Implantable medical devices (IMD), such as but not limited to leadless cardiac pacemakers (LCP), subcutaneous implantable cardioverter defibrillators (SICD), transvenous implantable cardioverter defibrillators, neuro-stimulators (NS), implantable monitors (IM), may be configured to communicate with each other. In some cases, a first IMD may transmit instructions to a second IMD. In order to improve the chances of a successfully received transmission, the first IMD may transmit the instructions several times during a particular time frame, such as during a single heartbeat. If the second IMD receives the message more than once, the second IMD recognizes that the messages were redundant and acts accordingly.

Wearable devices are provided herein including wearable defibrillators, wearable devices for diagnosing symptoms associated with sleep apnea, and wearable devices for diagnosing symptoms associated with heart failure. The wearable external defibrillators can include a plurality of ECG sensing electrodes and a first defibrillator electrode pad and a second defibrillator electrode pad. The ECG sensing electrodes and the defibrillator electrode pads are configured for long term wear. Methods are also provided for using the wearable external defibrillators to analyze cardiac signals of the wearer and to provide an electrical shock if a treatable arrhythmia is detected. Methods are also disclosed for refurbishing wearable defibrillators. Methods of using wearable devices for diagnosing symptoms associated with sleep apnea and for diagnosing symptoms associated with heart failure are also provided.

A computer implemented method and system are provided for detecting premature ventricular contractions (PVCs) in cardiac activity. The method and system obtain cardiac activity (CA) signals for a series of beats, and, for at least a portion of the series of beats, calculate QRS scores for corresponding QRS complex segments from the CA signals. The method and system calculate a variability metric for QRS scores across the series of beats, calculate a QRS complex template using QRS segments from the series of beats, calculate correlation coefficients between the QRS complex template and the QRS complex segments, compare the variability metric to a variability threshold and the correlation coefficients to a correlation threshold, and designate the CA signals to include a predetermined level of PVC burden based on the determining.

Several defibrillators, defibrillator architectures, defibrillator components and methods of operating defibrillators are described. In one aspect, a defibrillator (as for example an automated external defibrillator) that can be powered by a mobile communication device such as a smart cellular phone or a tablet computer is described. Utilizing a phone (or other mobile communication device) as the power supply for an external defibrillator allows the external defibrillator to be smaller and, in some circumstance, removes the need for a battery that stores sufficient energy for shock deliverywhich would need to be checked and/or replaced on a regular basis. Additionally, when desired, certain control functionality, computation, data processing, and user instructions can be handled/presented by the mobile communications device thereby further simplifying the defibrillator design and improving the user experience. This architecture takes advantage of the nearly ubiquitous availability of smart phones, tablet computers and other mobile communication devices.

In one example, a cardiac monitoring system comprises a processor to receive a segment of an electrocardiogram (ECG) signal of a patient, and a memory to store the segment of the ECG. The processor is configured to identify QRS complexes in the segment of the ECG signal, generate a supraventricular (SV) template for SV complexes in the QRS complexes, identify SV complexes in the QRS complexes using the template, identify normal sinus rhythm (NSR) complexes in the segment of the ECG signal, obtain an atrial template for atrial waveforms in the NSR complexes, measure a range of a P-wave of the atrial waveforms from the NSR complexes, save the measured P-waves, and classify the identified SV complexes as either atrial fibrillation (AF) or supraventricular tachycardia (SVT) using the atrial template. Other examples and related methods are also disclosed herein.

A method includes determining whether electrical activity is indicative of atrial fibrillation, determining whether mechanical activity is indicative of atrial fibrillation, and adjusting a pacing parameter or mode based on whether the electrical activity and the mechanical activity are indicative of atrial fibrillation. The electrical activity may be detected based on a far-field measurement. The method may be performed using a leadless implantable medical device.

In some examples, processing circuitry of a medical device system determines, for each of a plurality of patient parameters, a difference metric for a current period based on a value of a patient parameter determined for the current period and a value of the patient parameter determined for an immediately preceding period, and determines a score for the current period based on a sum of the difference metrics for at least some of the plurality of patient parameters. The processing circuitry determines a threshold for the current period based on scores determined for N periods that precede the current period, compares the score for the current period to the threshold, and determines whether to generate an alert indicating that an acute cardiac event of the patient, e.g., ventricular tachyarrhythmia, is predicted, and/or deliver a therapy configured to prevent the acute cardiac event, based on the comparison.

An implantable cardiac stimulation device provides electrical stimulation therapy to stabilize the ventricular rate of a heart during episodes of atrial fibrillation. The stimulation therapy may be a plurality of sub-threshold stimulation pulses delivered to capture AV node vagal innervations following the detection of atrial fibrillation.

An apparatus comprises an arrhythmia detection circuit configured to: detect atrial arrhythmia in a first portion of a sensed cardiac signal using a first arrhythmia detection criteria, wherein the sensed cardiac signal is representative of cardiac activity of a subject; and upon detection of the atrial arrhythmia, analyze a second portion of the cardiac signal that is prior in time to the first portion using a second different arrhythmia detection criteria to detect the presence or absence of the atrial arrhythmia in the second portion of the cardiac signal.

The present disclosure provides methods and systems for limiting arcing during an electroporation procedure. A method includes delivering a calibration shock using a catheter, measuring a current delivered during the calibration shock and a voltage delivered during the calibration shock, calculating, using a processing device, a calibration shock impedance based on the delivered current and the delivered voltage, calculating, using the processing device, a bridge impedance based on the calibration shock impedance and a target impedance, wherein the bridge impedance is a difference between the calibration shock impedance and the target impedance, adding an impedance in series with the catheter, the impedance being greater than or equal to the bridge impedance, and delivering a therapeutic shock using the catheter in series with the added impedance.