A quantum spin liquid (QSL) electrophysiology device comprising a spontaneous and an induced quantum arrhythmia vacuum states, switchable between them through at least one entangled measurement of one negative differential resistance.

A quantum spin liquid (QSL) electrophysiology device comprising a spontaneous and an induced quantum arrhythmia vacuum states, switchable between them through at least one entangled measurement of one negative differential resistance.

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.

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.

Devices, systems, and methods for treating cardiac arrhythmia are disclosed herein. In some embodiments, devices, systems, and methods disclosed herein deliver interrogating energy to tissue at a position on a wall of an anatomical structure of a patient. If the devices, systems, and methods disclosed herein detect a change in electrical activity of the anatomical structure in response to the interrogating energy, the devices, systems, and methods disclosed herein can apply irreversible therapy to the tissue. In some embodiments, the change in electrical activity corresponds to slowing or termination of a detected arrhythmia

Devices, systems, and methods for treating cardiac arrhythmia are disclosed herein. In some embodiments, devices, systems, and methods disclosed herein deliver interrogating energy to tissue at a position on a wall of an anatomical structure of a patient. If the devices, systems, and methods disclosed herein detect a change in electrical activity of the anatomical structure in response to the interrogating energy, the devices, systems, and methods disclosed herein can apply irreversible therapy to the tissue. In some embodiments, the change in electrical activity corresponds to slowing or termination of a detected arrhythmia

A method includes receiving a set of data points including positions and respective velocities of an activation wave in a tissue region of a cardiac chamber. The set is partitioned into at least two velocity clusters, each velocity cluster characterized by a respective velocity of the activation wave. One or more border curves are estimated, between the at least two clusters. The one or more border curves are indicated to a user as possible lines of block of the activation wave.

A method includes receiving a set of data points including positions and respective velocities of an activation wave in a tissue region of a cardiac chamber. The set is partitioned into at least two velocity clusters, each velocity cluster characterized by a respective velocity of the activation wave. One or more border curves are estimated, between the at least two clusters. The one or more border curves are indicated to a user as possible lines of block of the activation wave.

A method includes receiving intracardiac electrogram (IEGM) signals measured at a plurality of locations in a region of a heart that contains a His bundle of the heart. The IEGM signals are processed to find respective local activation time (LAT) values. A cluster of the locations is identified at which peaks associated with the LAT values occur later than a defined time. Respective time differences are calculated between times of occurrence of the associated peaks and a reference time. The time differences are compared to a threshold value to retain locations for which the time differences are below the threshold value. The respective IEGM signals are filtered to identify respective high-frequency peaks in the IEGM signals. The high-frequency peaks are cross-corelated to identify a subset of the locations whose high-frequency peaks meet a predefined cross-correlation level. The high-frequency peaks are tagged as His peaks and indicated on a cardiac map.

A method includes receiving intracardiac electrogram (IEGM) signals measured at a plurality of locations in a region of a heart that contains a His bundle of the heart. The IEGM signals are processed to find respective local activation time (LAT) values. A cluster of the locations is identified at which peaks associated with the LAT values occur later than a defined time. Respective time differences are calculated between times of occurrence of the associated peaks and a reference time. The time differences are compared to a threshold value to retain locations for which the time differences are below the threshold value. The respective IEGM signals are filtered to identify respective high-frequency peaks in the IEGM signals. The high-frequency peaks are cross-corelated to identify a subset of the locations whose high-frequency peaks meet a predefined cross-correlation level. The high-frequency peaks are tagged as His peaks and indicated on a cardiac map.