Detecting patterns in waves

Question

I'm trying to read an image from electrocardiography and detect each one of the main waves in it (P wave, QRS complex and T wave). Now I can read the image and get a vector like (4.2; 4.4; 4.9; 4.7; ...) representative of the values in the electrocardiography, which is half of the problem. I need an algorithm that can walk through this vector and detect when each of these waves starts and ends.

Here is an example of one of its graphs:

alt text

It would be easy if they always had the same size, but it's not like it works, or if I knew how many waves the ECG would have, but it can vary too. Does anyone have some ideas?

Thanks!

Answer 1

Your problem looks similar to onset detection, but the problem context is not similar to that. This type of biological signal processing, i.e., detection of the P, QRS, and T phases, that can exploit knowledge of specific time-domain characteristics of every waveforms. 

One approach that works for QRS detection is dynamic time warping. The time-domain characteristics remain invariant, Then it would work remarkably well.

A wavelet-based approach seems most intuitive to me. The wavelets are suited here is that they are useful at parameterizing a wide variety of shapes regardless of time or amplitude scaling. 

Hope this answer helps.

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