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How to predict heart rate?

See original GitHub issue

Could you please tell me whether to obtain the average heart rate it is enough to pass the output of the ordinal regression through the Hanh window, then Butterworth filter and Welch density decomposition, like the get_bpm function suggests?

https://github.com/eugenelet/Meta-rPPG/blob/bab00d97731d07966eaa3ca700be153fac0bd50a/data/data_utils.py#L127

If possible, I would be grateful if you could give an intuitive understanding of what the Butterworth bandpass does, since you use it both in pre-processing and post-processing.

Issue Analytics

  • State:open
  • Created 3 years ago
  • Comments:9 (1 by maintainers)

github_iconTop GitHub Comments

3reactions
aptlincommented, Aug 10, 2020

Increasing the sampling rate to 29 and bumping the block size from 40 to 200, I get the following metrics after estimating heart rate from the ground truth ordinal values:

Screen Shot 2020-08-10 at 14 23 43

Pearson r is still a bit off in comparison with the results from your paper:

Screen Shot 2020-08-10 at 14 27 26
0reactions
Z-Xiongcommented, Nov 9, 2020

How do you train this network and what data sets are used? I use the deap dataset, which is difficult to converge.

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