Heartbeat dynamics from a Microcanonical Multifractal approach

Heartbeat dynamics is a complex system. To characterize it properly, advanced nonlinear signal-processing methods are needed. In this context, recent developments on reconstructible signals and multiscale information content have led to the Microcanonical Multifractal Formalism (MMF). The MMF provides signal-analysis techniques particularly suited to heartbeat dynamics. In particular, electrocardiogram signals and electric potential in the endocardium allows detecting slow-changing transitions. Detecting regime transition could be used for early warning and treatment of cardiac arrhythmias. In this context, we present an application to the case of Atrial Fibrillation in which we detect distinctive parameters for the transition matrix.

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