I have some 64 channel EEG data sampled at 256Hz and I'm trying to conduct a time frequency analysis for each channel and plot a spectrogram.
The data is stored in a numpy 3d array, where one of the dimensions has length 256, each element containing a microvolt reading over all sampled time points (total length is 1 second for each channel of data)
To be clear: my 3D array is 64*256*913 (electrode * voltages * trial). Trial is just a single trial of an experiment. So what I want to do is take a single electrode, from a single trial, and the entire 1D voltage vector and creating a time-frequency spectrogram. So I want to create a spectrogram plot from data[0,:,0] for example.
For each electrode, I want a plot where the y axis is frequency, x axis is time, and colour/intensity is power
I have tried using this in python:
from matplotlib.pyplot import specgram #data = np.random.rand(256) specgram(data, NFFT=256, Fs=256)
This gives me something that looks like this:
Right off the bat this looks incorrect to me because the axis ranges are incorrect
Furthermore, when I run the same code for all EEG channels, over all of my data, I end up with the exact same plot (even though I have verified that the data is different for each)
I'm pretty new to signal processing, is there somewhere that I went wrong in either how my data is laid out or how I used my function?