Signal Processing Techniques

We utilized signal processing techniques to create spectograms

  • Because the Muse headset did not record with a consistent sampling rate, we used MATLAB’s resample function to acheive a consistent sampling rate between each reading
  • To remove the noisy signals, we applied a filter to the EEG Data we collected, by subtracting the average signal of each channel from the data
  • A spectrogram was then made using MATLAB’s spectrogram function. Below is an example spectrogram from Trial 27:
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  • This spectrogram shows all EEG Data from the full experiment. To further analyze our data we created spectrograms isolating the concentration control and of high, medium, and low subjective rankings.