I came along quite some papers in the field of biosignal processing which first apply a low-pass or bandpass filter to the recorded signals (to remove high frequency sensor noise, etc.) prior to spectral estimation.
Does this make sense? If I know that for instance the heart rate is between 30 bmp and 200 bmp, why would I not just compute the power spectral density and then look for the max in that very window?
Wouldn't a frequency selective filters skew the estimate (due to roll off and ripples in the pass band)?
The only reason I can think of, where you might want to do this, would be if you knew there was a strong interfering sinusoid, at a frequency in between two DFT frequency bins. Without pre-filtering, the energy due to this interferer would spread over all nearby DFT bins, and might mask/hide weaker signals of interest there. You may gain something if you designed a notch filter to remove the interferer, before doing your spectrum estimation. But yes, the filter may also adversely affect signals of interest.
But you could do the filtering in the frequency domain anyway, after you have computed the spectrum.
In general I would say that your intuition is correct - just look at the band of interest and don't bother filtering.
If You use Digital preconditioner filter prior to Digital spectral estimation, this realy doesnot make any sens.
But if You use Analog preconditioner filter prior to Digital spectral estimation, this does some sens:
The current filter designs are specific to the signals already established for clinical use. If you are doing research and looking for other information then you may simply remove all filters and take a look on the spectrum behavior. Once you spot something of interest to you by intuition, then design a filter for that. It would be a new discovery. Good luck and I wish you success.
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