Systems, devices, components and methods for detecting the locations of sources of cardiac rhythm disorders in a patient's heart

Abstract

Disclosed are various examples and embodiments of systems, devices, components and methods configured to detect a location of a source of at least one cardiac rhythm disorder in a patient's heart. In some embodiments, electrogram signals are acquired from a patient's body surface, and subsequently normalized, adjusted and/or filtered, followed by generating a two-dimensional spatial map, grid or representation of the electrode positions, processing the amplitude-adjusted and filtered electrogram signals to generate a plurality of three-dimensional electrogram surfaces corresponding at least partially to the 2D map, one surface being generated for each or selected discrete times, and processing the plurality of three-dimensional electrogram surfaces through time to generate a velocity vector or other type of map using one or more of optical flow, video tracking analysis, motion capture analysis, motion estimation analysis, data association and segmentation tracking analysis, particle tracking analysis, and single-particle tracking analysis methods corresponding at least partially to the 2D map. Trained atrial discriminative machine learning models that facilitate the foregoing systems and methods, and that provide predictions or results concerning a patient's condition, are also disclosed.