A system includes a pulse generator including a can electrode and a lead couplable to the pulse generator, the lead including a distal coil electrode and a proximal coil electrode, wherein both of the coil electrodes are electrically uncoupled from the can electrode such that a unipolar sensing vector is provided between at least one of the coil electrodes and the can electrode.

A system includes a pulse generator including a can electrode and a lead couplable to the pulse generator, the lead including a distal coil electrode and a proximal coil electrode, wherein both of the coil electrodes are electrically uncoupled from the can electrode such that a unipolar sensing vector is provided between at least one of the coil electrodes and the can electrode.

An implantable system for treating a heart contains a processor, a memory unit, a treatment unit including a treatment electrode, and a detection unit for detecting a cardiac event requiring treatment. The memory unit includes a computer-readable program, which prompts the processor to perform the following steps: a) detecting by way of the detection unit whether a cardiac event to be treated has occurred in the heart; b) if a cardiac event to be treated has occurred, determining a position of the treatment electrode or determining a variable correlating with this position; and c) comparing the position of the treatment electrode or the variable correlating with the position to a reference variable, and carrying out, or not carrying out a cardiac treatment by way of the treatment unit and the treatment electrode as a function of the position of the treatment electrode or the variable correlating with the position.

Techniques are disclosed for detecting arrhythmia episodes for a patient. A medical device may receive one or more sensor values indicative of motion of a patient. The medical device may determine, based at least in part on the one or more sensor values, an activity level of the patient. The medical device may determine a heart rate threshold for triggering detection of an arrhythmia episode based at least in part on the activity level of the patient. The medical device may determine whether to trigger detection of the arrhythmia episode for the patient based at least in part on comparing a heart rate of the patient with the heart rate threshold. The medical device may, in response to triggering detection of the arrhythmia episode, collect information associated with the arrhythmia episode.

Techniques are disclosed for detecting arrhythmia episodes for a patient. A medical device may receive one or more sensor values indicative of motion of a patient. The medical device may determine, based at least in part on the one or more sensor values, an activity level of the patient. The medical device may determine a heart rate threshold for triggering detection of an arrhythmia episode based at least in part on the activity level of the patient. The medical device may determine whether to trigger detection of the arrhythmia episode for the patient based at least in part on comparing a heart rate of the patient with the heart rate threshold. The medical device may, in response to triggering detection of the arrhythmia episode, collect information associated with the arrhythmia episode.

A medical system is provided. The medical system includes a medical device and a mobile computing device. The medical device includes at least one physiologic sensor configured to acquire physiological signals from a patient, at least one processor coupled to the at least one physiologic sensor, and at least one optical code encoded with encrypted data. The mobile computing device includes a camera and one or more processors coupled to the camera and configured to acquire one or more images of the at least one optical code, decode the one or more images of the at least one optical code to generate a copy of the encrypted data, decrypt the copy of the encrypted data to generate decrypted data, and process the decrypted data to establish an operable connection between the mobile computing device and the medical device.

The present invention relates to an electrocardiogram analysis matching support service system that supports timely and real-time analysis of an individual's electrocardiogram, and it is characterized in that it includes: a patient service app module that is installed and executed in a patient's mobile communication terminal, transmits an electrocardiogram measurement data received from a wearable electrocardiogram measurement device, requests for reading, and receives and displays the result of the reading; and a patient and medical staff matching server that reads the electrocardiogram measurement data transmitted from the patient service app module using a deep learning trained artificial intelligence network model, selects pre-registered medical staff according to the result of the reading, and supports reading the electrocardiogram measurement data.

The present invention relates to an electrocardiogram analysis matching support service system that supports timely and real-time analysis of an individual's electrocardiogram, and it is characterized in that it includes: a patient service app module that is installed and executed in a patient's mobile communication terminal, transmits an electrocardiogram measurement data received from a wearable electrocardiogram measurement device, requests for reading, and receives and displays the result of the reading; and a patient and medical staff matching server that reads the electrocardiogram measurement data transmitted from the patient service app module using a deep learning trained artificial intelligence network model, selects pre-registered medical staff according to the result of the reading, and supports reading the electrocardiogram measurement data.

A wearable medical includes a walking detector module with a motion sensor that is configured to detect when the patient is walking or running. In embodiments, a parameter (referred to herein as a “Bouncy” parameter) is determined from Y-axis acceleration measurements. In some embodiments, the Bouncy parameter is a measurement of the AC component of the Y-axis accelerometer signal. This detection can be used by the medical device to determine how and/or whether to provide treatment to the patient wearing the medical device. For example, when used in a WCD, the walking detector can prevent “false alarms” because a walking patient is generally conscious and not in need of a shock.

An example medical device includes a plurality of electrodes, therapy delivery circuitry, and processing circuitry configured to control the therapy delivery circuitry to deliver electrical stimulation to an intercostal nerve of a patient via at least two of the plurality of electrodes, wherein the electrical stimulation is delivered with stimulation parameters configured to suppress ventricular tachyarrhythmia of the patient, wherein the stimulation parameters comprise a stimulation frequency less than or equal to 40 hertz (Hz).