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Atrial fibrillation (AF) is one of the most common cardiac arrhythmia and it is mainly characterized by the presence of random RR intervals. In this way, atrial fibrillation has been studied as a stochastic process and it has been often modeled through Markov chains. Following previous studies on this subject, this work models time sequences of heartbeats as a three states Markov process for AF automatic detection. The model was trained and developed using signals from MIT-BIH database. Another consolidated method for AF detection, called “RR Ratios”, was also applied to compare Markov Model’s results. The performance evaluation of both methods was measured through sensitivity (Se) and positive predictive (+P) for AF detection. These two methods – Markov Model and “RR Ratio” – had their coefficients and thresholds optimized in order to maximize the values of Se and +P at the same time. After optimization, both methods were tested with another database, independent of development database. The obtained results were Se = 84,940% and +P = 81,579%, consolidating Markov Models for detecting random heartbeats. LISTA DE ABREVIATURAS E SIGLAS A Batimento Prematuro Atrial AAMI Association for the Advancement of Medical Instrumentation AFIB Fibrilação Atrial AV Nodo Átrio-Ventricular BIH Beth Israel Hospital BPV Batimento Prematuro Ventricular ECG Eletrocardiograma FA Fibrilação Atrial IRV Ritmo Idioventricular J Batimento Prematuro Juncional LA Left Arm LL Left Leg MIT Massachusetts Institute of Technology N Batimento Normal ou Ritmo Sinusal Normal NOD Ritmo Juncional AV +P Valor Preditivo Positivo RA Right Arm S Batimento Prematuro Supraventricular SA Nodo Sino-Atrial Se Sensibilidade T Trigeminismo V Batimento Prematuro Ventricular VT Taquicardia Ventricular 1 Estas siglas correspondem às marcações de arritmia realizadas pela base de dados MIT/BIH [18].

Detecção automática de fibrilação atrial através de modelos Markovianos.