FPQA Implementation of Huang Hilbert Transform for Classification of Epileptic Seizures Using Artificial Neural Network

G.Deepika1 and K.S.Rao2

1Research scholar at JNTU,Hyderabad , Asso.Prof at RRS college of Engg,

2Director & Professor in ECE Dept,Anurag group of Institutions, Hyderabad

ABSTRACT

The most common brain disorders due to abnormal burst of electrical discharges are termed as Epileptic seizures. This work proposes an efficient approach to extract the features of epileptic seizures by decomposing EEG into band limited signals termed as IMF’s by empirical decomposition EMD. Huang Hilbert Transform is applied on these IMF’s for calculating Instantaneous frequencies and are classified using artificial neural network trained by Back propagation algorithm. The results indicate an accuracy of 97.87%. The algorithm is implemented using Verilog HDL on Zynq 7000 family FPGA evaluation board using Xilinx vivado 2015.2 version.

KEYWORDS

EEG, IMF,EMD

ORIGINAL SOURCE URL: https://aircconline.com/vlsics/V10N3/10319vlsi02.pdf

http://airccse.org/journal/vlsi/vol10.html