many hours to analyze electrical seizure activity.

Key Terms in this Chapter

Wavelet Filter Banks: Filter banks generated from cascade iterations a regular low pass filter.

Regularity: It is the property of a discrete-time filter which generate a continuous time function from its cascade iterations.

Neural Network: It is a system used to determine the class of a given signal.

Time Frequency Localization: It is the property of a discrete time filter or a function which ensure minimizes the spreads or the variance in time and frequency domains.

Feature Extraction: It is the process to extract the main time frequency components of the signal to differentiate it from other signals.

Complete Chapter List

Search this Book:
Reset