You can find a good description of the current detection and segmentation of the heart rate on the Padirac Innovation web site:
https://padiracinnovation.org/2017/06/15/heart-beat-detection-and-segmentation/
Why is segmentation so important? Because we want to be able to explain our classification result. This means that we share understanding and vocabulary with cardiologists. This is opposed to current approaches to deep learning like "deep forest" that fit their internal model with features that might be only remotely connected to the physiology.
Why is it important to be able to understand what is going on at physiological level? Because the horror stories here are studies that claim to be able to predict with 98% accuracy re-hospitalization next year in diseases such as diabetes or heart failure, simply by looking at medical records. Obviously one does not need deep forest algorithms to predict that someone with a HF condition will be re-hospitalized next year.
We must make credible statements, if we want MDs and scientists to take us seriously.
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