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 map corresponding at least partially to the 2D map. The resulting velocity vector map maybe employed to classify a patient as one of an A-type patient, a B-type patient, and a C-type patient, and to guide therapy subsequently delivered to the patient. 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.

A computer implemented method and system for confirming a device documented arrhythmia in cardiac activity are provided. The method is under control of one or more processors configured with executable instructions. The method obtains a cardiac activity (CA) data set that includes CA signals for a series of cardiac events and includes device documented (DD) markers within the series of cardiac events. The device documented markers are indicative of atrial fibrillation (AF) detected by the ICM utilizing an on-board R-R interval irregularity (ORI) process to analyze the CA signals. The method applies a feature enhancement function to the CA signals to form modified CA signals with enhanced sinus features and analyzes the enhanced sinus features in the modified CA signals. The method utilized a confirmatory feature detection process to identify false AF detection by the ORI process. The method records a result of the analysis identifying false AF detection by the ORI process.

A catheter may be adapted to map a chamber of the heart. The catheter may include a magnetic and/or ultrasound sensor for navigation. The body of the catheter may be pliable and configured to form a predetermined shape upon exiting a catheter sheath. Upon exiting the catheter sheath, the catheter body may be configured to form one or more loops, and the loops may be non-overlapping loops. In some examples, the non-overlapping loops may be concentric loops. Alternatively, the catheter body may be configured to form one or more splines. The catheter body may include an embedded electrode assembly. The electrodes of the electrode assembly may be may be arranged in one or more rows and configured to detect a wave front. The electrode assembly may also be configured to generate and activation sequence and determine a direction of an activation source. The electrode assembly may also be configured to determine the type of activation source, for example a rotational activation source, a focal activation source, and a single-wide activation source.

An ambulatory medical device including a plurality of sensing electrodes and one or more processors operably coupled to the plurality of sensing electrodes is provided. Each sensing electrodes is configured to be coupled eternally to a patient and to detect one or more ECG signals. The one or more processors are configured to receive at least one electrode-specific digital signal for each of the plurality of sensing electrodes, determine a noise component for each of the electrode-specific digital signals, analyze each of the noise components for each of the plurality of sensing electrodes, generate electrode matching information for each sensing electrode of the plurality of sensing electrodes based upon analysis of each of the noise components, determine one or more sensing electrode pairs based upon the electrode matching information, and monitor each of the one or more sensing electrode pairs for ECG activity of the patient.

A computer implemented method and system for confirming a device documented arrhythmia in cardiac activity are provided. The method is under control of one or more processors configured with executable instructions. The method obtains a cardiac activity (CA) data set that includes CA signals for a series of cardiac events and includes device documented (DD) markers within the series of cardiac events. The device documented markers are indicative of atrial fibrillation (AF) detected by the ICM utilizing an on-board R-R interval irregularity (ORI) process to analyze the CA signals. The method applies a feature enhancement function to the CA signals to form modified CA signals with enhanced sinus features and analyzes the enhanced sinus features in the modified CA signals. The method utilized a confirmatory feature detection process to identify false AF detection by the ORI process. The method records a result of the analysis identifying false AF detection by the ORI process.

A method for adjusting parameters of a medical device includes collecting patient data by using the medical device, in which the medical device includes programmable parameters for affecting a function carried out by the medical device, transmitting the patient data to an external device, conducting an analysis of the transmitted patient data by using the external device, and providing an automatically computed proposal for adjusting at least one parameter, several parameters or all of the parameters based on the analysis. A corresponding system is also provided.

A dashboard centered around arrhythmia or atrial fibrillation tracking is provided. The dashboard includes a heart or cardiac health score that can be calculated in response to data from the user such as their ECG and other personal information and cardiac health influencing factors. The dashboard also provides to the user recommendations or goals, such as daily goals, for the user to meet and thereby improve their heart or cardiac health score. These goals and recommendations may be set by the user or a medical professional and routinely updated as his or her heart or cardiac health score improves or otherwise changes. The dashboard is generally displayed from an application provided on a smartphone or tablet computer of the user.

In accordance with some non-limiting examples of the disclosed subject matter, an ingestible system configured to acquire physiological information from an interior of a subject is provided, comprising a substrate and at least one physiological sensor. The at least one physiological sensor can be coupled to the substrate and configured to capture physiological data from at least one of an internal area or an orientation in a digestive tract of the subject. The system can include a controller coupled to the substrate and configured to receive the physiological data and prepare the physiological data for one of transmission from the subject or analysis of the physiological data. The substrate, including the at least one physiological sensor and the controller coupled thereto can be configured to self-orient within the digestive tract of the subject, during ingestion of the system by the subject.

A myocardial excitation complementation/visualization apparatus includes an acquiring section that acquires intracardiac electrocardiograms of a subject, the intracardiac electrocardiograms being recorded by a recording unit having a plurality of electrodes, a processing section that performs a computation for completing and visualizing a state of excitation in a myocardium of the subject based on the intracardiac electrocardiograms, and a displaying section that displays the state of excitation in the myocardium of the subject based on an output of the processing section. The processing section includes a first generating section, a correcting section, a second generating section, and a third generating section. The displaying section displays a change of the state of excitation in the myocardium of the subject based on the visualized data.

Methods, systems, and devices for signal analysis in an implanted cardiac monitoring and treatment device such as an implantable cardioverter defibrillator. In some examples, captured data including detected events is analyzed to identify likely overdetection of cardiac events. In some illustrative examples, when overdetection is identified, data may be modified to correct for overdetection, to reduce the impact of overdetection, or to ignore overdetected data. Several examples emphasize the use of morphology analysis using correlation to static templates and/or inter-event correlation analysis.