Techniques and systems disclosed herein are directed to determining pacing attributes for a patient and include determining use of a beta blocker with intrinsic sympathomimetic activity (ISA) by the patient, receiving a current physiological input, and determining pacing attributes based on the determining use of the beta blocker with ISA and the current physiological input. They further include receiving a current physiological input, determining pacing attributes based on the current physiological input, causing a pacing device to output pacing outputs based on the pacing attributes, receiving an updated physiological input after causing the pacing device to output the pacing outputs, determining that a difference between the current physiological input and the updated physiological input does not meet a threshold difference, and generating an indication of a presence or use of a non-ISA beta blocker based on the difference not meeting the threshold difference.

An implantable medical device (IMD) is configured with a pressure sensor. The IMD includes a housing, a pressure sensor and a fluid filled cavity. The housing has a diaphragm that is exposed to the environment outside of the housing. The pressure sensor has a pressure sensor diaphragm that is responsive to a pressure applied to the pressure sensor diaphragm and provides a pressure sensor output signal that is representative of the pressure applied to the pressure sensor diaphragm. The fluid filled cavity is in fluid communication with both the diaphragm of the housing and the pressure sensor diaphragm of the pressure sensor. The fluid filled cavity is configured to communicate a measure related to the pressure applied by the environment to the diaphragm of the housing to the pressure sensor diaphragm of the pressure sensor.

An implantable medical device system and associated method for use in guiding an acute decompensated heart failure therapy set an optimal fluid status measurement level. A physiological sensor signal sensed by an implantable medical device is used to compute the fluid status measurement. A target rate of change of the fluid status measurement is computed for guiding the therapy.

A medical device senses cardiac electrical signals including T-waves attendant to ventricular myocardial repolarizations and detects a T-wave template condition associated with non-pathological changes in T-wave morphology. The device generates a T-wave template from T-waves sensed by the sensing circuit during the T-wave template condition. After generating the T-wave template, the device acquires a T-wave signal from the cardiac electrical signal and compares the acquired T-wave signal to the T-wave template. The device detects a pathological event in response to the acquired T-wave signal not matching the T-wave template.

Systems and methods are provided for optimizing hemodynamics within a patient's heart, e.g., to improve the patient's exercise capacity. In one embodiment, a system is configured to be implanted in a patient's body to monitor and/or treat the patient that includes at least one sensor configured to provide sensor data that corresponds to a blood pressure within or near the patient's heart; at least one adjustable component designed to cause blood to flow in a direction opposite to the normal direction (regurgitation) within the patient's heart; and a controller configured for adjusting the function of the at least one adjustable component based at least in part on sensor data from the at least one sensor.

Systems and methods for adaptively controlling an electrical stimulation device, such as a closed-loop stimulation device, based in part on a Bayesian optimization of the operational parameters of the device are described. An adaptive dual control of the stimulation device can be provided. In a first control loop parameters are extracted from signals recorded from the subject by the stimulation device, and in a second control loop a Bayesian optimization is implemented with a hardware processor and memory to compute updated operational parameters for the stimulation device. As noted, the stimulation device is an electrical stimulation device, and may be a closed-loop stimulation device. Such devices can be used for deep brain stimulation (DBS), cardiac resynchronization therapy (CRT), and other electrophysiological stimulation applications.

A method is provided for use with a human subject. The method includes accessing a cardiac site via a vena cava of the subject, and alleviating heart failure of the subject by applying to the cardiac site, during a refractory period of the site, a refractory-period signal that affects the left ventricle of the subject's heart. Other embodiments are also described.

A cardiac pacing system having a pulse generator for generating therapeutic electric pulses, a lead electrically coupled with the pulse generator having an electrode, a first sensor configured to monitor a physiological characteristic of a patient, a second sensor configured to monitor a second physiological characteristic of a patient and a controller. The controller can determine a pacing vector based on variables including a signal received from the second sensor, and cause the pulse generator to deliver the therapeutic electrical pulses according to the determined pacing vector. The controller can also modify pacing characteristics based on variables including a signal received from the second sensor.

This invention is an integrated system for managing cardiac rhythm comprising a wearable device (such as a finger wring or wrist band) that measures body oxygen levels and an implanted cardiac rhythm management device (such as a pacemaker). Working together in an integrated system, a wearable device for measuring oxygen level in body extremities and an implanted device for cardiac rhythm management can help to prevent oxygen deficiencies in body extremities.

At least one of a medical device, such as an implantable medical device, and a programming device determines values for one or more metrics that indicate the quality of a patient's sleep. Sleep efficiency, sleep latency, and time spent in deeper sleep states are example sleep quality metrics for which values may be determined. In some embodiments, determined sleep quality metric values are associated with a current therapy parameter set. In some embodiments, a programming device presents sleep quality information to a user based on determined sleep quality metric values. A clinician, for example, may use the sleep quality information presented by the programming device to evaluate the effectiveness of therapy delivered to the patient by the medical device, to adjust the therapy delivered by the medical device, or to prescribe a therapy not delivered by the medical device in order to improve the quality of the patient's sleep.