Friday, 21 January 2022

An Artificial Neural Network Model for Classification of Epileptic Seizures Using Huang-Hilbert Transform

Shaik.Jakeer Husain1 and Dr.K.S.Rao2

1Dept. of Electronics and Communication Engineering , Vidya Jyothi Institute of Technology, Hyderabad India

ABSTRACT

Epilepsy is one of the most common neurological disorders characterized by transient and unexpected electrical disturbance in the brain. In This paper the EEG signals are decomposed into a finite set of band limited signals termed as Intrinsic mode functions. The Hilbert transom is applied on these IMF’s to calculate instantaneous frequencies. The 2nd,3rd and 4th IMF's are used to extract features of epileptic signal. A neural network using back propagation algorithm is implemented for classification of epilepsy. An overall accuracy of 99.8% is achieved in classification.

KEYWORDS

Electroencephalogram(EEG),Hilbert-Huang transform(HHT), Instantaneous frequency (ifs), intrinsic mode function (IMF) 

Original Source URL: https://airccse.org/journal/ijsc/papers/5314ijsc03.pdf

https://airccse.org/journal/ijsc/current2014.html





No comments:

Post a Comment

February Issue Journal! Authors are invited to submit papers!

International Journal on Soft Computing (IJSC) ISSN: 2229 - 6735 [Online]; 2229 - 7103 [Print] https://airccse.org/journal/ijsc/ijsc.html He...