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 obtain motion data indicative of at least one of a posture or a respiration cycle; obtain cardiac activity (CA) signals for a series of beats; identify whether a characteristic of interest (COI) from at least a first segment of the CA signals exceeds a COI limit; analyze the motion data to determine whether at least one of the posture or respiration cycle at least in part caused the COI to exceed the COI limit. Based on the analyzing operation, the methods and systems automatically adjust a CA sensing parameter utilized by the medical device to detect R-waves in subsequent CA signals; and detect an arrhythmia based on a presence or absence of one or more of the R-waves in at least a second segment of the CA signals.

Systems and methods for detecting arrhythmias in cardiac activity are provided and include memory to store specific executable instructions. One or more processors are configured to execute the specific executable instructions for obtaining first and second far field cardiac activity (CA) data sets over primary and secondary sensing channels, respectively, in connection with a series of beats. The system detects candidate atrial features from the second CA data set, identifies ventricular features from the first CA data set and utilizes the ventricular features to separate beat segments within the second CA data set. The system automatically iteratively analyzes the beat segments by overlaying an atrial activity search window with the second CA data set and determines whether one or more of the candidate atrial features occur within the atrial activity search window. The system adjusts an atrial sensitivity profile based on whether the atrial activity search window includes the one or more of the candidate atrial features and detects atrial events based on the atrial sensitivity profile.

A patient monitoring device configured to monitor cardiac activity and sleep stage information of a patient is provided. The device includes a plurality of electrodes to acquire electrocardiogram (ECG) signals from the patient, at least one motion sensor configured to generate a motion signal based upon movement of the patient, and at least one processor. The processor is configured derive motion parameters from the motion signal, derive ECG parameters from the ECG signals, determine whether the patient is in an immobilized sleep stage or a non-immobilized sleep stage based upon the motion parameters and the ECG parameters, adjust one or more cardiac arrhythmia detection parameters such that the device operates in a first monitoring and treatment mode when the patient is in an immobilized sleep stage, and monitor the patient for the cardiac arrhythmia using the first monitoring and treatment mode.

Techniques are disclosed for using both feature delineation and machine learning to detect cardiac arrhythmia. A computing device receives cardiac electrogram data of a patient sensed by a medical device. The computing device obtains, via feature-based delineation of the cardiac electrogram data, a first classification of arrhythmia in the patient. The computing device applies a machine learning model to the received cardiac electrogram data to obtain a second classification of arrhythmia in the patient. As one example, the computing device uses the first and second classifications to determine whether an episode of arrhythmia has occurred in the patient. As another example, the computing device uses the second classification to verify the first classification of arrhythmia in the patient. The computing device outputs a report indicating that the episode of arrhythmia has occurred and one or more cardiac features that coincide with the episode of arrhythmia.

A medical device is configured to deliver therapeutic electrical stimulation pulses by generating frequency modulated electrical stimulation pulse signals. The medical device includes a pulse signal source and a modulator. The pulse signal source generates an electrical stimulation pulse signal having a pulse width. The modulator may include a high frequency modulator configured to modulate a frequency of the pulse signal from a starting frequency down to a minimum frequency during the pulse width. The modulator may include a low frequency bias generator to modulate the offset of the pulse signal between a minimum offset and a maximum offset in other examples.

A medical device is configured to deliver therapeutic electrical stimulation pulses by generating frequency modulated electrical stimulation pulse signals. The medical device includes a pulse signal source and a modulator. The pulse signal source generates an electrical stimulation pulse signal having a pulse width. The modulator may include a high frequency modulator configured to modulate a frequency of the pulse signal from a starting frequency down to a minimum frequency during the pulse width. The modulator may include a low frequency bias generator to modulate the offset of the pulse signal between a minimum offset and a maximum offset in other examples.

A system for monitoring medical conditions including pressure ulcers, pressure-induced ischemia and related medical conditions comprises at least one sensor adapted to detect one or more patient characteristic including at least position, orientation, temperature, acceleration, moisture, resistance, stress, heart rate, respiration rate, and blood oxygenation, a host for processing the data received from the sensors together with historical patient data to develop an assessment of patient condition and suggested course of treatment, including either suspending or adjusting turn schedule based on various types of patient movement. Compliance with Head-of-Bed protocols can also be performed based on actual patient position instead of being inferred from bed elevation angle. The sensor can include bi-axial or tri-axial accelerometers, as well as resistive, inductive, capacitive, magnetic and other sensing devices, depending on whether the sensor is located on the patient or the support surface, and for what purpose.

An implantable medical device system receives a cardiac electrical signal produced by a patient's heart and comprising atrial P-waves and delivers a His bundle pacing pulse to the patient's heart via a His pacing electrode vector. The system determines a timing of a sensed atrial P-wave relative to the His bundle pacing pulse and determines a type of capture of the His bundle pacing pulse in response to the determined timing of the atrial P-wave.

An implantable medical device system receives a cardiac electrical signal produced by a patient's heart and comprising atrial P-waves and delivers a His bundle pacing pulse to the patient's heart via a His pacing electrode vector. The system determines a timing of a sensed atrial P-wave relative to the His bundle pacing pulse and determines a type of capture of the His bundle pacing pulse in response to the determined timing of the atrial P-wave.

This document discusses, among other things, systems and methods to receive cardiac electrical information and premature ventricular contraction (PVC) information of a subject, detect atrial fibrillation (AF) of the subject using the received cardiac electrical information, and adjust AF detection using the received PVC information.