Extract breaths from respiratory signal, i.e. peak detection I am trying to extract breaths from a respiratory signal, which is essentially peak detection. See the example below for what such a signal looks like. This particular signal looks rather clean, however, lower amplitude noise is very common (both high and low frequencies). 

I have tried the ones mentioned here, however, those seem to require that the height of the peak can be described by its y-value. As you can see below, the signal is very prone to baseline wander, and the top of a peak can very well fall below 0.

Any suggestions for a peak detection algorithm?
I have a slick trick which may do what you want.

Do an exponential smoothing in the forward direction, call it F.

Do an exponential smoothing in the backard direction, call it B.

Take the difference of these two D = (B - F) / 2.  (Rescaling by half isn't necessary)

This will do two things for you:

1) Smooth out the noise

2) Convert peaks (and troughs) to zero crossings, no matter what their height.

You can find details in my blog article "Exponential Smoothing with a Wrinkle".  There is a "ramp up" and "ramp down" zone at the beginning and the end that you should not use.  They are fairly short and their length depends on your smoothing factor.

Hope this helps,

Ced