how to do ecg classifications

Hi

i'm working on ECG Signal (Myocardial Infarction classification),i extract many feature using DWT,variance,mean.... from different Myocardial Infarction classes... what should i use on my next step to distinguish between those classes?

Answer 1

[Luuk van Oosten]

Dear Khouloud Daboussi,

If you now have a big table with all your features (DWT, variance, mean, etc) and the myocardial infarction classes, you could have a look at different types of classification algorithms that MATLAB provides in the classificationLearner app. Check the related documentation and examples of the classificationLear by clicking here.

Simply type

classificationLearner

and play around with the different classification algorithms and see which ones work best on your data set.

[khouloud daboussi]

thank you, I have another question If you don't mind. I have problems with power line filtering, can you suggest any specific filter?

[Luuk van Oosten]

Do you mean this? Credits should go here in that case, cause I had to google it myself.

If you have additional questions about the power line filtering, I suggest making a new question, so it will be easier for others to find, comment, and answer on.

Answer 2

[khouloud daboussi]

Thanx! That could be helpful

Answer 3

[Gonzalo]

you could aso look at these examples

https://www.mathworks.com/help/deeplearning/examples/waveform-segmentation-using-deep-learning.html

and

https://www.mathworks.com/help/wavelet/examples/ecg-signal-classification-using-wavelet-time-scattering.html

which use wavelets and deep learning to segment an ECG signal or classify it from raw data directly.