Abstract: Disclosed are systems, methods, and computer program product for cardiac event risk assessment including for assessing future cardiac risk for a patient. The disclosed systems can include a wearable cardiac sensing device configured to be removably, bodily-attached to the patient, configured to sense signals from a patient and provide the digitized to a processor configured to determine cardiac event risk assessment. In some embodiments, cardiac event risk assessment can be determined based on a cardiovibration classifier, counts or burdens associated with premature ventricular contractions (PVC) patterns, and multi-focal PVCs.

Abstract: A cardiac event monitoring system for applying improved ECG morphological analysis for determining abnormal cardiac events is provided. The system includes a wearable cardiac sensing device including physiological sensors such as ECG electrodes, an ECG digitizing circuit configured to provide digitized ECG signals, and a non-transitory memory configured to store the digitized ECG signals. The system also includes a processor in communication with the wearable cardiac sensing device. The processor is configured to extract a predetermined timeseries of ECG data points from the digitized ECG signals, identify ECG feature data points corresponding to a certain ECG feature, determine a minimum ECG morphological region based on the ECG feature data points, identify one or more measurements corresponding to the certain ECG feature using the minimum ECG morphological region, and determine whether the ECG feature data points correspond to an abnormal cardiac event, based on the one or more measurements.

Abstract: An ECG processing system for identifying noisy ECG data segments is provided. The ECG processing system includes a network interface and a processor. The network interface is configured to receive a first collection of ECG data segments from wearable medical devices associated with a plurality of patients, each wearable medical device of the wearable medical devices being configured to be continuously worn by a patient for an extended period of time. The processor is configured to produce a second collection of ECG data segments from the first collection of ECG data segments that excludes noisy ECG data segments.

Abstract: Systems, methods, and computer program products identify arrhythmias experienced by a patient. A system includes an external wearable heart monitoring device for continuous and long-term monitoring of a patient that includes electrocardiogram (ECG) electrodes and circuitry to sense surface ECG activity and provide ECG channel(s) producing ECG signal(s), a non-transitory computer-readable medium including an arrhythmia classifier including neural network(s), and processor(s). The neural network(s) are trained based on a historical collection of ECG signal portions with annotation data including at least one annotation for each ECG signal portion and based on weight data including a weight for each annotation based on the annotator thereof. The processor(s) receive the ECG signal(s), monitor the ECG signal(s) to detect at least one arrhythmia event based on the arrhythmia classifier, and transmit at least one communication based on the arrhythmia event(s) to a remote computer system.

Abstract: An ECG processing system for identifying noisy ECG data segments is provided. The ECG processing system includes a network interface and a processor. The network interface is configured to receive a first collection of ECG data segments from wearable medical devices associated with a plurality of patients, each wearable medical device of the wearable medical devices being configured to be continuously worn by a patient for an extended period of time. The processor is configured to produce a second collection of ECG data segments from the first collection of ECG data segments that excludes noisy ECG data segments.

Abstract: An ECG processing system for identifying noisy ECG data segments is provided. The ECG processing system includes a network interface and a processor. The network interface is configured to receive a first collection of ECG data segments from wearable medical devices associated with a plurality of patients, each wearable medical device of the wearable medical devices being configured to be continuously worn by a patient for an extended period of time. The processor is configured to produce a second collection of ECG data segments from the first collection of ECG data segments that excludes noisy ECG data segments.

Abstract: An ECG processing system for identifying noisy ECG data segments is provided. The ECG processing system includes a network interface and a processor. The network interface is configured to receive a first collection of ECG data segments from wearable medical devices associated with a plurality of patients, each wearable medical device of the wearable medical devices being configured to be continuously worn by a patient for an extended period of time. The processor is configured to produce a second collection of ECG data segments from the first collection of ECG data segments that excludes noisy ECG data segments.

Abstract: An ECG processing system for identifying noisy ECG data segments is provided. The ECG processing system includes a network interface and a processor. The network interface is configured to receive a first collection of ECG data segments from wearable medical devices associated with a plurality of patients, each wearable medical device of the wearable medical devices being configured to be continuously worn by a patient for an extended period of time. The processor is configured to produce a second collection of ECG data segments from the first collection of ECG data segments that excludes noisy ECG data segments.