A system and method for detecting and verifying bradycardia/asystole episodes includes sensing an electrogram (EGM) signal. The EGM signal is compared to a primary threshold to sense events in the EGM signal, and at least one of a bradycardia or an asystole is detected based on the comparison. In response to detecting at least one of a bradycardia or an asystole, the EGM signal is compared to a secondary threshold to sense events under-sensed by the primary threshold. The validity of the bradycardia or the asystole is determined based on the detected under-sensed events.

The present disclosure relates to a wearable monitor device and methods and systems for using such a device. In certain embodiments, the wearable monitor records cardiac data from a mammal and extracts particular features of interest. These features are then transmitted and used to provide health-related information about the mammal.

This document discusses, among other things, systems and methods to determine an indication of contractility of a heart of a patient using received physiologic information, and to determine blood pressure information of the patient using the heart sound information and the determined indication of contractility of the heart. The system can include an assessment circuit configured to determine an indication of contractility of a heart of the patient using first heart sound (S1) information of the patient, and to determine blood pressure information of the patient using second heart sound (S2) information of the patient and the determined indication of contractility of the heart.

An electrocardiogram (ECG) system is provided. The system includes an ECG device capable of receiving ECG signals from a lead system attached to the user. The ECG device then renders the ECG signals into ECG data, and transmits the ECG data to at least one of a user device, such as a smart phone, or a cloud-based storage system. The user device is capable of rendering the ECG data into an ECG graph, and displaying the ECG graph to the user on an application (app). The system also provides for a cloud-based storage system capable storing the ECG data and providing access to the ECG data to the user and to medical personal.

Physiological monitoring can be provided through a wearable monitor that includes two components, a flexible extended wear electrode patch and a removable reusable monitor recorder. The wearable monitor sits centrally (in the midline) on the patient's chest along the sternum oriented top-to-bottom. The placement of the wearable monitor in a location at the sternal midline (or immediately to either side of the sternum) benefits extended wear by removing the requirement that ECG electrodes be continually placed in the same spots on the skin throughout the monitoring period. Instead, the patient can place an electrode patch anywhere within the general region of the sternum. Ensuring that the quality level of ECG recording remains constant over an extended period of time is provided through self-authentication of electrode patches. The monitor recorder implements a challenge response scheme upon being connected to an electrode patch. Failing self-authentication, the monitor recorder signals an error condition.

Catheterization is carried out by inserting a sheath into a human patient and moving a catheter having an electrode through the sheath lumen. A variation between a first threshold value and a second threshold value in electrical current through the electrode is identified. Responsively to the variation, it is reported that a portion of the catheter has transitioned between an in-sheath condition and an out-of-sheath condition. The sheath is defined and identified by the historical data of the readings of the magnetic sensor during its movements.

Cardiac activity (e.g., a cardiac electrogram) is analyzed for local abnormal ventricular activity (LAVA), such as by using a LAVA detection and analysis module incorporated into an electroanatomical mapping system. The module transforms the electrogram signal into the wavelet domain to compute as scalogram; computes a one-dimensional LAVA function of the scalogram; detects one or more peaks in the LAVA function; and computes a peak-to-peak amplitude of the electrogram signal. If the peak-to-peak amplitude does not exceed a preset amplitude threshold, then the module can compute one or more of a LAVA lateness parameter for the electrogram signal using one of the one or more peaks detected in the LAVA function and a LAVA probability parameter for the electrogram signal.

Systems and methods for guiding a sensor to a location of a propagating wave source. The methods comprise: receiving, by the computing device, a plurality of signals generated by a plurality of electrodes of the sensor while the sensor resides at the first location in the object; processing, by the computing device, the plurality of signals to determine coordinates of an estimated location of the propagating wave source relative to the first location at which the sensor resides; and providing a visual aid facilitating sensor movement by plotting a dot on a grid overlaid on top of an object image displayed by the computing device.

One example of a device includes a sensor, a memristor code comparator, and a controller. The sensor is to provide a sensor signal. The memristor code comparator is to compare the sensor signal to a reference signal. The controller is to determine a status of the sensor signal based on the comparison.

A system for providing information about a patient's heart, the system including one or more catheters that receive intracardiac signals from electrical activity of the heart over one or more heart beat cycles and an electronic processor coupled to the one or more catheters. The electronic processor to: receive the intracardiac signals from the one or more catheters; preprocess the intracardiac signals to provide preprocessed signals, wherein each of the intracardiac signals is preprocessed to provide a corresponding preprocessed signal; and compare the preprocessed signals to a set of signals to determine a degree of similarity between each of the preprocessed signals and the set of signals.