An implantable pacemaker is configured to provide electrical pacing pulses to the heart of a patient. The pacemaker has a pulse generator configured to generate the electrical pacing pulses, at least one pacing electrode to apply the electrical pacing pulses to the heart, a sensing unit configured to sense events of electrical activity of a ventricle of the heart, a sensor configured to measure a signal relating to the patient, and a memory configured to store values of a parameter. The pacemaker is configured to be operated in a first mode to generate a reference curve and to select a target range of values of the parameter corresponding to a desired range of atrioventricular delays. The pacemaker is further configured to be operated in a second mode for approaching the target range.

In some examples, a system can be used for delivering cardiac resynchronization therapy (CRT). The system may include a pacing device configured to be implanted within a patient. The pacing device can include a plurality of electrodes, signal generation circuitry configured to deliver ventricular pacing via the plurality of electrodes, and a sensor configured to produce a signal that indicates mechanical activity of the heart. Processing circuitry can be configured to identify one or more features of a cardiac contraction within the signal, and determine whether the contraction was a fusion beat based on the one or more features.

A system for monitoring and evaluating the ventricular contractility of a heart muscle includes a device for electrically stimulating the heart muscle of a patient, and an extracorporeal blood pressure sensor. A record, responsive to stimulated ventricular contractions, is created by the pressure sensor. The response record is then evaluated to identify a pressure/time, rate-change in arterial pressure (dp/dt) that results within the time duration of a ventricular contraction in a cardiac cycle. In turn, dp/dt is evaluated as an indicator of ventricular contractility and the health of the patient's heart muscle.

An implantable medical device stimulates a human or animal heart. The medical device contains a processor, a memory unit, a His electrode having a first electrode pole configured to detect an electrical signal at a His bundle of a heart, and a further electrode having a further electrode pole configured to detect an electrical signal at a cardiac region of the same heart different from the His bundle. During operation of the device, performing the steps of: measuring electric signals at a His bundle of a heart with the first electrode pole; measuring electric signals at a cardiac region of the same heart different from the His bundle with the further electrode pole; and evaluating intracardiac electrogram signals and/or impedance signals measured between the first electrode pole and the further electrode pole, with the provision that this evaluating does not only contain a determination of an atrial-His bundle transition time.

Medical devices are provided, comprising a medical device and a sensor.

A method is provided. The method includes pacing, by electrodes of a catheter, a heart tissue with pulses. The method includes observing, by the electrodes, a period of electrophysiological repolarization for the heart tissue. The period of electrophysiological repolarization is caused by the pacing. The method also includes measuring, by the electrodes, an electrical signal within the heart tissue after the period of electrophysiological repolarization.

Techniques are disclosed for using feature delineation to reduce the impact of machine learning cardiac arrythmia detection on power consumption of medical devices. In one example, a medical device performs feature-based delineation of cardiac electrogram data sensed from a patient to obtain cardiac features indicative of an episode of arrythmia in the patient. The medical device determines whether the cardiac features satisfy threshold criteria for application of a machine learning model for verifying the feature-based delineation of the cardiac electrogram data. In response to determining that the cardiac features satisfy the threshold criteria, the medical device applies the machine learning model to the sensed cardiac electrogram data to verify that the episode of arrhythmia has occurred or determine a classification of the episode of arrythmia.

Techniques are disclosed for explaining and visualizing an output of a machine learning system that detects cardiac arrythmia in a patient. In one example, a computing device receives cardiac electrogram data sensed by a medical device. The computing device applies a machine learning model, trained using cardiac electrogram data for a plurality of patients, to the received cardiac electrogram data to determine, based on the machine learning model, that an episode of arrhythmia has occurred in the patient and a level of confidence in the determination that the episode of arrhythmia has occurred in the patient. In response to determining that the level of confidence is greater than a predetermined threshold, the computing device displays, to a user, a portion of the cardiac electrogram data, an indication that the episode of arrhythmia has occurred, and an indication of the level of confidence that the episode of arrhythmia has occurred.

A system for synchronizing application of treatment signals with a cardiac rhythm is provided. The system includes a memory that receives and stores a synchronization signal indicating that a predetermined phase such as R-wave of a cardiac rhythm of a patient has started. A synchronization module analyzes whether the stored synchronization signal is erroneous and if so, prevents a medical treatment device from applying a treatment energy signal such as an IRE pulse to a patient to take into account an irregular heart beat and noise in the synchronization signal in order to maximize safety of the patient,

Delivery of an implantable wireless receiver-stimulator (R-S) into the heart using delivery catheter is described. R-S comprises a cathode and an anode and wirelessly receives and converts energy, such as acoustic ultrasound energy, to electrical energy to stimulate the heart. Conductive wires routed through the delivery system temporarily connect R-S electrodes to external monitor and pacing controller. R-S comprises a first temporary electrical connection from the catheter to the cathode, and a second temporary electrical connection from the catheter to the anode. Temporary electrical connections allow external monitoring of heart's electrical activity as sensed by R-S electrodes to determine tissue viability for excitation as well as to assess energy conversion efficiency.