A novel framework for noninvasive analysis of short-term atrial activity dynamics during persistent atrial fibrillation

ECG-based representation of atrial fibrillation (AF) progression is currently limited. We propose a novel framework for
a more sensitive noninvasive characterization of the AF substrate during persistent AF. An atrial activity (AA) recurrence
signal is computed from body surface potential map (BSPM) recordings, and a set of characteristic indices is derived from
it which captures the short- and long-term recurrent behaviour in the AA patterns. A novel measure of short- and longterm spatial variability of AA propagation is introduced, to provide an interpretation of the above indices, and to test the
hypothesis that the variability in the oscillatory content of AA is due mainly to a spatially uncoordinated propagation of the
AF waveforms. A simple model of atrial signal dynamics is proposed to confirm this hypothesis, and to investigate a possible
influence of the AF substrate on the short-term recurrent behaviour of AA propagation. Results confirm the hypothesis, with
the model also revealing the above influence. Once the characteristic indices are normalized to remove this influence, they
show to be significantly associated with AF recurrence 4 to 6 weeks after electrical cardioversion. Therefore, the proposed
framework improves noninvasive AF substrate characterization in patients with a very similar substrate.