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I am currently doing analysis on Photoplethysmograph (PPG) data and I want to know the frequency (heart rate) at every time point so a windowed FFT might not be the best option. I am looking at wavelet to generate frequency and time information. I have been working with matlab example code however I have trouble determining what is the best wavelet to use for this application. I do now know much about wavelet. Does the wavelet used being dictated by the shape of my signal. In my case PPG signal which looks like this:

http://home.lu.lv/~spigulis/PPG-bios02_files/image004.gif

Or some other consideration is needed when choosing wavelet? How critical is the choice of wavelet?

Thanks, Kelvin

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What information are you trying to extract from your signal?

I want to know the frequency (heart rate) at every time point

If this is the information you want then any sort of frequency analysis is unlikely to be very useful. It will show you that you have a 1 or 2 hz periodic signal with a particular frequency profile, but you already know all of this information so that won't be especially illuminating.

You are probably better off with peak detection, or local minima/maxima detection to extrapolate beats.

If you can provide a sample of your data, and/or more details about the exact information you are trying to extract then it will help us to find a more precise solution to your problem.

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  • $\begingroup$ Hi PAK-9. Basically my concern is that a moving window FFT is not good enough to track fast changing in frequency (heart rate) of my signal. Hence the idea of implementing wavelet transform for better time-frequency analysis. I can put up some sample data at the end of the day but the SNR of my sample is usually very low so peak detection didnt work well. $\endgroup$ – KelvinIPE Sep 3 '14 at 2:31

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