Comput. Biol. Med. - Atrial activity extraction from single lead ECG recordings: evaluation of two novel methods.

Tópicos

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Resumo

Two different methods for extracting atrial activity (AA) signal from single lead electrocardiogram (ECG) of atrial fibrillation were proposed. The first one is a weighted average beat subtraction (WABS) method. Coefficients of QRS complexes used for constructing QRS template were obtained by minimizing mean square error. The second method is based on maximum likelihood estimation (MLE). Probability density functions of AA signal and ventricular activity (VA) signals were estimated using generalized Gaussian model. Then AA signal was extracted by maximizing likelihood function. Simulated signal and clinical ECG were used to evaluate the performance of ABS, WABS and MLE-based algorithm. In comparison with ABS, WABS and MLE-based algorithm reduced normal mean square error by 23.5% and 20.2%, respectively.

Resumo Limpo

two differ method extract atrial activ aa signal singl lead electrocardiogram ecg atrial fibril propos first one weight averag beat subtract wab method coeffici qrs complex use construct qrs templat obtain minim mean squar error second method base maximum likelihood estim mle probabl densiti function aa signal ventricular activ va signal estim use general gaussian model aa signal extract maxim likelihood function simul signal clinic ecg use evalu perform ab wab mlebas algorithm comparison ab wab mlebas algorithm reduc normal mean squar error respect

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