Abstract: A system is provided for augmenting a three-dimensional (3D) model of a heart to indicate the tissue state. The system accesses a 3D model of a heart, accesses two-dimensional (2D) images of tissue state slices of the heart, and accesses source location information of an arrhythmia. The system augments the 3D model with an indication of a source location based on the source location information. For each of a plurality of the tissue state slices of the heart, the system augments a 3D model slice of the 3D model that corresponds to that tissue state slice with an indication of the tissue state of the heart represented by the tissue state information of that tissue state slice. The system then displays a representation of the 3D model that indicates the source location of the arrhythmia and the tissue state of the heart.

Abstract: A system is provided for augmenting a three-dimensional (3D) model of a heart to indicate the tissue state. The system accesses a 3D model of a heart, accesses two-dimensional (2D) images of tissue state slices of the heart, and accesses source location information of an arrhythmia. The system augments the 3D model with an indication of a source location based on the source location information. For each of a plurality of the tissue state slices of the heart, the system augments a 3D model slice of the 3D model that corresponds to that tissue state slice with an indication of the tissue state of the heart represented by the tissue state information of that tissue state slice. The system then displays a representation of the 3D model that indicates the source location of the arrhythmia and the tissue state of the heart.

Abstract: A system for generating an encoding of a lead of electrocardiogram (ECG) represented as an ECG image. The system identifies a reference pulse of the ECG image having a reference width pixel count, a reference height pixel count, a reference time, and a reference voltage. The system identifies a baseline pixel-row of a plotline of the ECG image that contains a graph of the lead. The system encodes per-pixel timing information based on the reference time and the reference width pixel count. The system, for a plurality of pixel-columns, identifies a voltage pixel-row of that pixel-column that has an ECG value of the graph and encodes a voltage based on distance between the baseline pixel-row and the voltage pixel-row and based on the reference voltage and the reference height pixel count.

Abstract: A system is provided for augmenting a three-dimensional (3D) model of a heart to indicate the tissue state. The system accesses a 3D model of a heart, accesses two-dimensional (2D) images of tissue state slices of the heart, and accesses source location information of an arrhythmia. The system augments the 3D model with an indication of a source location based on the source location information. For each of a plurality of the tissue state slices of the heart, the system augments a 3D model slice of the 3D model that corresponds to that tissue state slice with an indication of the tissue state of the heart represented by the tissue state information of that tissue state slice. The system then displays a representation of the 3D model that indicates the source location of the arrhythmia and the tissue state of the heart.

Abstract: Methods and systems for analyzing and treating digestive disorders (including gastrointestinal disorders) are provided. A system provides various technologies (e.g., machine learning and simulations) to support such analysis and treatment of digestive disorders. The system may employ computational modeling of the digestive system based on anatomical characteristics and electrical characteristics of the digestive system to simulate motion and electrical activity. The system generates representations of the electrical activity such as an electrogastrogram and generates mappings of the representations to characteristic values of the simulations. The system may train a machine learning model based on the mappings. When treating a patient, the mappings and/or the machine learning model may be employed to identify a patient characteristic based on a patient representation of electrical activity collected from the patient.

Abstract: A method is provided for treating a patient with an arrhythmia. In some embodiments, the method collects a first patient arrhythmia cardiogram from the patient. The method identifies a first target location and a first ablation pattern associated with a first library arrhythmia cardiogram that is similar to the first patient arrhythmia cardiogram. The method then performs a first ablation near the first target location, factoring in the first ablation pattern, and after the ablation, collects a second patient arrhythmia cardiogram of the patient. The method continues to identify a second target location and a second ablation pattern associated with a second library arrhythmia cardiogram that is similar to the second patient arrhythmia cardiogram. The second library arrhythmia cardiogram is identified, in part, based on ablation characteristics of the first ablation. The method then performs a second ablation near the second target location, factoring in the second ablation pattern.

Abstract: A system for guiding implantation of an energy delivery component of a cardiac pacing device at a fixation location within a heart of a patient is provided. During a procedure to implant an energy pulse delivery component, the system receives a patient cardiogram collected during pacing of the energy pulse delivery component while the energy pulse delivery component is positioned at a current location within the heart. The system then determines based on the patient cardiogram the current location of the energy pulse delivery component. The system then outputs an indication of the current location to guide affixing of the energy pulse delivery component at the intended fixation location. This process is repeated until the energy pulse delivery component is at the fixation location. The system also evaluates the effectiveness of pacing at intermediate location to optimize the final location based upon simulated electro-mechanics of the system in near-real time.