Morphological Image Analysis: Principles and Applications
Morphological Image Analysis: Principles and Applications
Automated ECG diagnostic P-wave analysis using wavelets
Computer Methods and Programs in Biomedicine
Analyzing ECG for cardiac arrhythmia using cluster analysis
Expert Systems with Applications: An International Journal
Feature extraction for ECG heartbeats using higher order statistics of WPD coefficients
Computer Methods and Programs in Biomedicine
Artificial neural networks for automatic ECG analysis
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
QRS detection based on wavelet coefficients
Computer Methods and Programs in Biomedicine
Unsupervised feature relevance analysis applied to improve ECG heartbeat clustering
Computer Methods and Programs in Biomedicine
A heart disease recognition embedded system with fuzzy cluster algorithm
Computer Methods and Programs in Biomedicine
Check Your Biosignals Here: A new dataset for off-the-person ECG biometrics
Computer Methods and Programs in Biomedicine
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The paper presents an adaptive morphological filter developed using multiscale mathematical morphology (MM) to reject broadband noise from ECG signals without affecting the feature waveforms. As a pre-processing procedure, the adaptive morphological filter cleans an ECG signal to prepare it for further analysis. The noiseless ECG signal is embedded within a two-dimensional phase space to form a binary image and the identification of the feature waveforms is carried out based on the information presented by the image. The classification of the feature waveforms is implemented by an adaptive clustering technique according to the geometric information represented by the image in the phase space. Simulation studies on ECG records from the MIT-BIH and BIDMC databases have demonstrated the effectiveness and accuracy of the proposed methods.