Time–frequency localized three-band biorthogonal wavelet filter bank using semidefinite relaxation and nonlinear least squares with epileptic seizure EEG signal classification

2017 ◽  
Vol 62 ◽  
pp. 259-273 ◽  
Author(s):  
Dinesh Bhati ◽  
Manish Sharma ◽  
Ram Bilas Pachori ◽  
Vikram M. Gadre
Keyword(s):  
Epileptic Seizure ◽  
Filter Bank ◽  
Nonlinear Least Squares ◽  
Signal Classification ◽  
Eeg Signal ◽  
Wavelet Filter ◽  
Biorthogonal Wavelet ◽  
Time Frequency ◽  
Wavelet Filter Bank ◽  
Eeg Signal Classification

Multi-category EEG signal classification developing time-frequency texture features based Fisher Vector encoding method

2016 ◽  
Vol 218 ◽  
pp. 251-258 ◽  
Author(s):  
Ömer F. Alçіn ◽  
Siuly Siuly ◽  
Varun Bajaj ◽  
Yanhui Guo ◽  
Abdulkadir Şengu¨r ◽  
...  
Keyword(s):  
Texture Features ◽  
Signal Classification ◽  
Eeg Signal ◽  
Time Frequency ◽  
Fisher Vector ◽  
Fisher Vector Encoding ◽  
Eeg Signal Classification ◽  
Encoding Method

scholarly journals Dissimilarity-based time–frequency distributions as features for epileptic EEG signal classification

2021 ◽  
Vol 64 ◽  
pp. 102268
Author(s):  
Y. Ech-Choudany ◽  
D. Scida ◽  
M. Assarar ◽  
J. Landré ◽  
B. Bellach ◽  
...  
Keyword(s):  
Signal Classification ◽  
Eeg Signal ◽  
Frequency Distributions ◽  
Time Frequency ◽  
Eeg Signal Classification

scholarly journals Eeg signal classification for epileptic seizure using MATLAB

2019 ◽  
Vol 8 (9) ◽  
pp. 1458-1461
Keyword(s):  
Epileptic Seizure ◽  
Neurological Disorder ◽  
Matrix Algebra ◽  
General Purpose ◽  
Signal Classification ◽  
Eeg Signal ◽  
Eeg Signals ◽  
Computer Aided ◽  
Eeg Signal Classification ◽  
The Brain

Epilepsy is explained as a group of neurological disorder which may be characterized by epileptic seizure within some consequence of unconstraints because of peculiar cortical nerve cell activities in the brain. The manual detection of this disorder by a neurologist is expensive and time consuming also and there may be some loss of accuracy because of fatigue, computer aided approach etc. This work has proposed a method which is highly efficient and gives accurate results over electroencephalogram signals for epilepsy. MATLAB is a very popular, powerful, general-purpose system or it can be said that it is an general purpose environment for matrix algebra calculations and many other more specific computations. It has various applications in Aerospace, Biology, Finance, data acquisition, etc. Here Matlab is used to classify the EEG signals over some parameters. Here a program is developed in MATLAB to check the condition of signal whether it is healthy or unhealthy

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

2020 ◽  
pp. 220-236
Author(s):  
Dinesh Bhati ◽  
Akruti Raikwar ◽  
Ram Bilas Pachori ◽  
Vikram M. Gadre
Keyword(s):  
Classification Accuracy ◽  
Filter Bank ◽  
Optimality Criteria ◽  
Wavelet Filter ◽  
Eeg Signals ◽  
Time Frequency ◽  
Minimal Time ◽  
Frequency Spread ◽  
Band Filter ◽  
Wavelet Filter Bank

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.

Sign in / Sign up

Export Citation Format

Share Document