FPGA implementation of Morlet continuous wavelet transform for EEG analysis

Abstract

This article presents the design and implementation of continuous wavelet transform (CWT) of nonstationary Electroencephalogram (EEG) signals using a Spartan 3AN FPGA. The widely applied Morlet wavelet function was used for obtaining the CWT coefficients. The complex convolutions were executed in Fourier space using simple multipliers. Altium designer was used to import Xilinx FFT core configured in Radix 4. Two VHDL controllers were built to control the FFT core operation (which handles both the FFT-IFFT computations) for the first controller; and the multiplication processes in between for the second one. The results showed that the digital architecture of Morlet wavelet function in Fourier space is very time efficient. By an optimized trade-off between speed and silicon area, the design can produce the wavelet coefficients at all scales of 1024 points EEG signal in approximately 1 msec when it runs at maximum clock speed of 125 MHz.