I am trying to detect some events on this signal :

enter image description here

This is the acceleration of someone running. By eyes we can detect many blocs, sometimes separated by a little interval. I would like to be able to detect automatically all those blocs. With this post, it helped me detect those blocks if the signals is less noisy. But if the signal is really noisy and intervals between blocks are really short I can not use the idea of that post (as known force value above a threshold to be 1 and take parts when we find 100 consecutive values of 1 for exemple).

Any documentation or info could be useful... :)

  • $\begingroup$ You are asking two questions, both of which are quite broad: how to detect the blocks, and what is autocorrelation. You're likely to attract more helpful answers if you can ask one specific question, pinpointing what you know, what you don't, what you are expect to obtain, and what you're actually obtaining. $\endgroup$ – MBaz Jul 27 '16 at 13:59
  • $\begingroup$ Having admitted that your samples are "noisy", have you tried filtering them to see if a more "detectable" pattern emerges? $\endgroup$ – Mark Jul 27 '16 at 23:14
  • $\begingroup$ yes I did with low pass filter at 5Hz and also high pass at 5Hz (using a spectral analysis in the first place). But between blocks it still quiet noisy. I was thinking if it' possible to have a spectral analysis for each sample ? Thank you. @Mark $\endgroup$ – YLM Jul 28 '16 at 7:22

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