Med Biol Eng Comput - Detection of occult paroxysmal atrial fibrillation.

Tópicos

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Resumo

This work introduces a novel approach to the detection of brief episodes of paroxysmal atrial fibrillation (PAF). The proposed detector is based on four parameters which characterize RR interval irregularity, P-wave absence, f-wave presence, and noise level, of which the latter three are determined from a signal produced by an echo state network. The parameters are used for fuzzy logic classification where the decisions involve information on prevailing signal quality; no training is required. The performance is evaluated on a large set of test signals with brief episodes of PAF. The results show that episodes with as few as five beats can be reliably detected with an accuracy of 0.88, compared to 0.82 for a detector based on rhythm information only (the coefficient of sample entropy); this difference in accuracy increases when atrial premature beats are present. The results also show that the performance remains essentially unchanged at noise levels up to [Formula: see text] RMS. It is concluded that the combination of information on ventricular activity, atrial activity, and noise leads to substantial improvement when detecting brief episodes of PAF.

Resumo Limpo

work introduc novel approach detect brief episod paroxysm atrial fibril paf propos detector base four paramet character rr interv irregular pwave absenc fwave presenc nois level latter three determin signal produc echo state network paramet use fuzzi logic classif decis involv inform prevail signal qualiti train requir perform evalu larg set test signal brief episod paf result show episod five beat can reliabl detect accuraci compar detector base rhythm inform coeffici sampl entropi differ accuraci increas atrial prematur beat present result also show perform remain essenti unchang nois level formula see text rms conclud combin inform ventricular activ atrial activ nois lead substanti improv detect brief episod paf

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