A method and device apparatus to deliver a pacing therapy capable of remodeling a patient's heart over a period of time that includes monitoring one or more parameters in response to a delivered cardiac remodeling pacing, determining whether the cardiac remodeling pacing has an effect on cardiac normalization in response to the monitoring, and adjusting the cardiac remodeling pacing in response to the determined effect on cardiac normalization. The method and device may also perform short-term monitoring of one or more parameters in response to the delivered cardiac remodeling pacing, monitor one or more long-term parameter indicative of a long-term effect of the delivered cardiac remodeling pacing, determine the long-term effect of the delivered cardiac remodeling pacing on cardiac normalization in response to the monitoring, and adjust the cardiac remodeling pacing in response to one or both of the short-term monitoring and the determined long-term effect on cardiac normalization.

An example device for detecting one or more parameters of a cardiac signal is disclosed herein. The device includes one or more electrodes and sensing circuitry configured to sense a cardiac signal via the one or more electrodes. The device further includes processing circuitry configured to determine a representative signal based on the cardiac signal, the representative signal having a single polarity, and determine an end of a T-wave of the cardiac signal based on an area under the representative signal.

A medical device includes: a case at least a portion of which functions as a first electrode; a second electrode disposed in a header coupled to the case; a core assembly, the core assembly including operational circuitry enclosed within a core assembly housing, wherein the case includes the core assembly housing; and a battery assembly, the battery assembly including a battery enclosed within a battery housing, where the case further comprises the battery housing; where the operational circuitry is configured to drive a regulated voltage onto the case.

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.

A medical device system, such as an extra-cardiovascular implantable cardioverter defibrillator ICD, senses R-waves from a first cardiac electrical signal by a first sensing channel and stores a time segment of a second cardiac electrical signal in response to each sensed R-wave. The medical device system determines a morphology parameter correlated to signal noise from time segments of the second cardiac electrical signal, detects a noisy signal segment based on the signal morphology parameter; and withholds detection of a tachyarrhythmia episode in response to detecting a threshold number of noisy signal segments.

Systems, interfaces, and methods are described herein for evaluation and adjustment cardiac therapy. The systems, interfaces, and methods may utilize, or include, a graphical user interface to display various information with respect to a plurality of external electrodes and electrical activity monitored using such external electrodes and to allow a user to adjust what information to display.

The present disclosure relates generally to electroporation systems and utilizing algorithms for electroporation pulse delivery including a patient's EKG/EGM monitoring. In some embodiments, an electroporation delivery system may include an electrocardiogram operatively connected to a processing device and a memory. One or more sensors may be operatively connected to the electrocardiogram for measuring electrical activity QRS complex of a patient's heart. One or more electrodes for treatment may be disposed in, at, or near the patient's heart, the one or more electrodes operatively connected to a pulse delivery mechanism. The electroporation delivery system may be configured to determine whether an electroporation pulse is deliverable to a patient based on the electrocardiogram.

An implantable system for stimulating a heart contains a processor, a memory, a stimulator, and a first detection unit for detecting a cardiac rhythm disturbance of a cardiac region. The memory includes a computer-readable program, which prompts the processor to carry out the following steps: a) detecting via the first detection unit whether a cardiac rhythm disturbance is present in a cardiac region of a heart of a patient; b) when a cardiac rhythm disturbance is present, selecting a stimulation strategy based on a selection criterion; c) stimulating the cardiac region in which the cardiac rhythm disturbance was detected by way of the stimulator, using the selected stimulation strategy; d) detecting a success and/or an efficiency of the conducted stimulation; e) comparing the success and/or the efficiency to a predefinable success and/or efficiency criterion; and f) if the predefinable success and/or efficiency criterion was not achieved, optimizing the stimulation strategy.

An apparatus comprises an arrhythmia detection circuit configured to: receive a cardiac signal representative of cardiac activity of a subject; apply a first arrhythmia detection criteria to the received cardiac signal; apply, in response to the applied first arrhythmia detection criteria producing a positive indication of arrhythmia, a second arrhythmia detection criteria to the received cardiac signal, wherein the second arrhythmia detection criteria is more specific to detection of arrhythmia than the first detection criteria; detect, in response to the applied first and second arrhythmia detection criteria, a sensing event indicating one or both of the first and second arrhythmia detection criteria are susceptible to false indications of arrhythmia; and adjust, in response to a detected sensing event, sensitivity or specificity of one or both of the first and second arrhythmia detection criteria.

Computer implemented methods and systems are provided that comprise, under control of one or more processors of a medical device, where the one or more processors are configured with specific executable instructions. The methods and systems include sensing circuitry configured to define a sensing channel to collect biological signals, memory configured to store program instructions, a processor configured to implement the program instructions to at least one of analyze the biological signals, manage storage of the biological signals or deliver a therapy, and communication circuitry configured to wirelessly communicate with at least one other implantable or external device, the communication circuitry configured to transition between a sleep state, a partial awake state and a fully awake state. When in the fully awake state, the communication circuitry is configured to execute tasks and actions associated with a communications protocol startup (CPS) instruction set that includes an advertisement scanning related (ASR) instruction subset and a non-ASR instruction subset. When in the partially awake state, the communication circuitry is configured to execute, as the ASR instruction subset, transmit advertising notices over one or more channels according to a wireless communications protocol, scan the one or more channels for a connection request from an external device. When a connection request is not received, return to the sleep state, without performing actions or tasks associated with the non-ASR instruction subset of the CPA instruction set.