Again, my snoring detector:
When I look at the rhythm of snoring vs the rhythm of talking in terms of peaks/events (which would represent snores) per hour, there's not much difference -- they range from roughly 500 to 900 per hour. But it occurred to me that perhaps there's a significant difference in the regularity of the rhythm. In particular, I suspect that talking would have a more irregular rhythm than snoring, and I was wondering what might be some ways to characterize that difference.
Note that this is a bit different from tempo/beat detection in music in that there is no master clock, and individual "beats" are not "skipped" but elongated, so, eg, an autocorrelation would likely not reveal much.
The simplest approach would be to measure standard deviation of the event intervals, but I'm unsure to what extent that would discriminate between apneic breathing (snore, snore, snore, pause, snore) vs simply irregular intervals. And, as you know, my statistics background is weak.
Any other suggestions? (Take as a given that I have already discriminated the "events" and can produce a train of intervals, vs deriving rhythm from raw data.)