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  • Author Author: fustini
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Smooth (heart) beats

fustini

Howdy,

 

Thanks to a comment by on my last post, I started thinking that I need to do more averaging to achieve a smoother graph.  It turns out that this is very simple to do as the Arduino sketch writes 30 BPM samples per line to the text file on the SD card.  I created a new script named parse-avg.pl to take the average of every 30 sample set.  This created a graph with less fluctuation:

image

This new averaged data is feed into filter.pl, and a much smoother graph is generated:

image

Here is a comparison with both on a the same plot:

image

So I think the plot of the filtered data now is much easier to interpret.  However, I need to verify that the data is actually still accurate.  I have basic Polar wrist watch receiver which I can use to benchmark.  It doesn't log BPM readings, so I will have to write down the reading 30 sec for a short test run (say 10 minutes).  Then I can graph the written-down wristwatch readings versus the hrmshield filtered data.

 

Cheers,

Drew

  • in reply to DAB

    Thanks for the tips.  Yeah, I'm concerned that by filtering too strongly I'll miss what was actually happening. 

     

    For example, the final peak was from push-ups and jumping jacks.  I know it was more intense than any previous activity.  However, the "filter" plot starts to loose the difference in activity between that and the second to last peak.

     

    I'll try plotting those different functions to contrast.

     

    Thanks,

    Drew

  • Hi Drew,

     

    You may need to play around with your averaging levels before you get the best combination for the data.

    You might take a look at running min, max and average analysis and use a least squares fit to see which gives you a close fit.

    If you over filter, sometimes you can miss critical transitions in the data.

     

    Just a thought,

    DAB