Since itsinvention by the Dutchman Willem Einthoven (1860–1927) during the late 19th and early 20th centuries, when it was little more than a scientific curiosity, the elec-trocardiogram (ECG) has developed into one of the most important and widely used quantitative diagnostic tools in medicine. It is essential for the identification of disorders of the cardiac rhythm, extremely useful for the ...

This paper presents an efficient method of electrocardiogram signal denoising based on a hybrid approach. Two techniques are brought together to create an efficient denoising process. The first is an Adaptive Dual Threshold Filter (ADTF) and the second is the Discrete Wavelet Transform (DWT). The presented approach is based on three steps of denoising, the DWT decomposition, the ADTF step and t...

We sought to establish pathogenetic links between electrophysiology, histopathology, and ventricular tachyarrhythmias in patients with Ebstein's anomaly. The atrialized right ventricle (ARV) is the site of mechanically inducible ventricular tachyarrhythmias, but relations between the arrhythmogenic substrate, the type of tachyarrhythmias, and the trigger(s) have not been established. This study...

In this paper, a wavelet based methodology is presented for compression of electrocardiogram (ECG) signal. The methodology employs new wavelet filters whose coefficients are derived with beta function and its derivatives. A comparative study of performance of different existing wavelet filters and the Beta wavelet filters is made in terms of compression ratio (CR), percent root mean square diff...

Patients with obstructive sleep apnoea demonstrate an increased rate of ventricular arrhythmias. The present study was designed in order to investigate whether these arrhythmias may be related to myocardial injury, since myocardial injury of various aetiologies has been observed to change the signal averaged electrocardiogram (ECG). Signal averaged ECG was registered in 23 patients with obstruc...

The processing of electrocardiogram signals (ECG) using Hidden Markov Models (HMM) methodology is presented. The proposed framework enables complex ECG signal processing with all the necessary steps resolved by HMM approach. Firstly, general description and comprehensive survey of actual HMM state of art is carried out. Secondly, the ECG processing methods as noise removal, characteristic point...

Abstract Accurate estimation of heart beats from electrocardiogram (ECG) signals during exercise activity is a very challenging problem. Unlike standard ECG, the recorded can affect accuracy QRS detection due to noises and artifacts arise body movements activity. However, most studies on often used clean data for evaluations assumed reflect overall performance detectors. In addition, there are ...