EEG Signal Features Extraction using DWT

Hi, all.

I am currently doing an analysis on an EEG signal. The raw EEG signal has been pre-processed using a band pass filter to its Alpha Band. Then, the pre-processed EEG signal will undergo Feature Extraction using DWT to extract a specific frequency. Following is my code for 1-D DWT, however after the decomposition, the graph plotted was in time domain. I need help on how to convert it to frequency domain?

%DISCRETE WAVELET TRANSFORM, 5 level wavelet db2
waveletFunction = 'db2';
[C,L] = wavedec(ep5,5,waveletFunction);
cD1 = detcoef(C,L,1);                   %NOISY
cD2 = detcoef(C,L,2);                  %Gamma
cD3 = detcoef(C,L,3);                   %Beta
cD4 = detcoef(C,L,4);                   %Alpha
cD5 = detcoef(C,L,5);                   %Delta
cA5 = appcoef(C,L,waveletFunction,5);   %Theta

subplot(6,1,1)
plot(cA5)
title('Approximation Coefficients Theta')
subplot(6,1,2)
plot(cD5)
title('Level 5 Detail Coefficients Delta')
subplot(6,1,3)
plot(cD4)
title('Level 4 Detail Coefficients Alpha')
subplot(6,1,4)
plot(cD3)
title('Level 3 Detail Coefficients Beta')
subplot(6,1,5)
plot(cD2)
title('Level 2 Detail Coefficients Gamma')
subplot(6,1,6)
plot(cD1)
title('Level 1 Detail Coefficients Noise')

Your help will be highly appreciated. Thank you very much.

[thejaswini M S]

hello ,i have difficulty in computing DWT for EEG signals for emotion recognition ...please can i have entire code for computing DWT

Answer 1

[VISHWANATH KOLLIYAVAR]

post the output waveform of this code

Answer 2

[Alla Zwawi]

I think a very easy way to convert the extracted wavelets is to use fourier transform or FFT to get the power spectrum of frequency bands and then plot that.