How to apply PCA (Principal Component Analysis) on ECG signals
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djamaleddine djeldjli
le 1 Août 2017
Modifié(e) : Image Analyst
le 2 Août 2017
Hello.
I have three ECG signals, called X1,X2,X3 for three different leads, and I want apply PCA (Principal Components Analysis) on all of them to find the component which has the least noise.
Could anybody help me?
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Image Analyst
le 1 Août 2017
I assume you looked at the help and tried
coefficients = pca([X1, X2, X3]);
Why did that not work? What went wrong?
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Image Analyst
le 1 Août 2017
Modifié(e) : Image Analyst
le 2 Août 2017
You forgot to attach the .mat files so I can't do anything to help you other than to check the sizes of your vectors and make sure they're in columns and not empty.
I'm attaching an example of how to use PCA to determine principal components of the 3-D color gamut.
If Star (our resident physician) reads this he might tell you if this makes any sense. Even though you can do PCA on something you have to know how to interpret the components you get out. So whether a weighted sum of your different cardiac signal actually means anything meaningful is a good question. I think that, depending on which signals you combine, it may well be meaningless.
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