Comput. Biol. Med. - A correlation analysis-based detection and delineation of ECG characteristic events using template waveforms extracted by ensemble averaging of clustered heart cycles.

Tópicos

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Resumo

The goal of this study is to introduce a simple, standard and safe procedure to detect and to delineate P and T waves of the electrocardiogram (ECG) signal in real conditions. The proposed method consists of four major steps: (1) a secure QRS detection and delineation algorithm, (2) a pattern recognition algorithm designed for distinguishing various ECG clusters which take place between consecutive R-waves, (3) extracting template of the dominant events of each cluster waveform and (4) application of the correlation analysis in order to delineate automatically the P- and T-waves in noisy conditions. The performance characteristics of the proposed P and T detection-delineation algorithm are evaluated versus various ECG signals whose qualities are altered from the best to the worst cases based on the random-walk noise theory. Also, the method is applied to the MIT-BIH Arrhythmia and the QT databases for comparing some parts of its performance characteristics with a number of P and T detection-delineation algorithms. The conducted evaluations indicate that in a signal with low quality value of about 0.6, the proposed method detects the P and T events with sensitivity Se=85% and positive predictive value of P+=89%, respectively. In addition, at the same quality, the average delineation errors associated with those ECG events are 45 and 63ms, respectively. Stable delineation error, high detection accuracy and high noise tolerance were the most important aspects considered during development of the proposed method.

Resumo Limpo

goal studi introduc simpl standard safe procedur detect delin p t wave electrocardiogram ecg signal real condit propos method consist four major step secur qrs detect delin algorithm pattern recognit algorithm design distinguish various ecg cluster take place consecut rwave extract templat domin event cluster waveform applic correl analysi order delin automat p twave noisi condit perform characterist propos p t detectiondelin algorithm evalu versus various ecg signal whose qualiti alter best worst case base randomwalk nois theori also method appli mitbih arrhythmia qt databas compar part perform characterist number p t detectiondelin algorithm conduct evalu indic signal low qualiti valu propos method detect p t event sensit se posit predict valu p respect addit qualiti averag delin error associ ecg event ms respect stabl delin error high detect accuraci high nois toler import aspect consid develop propos method

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