A method for differentiating heart failure risk scores that includes receiving a current data transmission and acquiring patient metrics from a remote device, determining a daily heart failure risk score for each day occurring during a time period from a previous received data transmission to the current received data transmission based on the acquired patient metrics, determining a maximum daily heart failure risk score of the determined daily heart failure risk scores during a lookback window prior to the current received data transmission, determining a heart failure risk status alert for the received data transmission based on the temporal proximity of the determined maximum heart failure risk score and receipt of the current data transmission, selecting a type of notification based on the heart failure risk status differentiation, and indicating the transmission heart failure risk status and the heart failure risk status differentiation via the selected type of notification.

A medical device is configured to set a post-atrial time interval in response to an atrial event and generate an event time signal in response to a ventricular electrical signal crossing an R-wave sensing threshold during the post-atrial time interval. The device accumulates oversensing evidence in response to the event time signal and adjusts a ventricular sensing control parameter based on the accumulated oversensing evidence in some examples.

Systems and methods to determine P wave oversensing (PWOS) are disclosed, including identifying cardiac signal features in received cardiac electrical information, determining a first indication of PWOS using a pattern of identified cardiac signal features, and in response to the determined first indication of PWOS, determining a second indication of PWOS using a morphology of the received cardiac electrical information.

A method for differentiating heart failure risk scores that includes receiving a current data transmission and acquiring patient metrics from a remote device, determining a daily heart failure risk score for each day occurring during a time period from a previous received data transmission to the current received data transmission based on the acquired patient metrics, determining a maximum daily heart failure risk score of the determined daily heart failure risk scores during a lookback window prior to the current received data transmission, determining a heart failure risk status alert for the received data transmission based on the temporal proximity of the determined maximum heart failure risk score and receipt of the current data transmission, selecting a type of notification based on the heart failure risk status differentiation, and indicating the transmission heart failure risk status and the heart failure risk status differentiation via the selected type of notification.

Embodiments disclosed herein relate to systems and methods for detecting faults in leads and automatically reconfiguring a stimulation pattern of the leads based on a detected fault.

Described herein are methods, systems, and devices for estimating remaining longevity of an IMD powered by a battery that at any given time has a battery voltage (BV) and a remaining battery capacity (RBC). Such a method can include estimating the RBC using a first technique when the battery is operating within a t least one of one or more plateau regions, estimating the RBC using a second technique, that differs from the first technique when the battery is operating within a decline region, and estimating the remaining longevity of the IMD based on at least one of the estimates of the RBC. Additionally, historical battery data can be stored and used to estimate the RBC, e.g., when the battery is operating within a heavy usage and recovery period. RBC estimation can also depend on whether the IMD is close to its recommended replacement time (RRT).

A medical device is configured to sense a cardiac electrical signal and determine from the cardiac electrical signal at least one of a maximum peak amplitude of a positive slope of the cardiac electrical signal and a maximum peak time interval from a pacing pulse to the maximum peak amplitude. The device is configured to determine a capture type of the pacing pulse based on at least one or both of the maximum peak amplitude and the maximum peak time interval.

An apparatus for applying at least one electric pulse to a living myocardial tissue comprises an input configured to receive an electric signal representing a present electric activity of the myocardial tissue; a signal processor configured to process the electric signal to calculate a present permutation value of the electric signal in the state space and to only output a control signal when the calculated present entropy value of the electric signal is lower than a predetermined entropy threshold value; a pulse generator configured to generate the at least one electric pulse in response to the control signal; and an output configured to output the at least one electric pulse to the myocardial tissue.

An energy harvester converts into electrical energy the external stresses applied to the implant at the rhythm of the heartbeats. This harvester comprises an inertial unit. A transducer provides an oscillating electrical signal that is rectified and regulated, for powering the implant and/or charging a battery. The instantaneous variations of this electrical signal between two heartbeats are analyzed inside successive time windows, to derive therefrom a physiological parameter and/or a physical activity parameter of the patient with the implant, in particular as a function of a peak of amplitude of the first oscillation of the electrical signal, and of the level of this signal after the bounce phase of the signal oscillation.

A system including a medical device is provided. The medical device includes at least one sensor configured to acquire first data descriptive of a patient, first memory storing a plurality of templates, and at least one processor coupled to the at least one sensor and the first memory. The at least one processor is configured to identify a first template of the plurality of templates that is similar to the first data, to determine first difference data based on the first template and the first data, and to store the first difference data in association with the first template. The system may further include the programmable device.