Using a comb filter to reduce noise/amplitude?
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My goal is to reduce the signal's noise and amplitude using comb,fir, or iir filters. I'm not sure where to start as it is not one particular frequency.
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Star Strider
2014-9-26
You seem to be filtering an EEG, so there must be a band of specific frequencies you’re interested in. I would use a bandpass filter to include those frequencies and exclude those you’re not interested in.
There are several possibilities, of which the Butterworth design might be the best for most biomedical signals. Decide the frequencies you want to study (perhaps 0.5 to 15 Hz), design your filter with buttord, butter, then tf2sos or zp2sos (the second-order-section representation being more stable), then filtfilt to filter your signal. (The low frequency cutoff of 0.5 Hz removes baseline drift and DC offset.)
I always use freqz to assess the characteristics of a filter before actually using it, to be certain it has the characteristics I want it to have.
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Star Strider
2014-9-27
The problem is that the waveform itself is meaningless without the time vector, even if it’s from a subject without any known pathology. (There are normal ranges, but no normal constants.) When I do an FFT, I can’t find anything like a 50-60 Hz peak that I might normally use to figure out the frequency. I searched PubMed and could find no common sampling frequency for EEG. They ranged from 1-5 KHz. I have no idea what yours could be.
It’s not possible to design a correct filter without knowing the sampling frequency, especially with a signal that appears to have broadband noise. It might be possible to de-noise it somewhat with wavelets, but without the sampling time vector it would still be clinically meaningless.
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