Adaptive Hierarchical Clustering Based ECG Pattern Classification

Abstract: This paper gives a review of ECG analysis using cross wavelet transform method. The application of the continuous wavelet transform to two time series and the cross examination of the two decompositions reveal localized similarities in time and frequency. Application of the XWT to a pair of data yields wavelet cross spectrum (WCS) and wavelet coherence (WCOH). The algorithm analyzes ECG data utilizing XWT and explores the resulting spectral differences. Hierarchical clustering extracts the parameter(s) from the WCS and WCOH. Empirical tests establish that the parameter(s) are relevant for classification of normal and abnormal cardiac patterns. The accuracy is higher than normal wavelet denoising and threshold based classification Keywords: Hierarchical clustering, wavelet cross spectrum, wavelet coherence,