BSL PRO Software Guide - Biopac

225The raw data, prior to FFT:This electroencephalogram (EEG) signal wasacquired as the subject alternated betweeneyes open and eyes closed states. Typicalresults suggest that higher levels of alphaactivity (with frequency components between8Hz and 13Hz) are to be expected when asubject’s eyes are closed.FFT EXAMPLEEyes Eyesopen EyesopenclosedTo perform the FFT:1) Click the Transform menu and scroll toselect FFT.This will generate the FFT Parametersdialog.2) Establish the FFT parameters (theWindow type used here is KaiserBessel, butyou could choose any type).3) Click OK.4) A frequency domain window (a graphwindow that places frequency rather thantime along the horizontal axis) will begenerated, showing the spectrum of the inputdata. The window is named “Spectral of (theoriginal window name)” and ends with thechannel number, as shown here. Theresulting magnitude value for eachcomponent is equal to the peak value of thesine wave contributing to that component.The entire pattern of frequency componentsis known as the frequency spectrum of thedata. The somewhat erratic appearance of thespectrum is usually due to small-scalevariations in the original waveform. This“noise” can be removed by applying asmoothing transformation to the FFT output.In this example, there is a pronouncedfrequency component centered on 8Hz,which corresponds to the alpha wavefrequency band (8Hz - 13Hz). The frequencyspectrum (0-20 Hz shown) used 20-pointsmoothing.