BSL PRO Software Guide - Biopac

224 Part DRemove trendSometimes, data contains a positive or negativetrend that can cause extraneous frequencycomponents to “leak” into the frequencyspectrum. For example, the following sine wavehas an upward trend through the data (positivetrend component).In this case, you could select remove trend whenyou perform the FFT, which would draw a linethrough the endpoints, and then subtract the trendfrom the waveform.The second screen shows FFTs of the skewedsine wave data with and without the trendremoved:Note that the spectrum of the data without thetrend removal has gradually decreasing frequencycomponents, while the data with the trendremoved has far fewer frequency componentsexcept for the single spike due to the sine wave.without trend removaltrend removedWindowA “window” refers to a computation thatspans a fixed number of adjacent datapoints. Window functions are used toeliminate discontinuities that may result atthe edges of the fixed span of data pointsfor the FFT.To apply a window transformation,check the box next to Window andchoose a type of window from thepull-down menu. Each of the windowshas slightly different characteristics,although in practice each providessimilar results within measurementerror.As noted earlier, the FFT algorithm treats the data as an infinitely repeating signal with a period equal to thelength of the waveform. Therefore, if the endpoint values are unequal, you will get a frequency spectrum withlarger than expected high frequency components due to the discontinuity. Windowing these data minimizes thisphenomenon.As shown here, the frequency spectra of the windowed and non-windowed data differ significantlywhen the endpoints are unequal. When the data are not windowed, the very low and very highfrequencies are not attenuated to the same extent as when the data are windowed.Visit the online support center at www.biopac.com