This document discusses, among other things, apparatus, systems, or methods to efficiently collect heart sound data, including detecting first heart sound information of a heart of a patient using a heart sound sensor in a first, low-power operational mode, and detecting second heart sound information of the heart using the heart sound sensor in a separate second, high-power operational mode. The operational mode of the heart sound sensor can be controlled using physiologic information from the patient, including heart sound information, information about a heart rate of the patient, or other physiologic information from the patient that indicates worsening heart failure.

An apparatus comprises a respiration sensing circuit configured for coupling electrically to a plurality of electrodes and for sensing a respiration signal representative of respiration of a subject; a signal processing circuit electrically coupled to the respiration sensing circuit and configured to extract a respiration parameter from a sensed respiration signal and determine a signal performance metric for the sensed respiration signal using the respiration parameter; and a control circuit. The control circuit is configured to: initiate sensing of a plurality of respiration signals using different electrode combinations of the plurality of electrodes and determining of the signal performance metric for the sensed respiration signals; and enable an electrode combination from the plurality of electrodes and for use in monitoring respiration of the subject according to the signal performance metric.

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 component designed to cause dyssynchrony of the right ventricle, and a controller configured for adjusting the function of the at least one component based at least in part on sensor data from the at least one sensor.

A wireless circuit includes a housing having at least one opening, and sensor connected to the housing at the opening. The sensor includes a first layer having a first dimension and a second layer having a second dimension shorter than the first dimension. The second layer may be positioned entirely within the housing and a surface of said first layer may be exposed to an exterior of the housing.

Spinal device/implants are provided, comprising a spinal device/implant and a sensor.

The systems and methods described herein determine metrics of cardiac or vascular performance, such as cardiac output, and can use the metrics to determine appropriate levels of mechanical circulatory support to be provided to the patient. The systems and methods described determine cardiac performance by determining aortic pressure measurements (or other physiologic measurements) within a single heartbeat or across multiple heartbeats and using such measurements in conjunction with flow estimations or flow measurements made during the single heartbeat or multiple heartbeats to determine the cardiac performance, including determining the cardiac output. By utilizing a mechanical circulatory support system placed within the vasculature, the need to place a separate measurement device within a patient is reduced or eliminated. The system and methods described herein may characterize cardiac performance without altering the operation of the heart pump (e.g., without increasing or decreasing pump speed).

A wearable drug delivery device, techniques, and computer-readable media that provide an application that implements a diabetes treatment plan for a user are described. The drug delivery device may include a controller operable to direct operation of the wearable drug delivery device. The controller may provide a selectable activity mode of operation for the user. Operation of the drug delivery device in the activity mode of operation may reduce a likelihood of hypoglycemia during times of increased insulin sensitivity for the user and may reduce a likelihood of hyperglycemia during times of increased insulin requirements for the user. The activity mode of operation may be manually activated by the user or may be activated automatically by the controller. The controller may automatically activate the activity mode of operation based on a detected activity level of the user and/or a detected location of the user.

A system and method for display of subcutaneous cardiac monitoring data are provided. Cutaneous action potentials of a patient and other sensed data associated with the patient are recorded as electrocardiogram (EGC) data over a set time period using a subcutaneous insertable cardiac monitor. A set of R-wave peaks is identified within the ECG data and an R-R interval plot is constructed. A difference between recording times of successive pairs of the R-wave peaks in the set is determined. A heart rate associated with each difference is also determined. The pairs of the R-wave peaks and associated heart rate are plotted as the R-R interval plot. A diagnosis of cardiac disorder is facilitated based on patterns of the plotted pairs of the R-wave peaks, the associated heart rates in the R-R interval plot, and background data based on the other sensed data.

A continuous glucose monitoring system may utilize externally sourced information regarding the physiological state and ambient environment of its user for externally calibrating sensor glucose measurements. Externally sourced factory calibration information may be utilized, where the information is generated by comparing metrics obtained from the data used to generate the sensor's glucose sensing algorithm to similar data obtained from each batch of sensors to be used with the algorithm in the future. The output sensor glucose value of a glucose sensor may also be estimated by analytically optimizing input sensor signals to accurately correct for changes in sensitivity, run-in time, glucose current dips, and other variable sensor wear effects. Correction actors, fusion algorithms, EIS, and advanced ASICs may be used to implement the foregoing, thereby achieving the goal of improved accuracy and reliability without the need for blood-glucose calibration, and providing a calibration-free, or near calibration-free, sensor.

A medical device is configured to sense an electrical signal and determine that signal to noise criteria are met based on electrical signal segments stored in response to sensed electrophysiological events. The medical device is configured to determine an increased gain signal segment from one of the stored electrical signal segments in response to determining that the signal to noise criteria are met. The medical device determines a noise metric from the increased gain signal segment. The stored electrical signal segment associated with the increased gain signal segment may be classified as a noise segment in response to the noise metric meeting noise detection criteria.