摘要:
An example method includes monitoring a first posture including a first lateral decubitus posture (LDP), recording a first LDP record based on the first LDP, computing a first posture trend based on the first LDP record and determining and providing a wellness indication based on the first posture trend.
摘要:
An example method includes monitoring a first posture including a first lateral decubitus posture (LDP), recording a first LDP record based on the first LDP, computing a first posture trend based on the first LDP record and determining and providing a wellness indication based on the first posture trend.
摘要:
Systems and methods include accessing a plurality of cardiac indications. A heart rate variability metric is produced by analyzing the plurality of cardiac indications using a measurement from a class of nonlinear measurements. Nonlinear measurements include, but are not limited to, approximate entropy, X-Y scatter from a Poincaré plot, fractal dimension, and detrended fluctuation analysis, in various examples. Based on the heart rate variability metric, a cardiac ischemic state is detected.
摘要:
Systems and methods include obtaining a measure of cardiac contractility. A cardiac contractility variability is determined from the measure of cardiac contractility. Analyzing the cardiac contractility variability, an indication of cardio-vasculature health is provided.
摘要:
Systems and methods include obtaining a measure of cardiac contractility. A cardiac contractility variability is determined from the measure of cardiac contractility. Analyzing the cardiac contractility variability, an indication of cardio-vasculature health is provided.
摘要:
A system and method automatically calibrate a posture sensor, such as by detecting a walking state or a posture change. For example, a three-axis accelerometer can be used to detect a patient's activity or posture. This information can be used to automatically calibrate subsequent posture or acceleration data.
摘要:
In an embodiment, an implantable medical device includes a controller circuit, a posture sensing circuit, and a physiological sensing circuit. The controller circuit senses a change in a physiological signal as a result of a change in posture, and generates a response as a function of that change. In another embodiment, the controller circuit identifies a heart failure condition as a function of the change in the physiological signal.
摘要:
A system and method automatically calibrate a posture sensor, such as by detecting a walking state or a posture change. For example, a three-axis accelerometer can be used to detect a patient's activity or posture. This information can be used to automatically calibrate subsequent posture or acceleration data.
摘要:
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.
摘要:
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.