Comparing wavelet transforms for recognizing cardiac patterns
Résumé
The authors' study made use of wavelet transforms to describe and recognize isolated cardiac beats. The choice of the wavelet family as well as the selection of the analyzing function into these families are discussed. The criterion used in the first case was the correct classification rate, and in the second case, the correlation coefficient between the original pattern and the reconstructed one. Two types of description have been considered-the energy-based representation and the extrema distribution estimated at each decomposition level-and their quality has been assessed by using principal component analysis. Their capability of discrimination between normal, premature ventricular contraction, and ischemic beats has been studied by means of linear discriminant analysis. This work leads also, for the problem at hand, to the identification of the most relevant resolution levels
Mots clés
ECG analysis
cardiac patterns recognition
decomposition level
energy-based representation
extrema distribution
ischemic beats
isolated cardiac beats
normal beats
premature ventricular contractions
principal component analysis
resolution level
wavelet transforms comparison
ECG
PVC
Arrhythmia
classification
detection
wavelet transform
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