A medical device and method conserve electrical power used in monitoring cardiac arrhythmias. The device includes a sensing circuit configured to sense a cardiac signal, a power source and a control circuit having a processor powered by the power source. The control circuit is configured to operate in a normal state by waking up the processor to analyze the cardiac electrical signal for determining a state of an arrhythmia. The control circuit switches from the normal state to a power saving state that includes waking up the processor at a lower rate than during the normal state.

Techniques for switching an implantable medical device (IMD) from a first mode to a second mode in relation to signals obtained from internal sensors are described. The internal sensors may include a temperature sensor and a biosensor. In some examples, processing circuitry of the IMD may make a first preliminary determination that the IMD is implanted based on a first signal from the temperature sensor. In response to the first preliminary determination being that the IMD is implanted, the processing circuitry may make a second preliminary determination that the IMD is implanted based on a second signal from the biosensor. The processing circuitry may switch the IMD from a first mode to a second mode based on both the first preliminary determination and the second preliminary determination being that the IMD is implanted.

Techniques for using multiple physiological parameters to provide an early warning for worsening heart failure are described. A system is provided that monitors a multiple diagnostic parameters indicative of worsening heart failure. The parameters preferably include are least one parameter acquired from an implanted device, such as intrathoracic impedance. The system device derives an index of the likelihood of worsening heart failure based upon the parameters using a Bayesian approach and displays the resultant index for review by a physician.

System and methods for monitoring and/or controlling nerve activity in a subject are provided. In one embodiment, a system includes electrodes configured to be placed proximate to a subject's skin, and a signal detector configured to detect electrical signals using the electrodes. The system also includes a signal processor configured to receive the electrical signals from the signal detector, and apply a filter to the received electrical signals to generate filtered signals, the filter configured to attenuate at least signals having frequencies corresponding to heart muscle activity during a heartbeat. The signal processor is also configured to identify a skin nerve activity using the filtered signals, estimate a sympathetic nerve activity using the identified skin nerve activity, and further to generate a report indicative of the estimated sympathetic nerve activity. In some aspects, the system further includes a signal generator to deliver the electrical stimulation to the subject's skin.

An implantable medical device performs a method that includes detecting a cardiac event interval that is greater than a P-wave oversensing threshold interval. In response to detecting the cardiac event interval greater than the P-wave oversensing threshold interval, the device determines the amplitude of the sensed cardiac signal and withholds restarting a pacing interval in response to the amplitude satisfying P-wave oversensing criteria. A pacing pulse may be generated in response to the pacing interval expiring without sensing an intrinsic cardiac electrical event that is not detected as a P-wave oversensing event.

Methods and systems for alleviating disorders and complications associated with autonomic nervous system dysfunction. The approach generally includes measuring heart rate signals from a subject to measure heart rate variability and determine a heart rate variability threshold, determining that the subject is experiencing autonomic nervous system dysfunction, and alerting the subject to stimulate the auricular branch of the vagus nerve with an ear device.

A wearable cardioverter defibrillator (WCD) system includes a support structure having an adjustable fastening assembly to fasten portions of the support structure together to fit the support structure on a patient. The adjustable fastening assembly enables the patient wearing the support structure to adjust the fit of the support structure without unfastening the portions from each other. The adjustable fastening assembly may also enable the patient to adjust the fit of the support structure while wearing clothing over the support structure and without having to adjust the clothing to view or access the adjustable fastening assembly.

A device for providing cardiac pacing of triangle of Koch and bundle of His zones by multiple electrodes inserted using in a single conduit is disclosed. The single conduit includes a plurality of individual electrodes capable of expanding from the distal end and forming a scattered pattern once deployed in the heart. Individual or group testing against a predetermined acceptance criterion is used to select a subset of individual electrodes for use in cardiac pacing.

Techniques that include applying machine learning models to episode data, including a cardiac electrogram, stored by a medical device are disclosed. In some examples, based on the application of one or more machine learning models to the episode data, processing circuitry derives, for each of a plurality of arrhythmia type classifications, class activation data indicating varying likelihoods of the classification over a period of time associated with the episode. The processing circuitry may display a graph of the varying likelihoods of the arrhythmia type classifications over the period of time. In some examples, processing circuitry may use arrhythmia type likelihoods and depolarization likelihoods to identify depolarizations, e.g., QRS complexes, during the episode.

A system and method are provided. The system includes a HIS electrode configured to be located proximate to a HIS bundle. A pulse generator is coupled to the HIS electrode and is configured to deliver HIS bundle pacing (HBP), a right atrial (RA) electrode is located in a right atrium, a sensing circuitry coupled to the RA electrode and defines an RA sensing channel that does not utilize the HIS electrode. The system includes a memory including program instructions. The system includes a processor is configured to collect cardiac activity (CA) signals over the RA sensing channel utilizing the RA electrode. The CA signals include a far field (FF) component associated with a ventricular event (VE). The processor analyzes the FF component to identify first and second FF component (FFC) characteristics of interest (COI) of the ventricular event and utilizes the first FFC COI to apply a first capture class (CC) discriminator to distinguish between first and second capture classes. The first capture class includes first and second capture types. The processor utilizes the second FFC COI to apply a second CC discriminator to distinguish between at least one of i) the first and second capture types within the first capture class, or ii) third and fourth capture classes and manages HIS bundle pacing based on distinctions by the first and second CC discriminators.