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What is Arrhythmia Classification Using WKNN about?

This study presents a new method for classifying arrhythmias using a combination of principal component analysis (PCA) and linear discriminant analysis (LDA) features, along with a weighted k-nearest neighbor (WKNN) algorithm and fitness rules to improve classification accuracy. The method effectively preprocesses ECG signals to remove noise, extracts relevant features, and achieves high sensitivity (97.57%) and specificity (99.42%) in arrhythmia detection. The results indicate that combining PCA and LDA fe

Author

Ashis Kumar Das

Language

EN