Abstract: A device can include a multi-dimensional posture sensor that provides an electrical sensor output representative of alignment of first, second, and third non-parallel axes of the device with the gravitational field of the earth, and a processor that includes a calibration circuit and a posture circuit. The calibration circuit measures a first sensor output for the first device axis and a second sensor output for one of a second device axis while the subject is in a first specified posture, measures sensor outputs for the first, second, and third device axes while the subject is in a second specified posture, calculates one or more coordinate transformations, generates transformed sensor outputs using the coordinate transformations, and calibrates the posture sensor by calculating a calibration transformation using the first and second sensor outputs and the transformed sensor outputs. The posture circuit determines a subsequent posture of the subject using the posture sensor.

Abstract: This document discusses, among other things, systems and methods to determine amplitude and morphology variations of a first heart sound over a first number of cardiac cycles, and to calculate an atrial fibrillation metric indicative of an atrial fibrillation episode of the heart using the determined amplitude and morphology variations. The systems and methods can determine a variability score using the determined amplitude and morphology variations, and can calculate the atrial fibrillation metric using the variability score.

Abstract: Systems and methods for detecting atrial tachyarrhythmias (AT) such as atrial fibrillation (AF) are disclosed. A medical system can include a cardiac signal sensor circuit to sense a cardiac electrical signal and a heart sound (HS) sensor to sense heart a HS signal A cardiac electrical signal metric, including a cycle length variability or a detection of atrial electrical activity, can be generated from the cardiac electrical signal A HS metric can be generated from the HS signal, including a status of detection of S4 heart sound or a S4 heart sound intensity indicator. The system can include an AT detector circuit that can detect an AT event, such as an AF event, using the cardiac electrical signal metric and the HS metric The system can additionally classify the detected AT event as an AF or an atrial flutter event.

Abstract: A mobile device, having a processor, includes an accelerometer configured to generate acceleration data, the acceleration data including a plurality of acceleration measurements. The mobile device also includes a memory having embodied thereon computer-executable instructions that are configured to, when executed by the processor, cause the processor to: obtain the acceleration data from the accelerometer; and generate, based on the acceleration data, heart sound data, the heart sound data including data associated with one or more heart sounds.

Abstract: This document discusses, among other things, systems and methods to determine amplitude and morphology variations of a first heart sound over a first number of cardiac cycles, and to calculate an atrial fibrillation metric indicative of an atrial fibrillation episode of the heart using the determined amplitude and morphology variations. The systems and methods can determine a variability score using the determined amplitude and morphology variations, and can calculate the atrial fibrillation metric using the variability score.

Abstract: Embodiments include medical device systems, medical devices, including accelerometers and chemical sensors, and methods of using the same to determine the posture of a patient. In an embodiment, a medical device system herein includes an accelerometer configured to generate a signal reflecting a position of a patient, a chemical sensor configured to generate a signal reflecting physiological analyte data of the patient and a controller in electrical communication with the accelerometer and the chemical sensor. The controller can be configured to determine a posture of the patient using the position signal generated by the accelerometer and the signal generated by the chemical sensor. Other embodiments are also included herein.

Abstract: Systems and methods for detecting atrial tachyarrhythmias (AT) such as atrial fibrillation (AF) are disclosed. A medical system can include a cardiac signal sensor circuit to sense a cardiac electrical signal and a heart sound (HS) sensor to sense heart a HS signal. A cardiac electrical signal metric, including a cycle length variability or a detection of atrial electrical activity, can be generated from the cardiac electrical signal. A HS metric can be generated from the HS signal, including a status of detection of S4 heart sound or a S4 heart sound intensity indicator. The system can include an AT detector circuit that can detect an AT event, such as an AF event, using the cardiac electrical signal metric and the HS metric. The system can additionally classify the detected AT event as an AF or an atrial flutter event.

Abstract: Systems, devices and methods for using environmental data to manage health care are disclosed. One aspect is an advanced patient management system. In various embodiments, the system includes at least one implantable medical device (IMD) to acquire at least one IMD parameter indicative of patient wellness, means to acquire at least one environmental parameter from at least one external source, and means to correlate the at least one parameter indicative of patient wellness and the at least one environmental parameter to assist with patient health care decisions. Other aspects and embodiments are provided herein.

Abstract: Methods and devices for configuring the use of a motion sensor in an implantable cardiac device. The electrical signals of the patient's heart are observed and may be correlated to the physical motion of the heart as detected by the motion sensor of the implantable cardiac device in order to facilitate temporal configuration of motion sensor data collection that avoids detecting cardiac motion in favor of overall motion of the patient.

Abstract: Patient posture information can be received, such as to indicate a change in patient posture by at least a threshold amount. A transient response signal indicative of a change in a physiological parameter can be received at multiple instances near a change in patient posture. Waveform morphology features can be extracted from a transient response signal and used to provide an indication of a cardiac status, such as a heart failure status.

Abstract: Implantable devices having motion sensors. In some examples the a configuration is generated for the implantable device to use the motion sensor in an energy preserving mode in which one or more axis of detection of the motion sensor is disabled or ignored. In some examples the motion sensor outputs along multiple axes are analyzed to determine which axes best correspond to certain patient parameters including patient motion/activity and/or cardiac contractility. In other examples the output of the motion sensor is observed across patient movements or postures to develop conversion parameters to determine a patient standard frame of reference relative to outputs of the motion sensor of an implanted device.

Abstract: Methods and devices for configuring the use of a motion sensor in an implantable cardiac device. The electrical signals of the patient's heart are observed and may be correlated to the physical motion of the heart as detected by the motion sensor of the implantable cardiac device in order to facilitate temporal configuration of motion sensor data collection that avoids detecting cardiac motion in favor of overall motion of the patient.

Abstract: Systems and methods for diagnosing one or more respiration distress manifestations by implantably recognizing their occurrence and evaluating information about the same to provide an indication of present or impending worsening heart failure are discussed. Using information produced by an implantable respiration sensor circuit and an implantable physiological sensor circuit, such as at least one of a physical activity sensor circuit or a posture sensor circuit, an implantable or external processor circuit may detect a respiration disturbance and an associated subsequent arousal from stable state occurrence and thereafter evaluate over time arousal from stable state occurrences to provide the indication of present or impending worsening heart failure. In one example, information about a fluid level within a subject is used in determining the indication of worsening heart failure.

Abstract: 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.

Abstract: Disordered breathing events may be classified as central, obstructive or a combination of central an obstructive in origin based on patient motion associated with respiratory effort. Central disordered breathing is associated with disrupted respiration with reduced respiratory effort. Obstructive disordered breathing is associated with disrupted respiration accompanied by respiratory effort. A disordered breathing classification system includes a disordered breathing detector and a respiratory effort motion sensor. Components of the disordered breathing classification system may be fully or partially implantable.

Abstract: A system for performing a sleep study includes an implant able medical device (IMD) having a first sensor configured to obtain a first physiological parameter signal; a second sensor configured to obtain a second physiological parameter signal; and at least one processing device. The at least one processing device is configured to: receive the first physiological parameter signal and the second physiological parameter signal; and identify, based on a set of episode data, an occurrence of an episode during a sleep session, the episode corresponding to a sleep disorder, the set of episode data based on at least one of the first physiological parameter signal and the second physiological parameter signal. The at least one processing device is further configured to generate, based on the first physiological parameter signal and the second physiological parameter signal, a study report, the study report comprising an indication of the episode.

Abstract: A device and method can monitor or trend a patient's respiration rate measurements according to the time of day. The device, which may be implantable or external, collects and classifies respiration rate measurements over time. The trended information about particular classes of respiration rate measurements is then communicated to a remote external device, which in turn provides an indication of heart failure decompensation. Examples of classes of respiration rate measurements include a daily maximum respiration rate value, a daily minimum respiration rate value, a daily maximum respiration rate variability value, a daily minimum respiration rate variability value, and a daily central respiration rate value. These respiration rate measurements can be further classified into daytime or nighttime respiration rate measurements.

Abstract: This document discusses, among other things, systems and methods to determine amplitude and morphology variations of a first heart sound over a first number of cardiac cycles, and to calculate an atrial fibrillation metric indicative of an atrial fibrillation episode of the heart using the determined amplitude and morphology variations. The systems and methods can determine a variability score using the determined amplitude and morphology variations, and can calculate the atrial fibrillation metric using the variability score.

Abstract: An apparatus comprises plurality of sensors and a processor. Each sensor provides a sensor signal that includes physiological information and at least one sensor is implantable. The processor includes a physiological change event detection module that detects a physiological change event from a sensor signal and produces an indication of occurrence of one or more detected physiological change events, and a heart failure (HF) detection module. The HF detection module determines, using a first rule, whether the detected physiological change event indicative of a change in HF status of a subject, determines whether to override the first rule HF determination using a second rules, and declares whether the change in HF status occurred according to the first and second rules.

Abstract: Systems and methods for detecting atrial tachyarrhythmias (AT) such as atrial fibrillation (AF) are disclosed. A medical system can include a cardiac signal sensor circuit to sense a cardiac electrical signal and a heart sound (HS) sensor to sense heart a HS signal. A cardiac electrical signal metric, including a cycle length variability or a detection of atrial electrical activity, can be generated from the cardiac electrical signal. A HS metric can be generated from the HS signal, including a status of detection of S4 heart sound or a S4 heart sound intensity indicator. The system can include an AT detector circuit that can detect an AT event, such as an AF event, using the cardiac electrical signal metric and the HS metric. The system can additionally classify the detected AT event as an AF or an atrial flutter event.