Abstract: According to an aspect, an implantable medical device includes an electronic pump device configured to transfer fluid between a fluid reservoir and an inflatable member to inflate or deflate the inflatable member, and an external controller configured to wirelessly communicate with the electronic pump device. The external controller or the electronic pump device is configured to receive a selected rigidity level from a user, convert the selected rigidity level to a target pressure value, obtain an ambient pressure value, compute a gauge pressure value based on the target pressure value and the ambient pressure value, and control inflation or deflation of the inflatable member using the gauge pressure value.

Abstract: According to an aspect, an implantable medical device includes an electronic pump device configured to transfer fluid between a fluid reservoir and an inflatable member to inflate or deflate the inflatable member, and an external controller configured to wirelessly communicate with the electronic pump device. The external controller or the electronic pump device configured to receive a selected rigidity level from a user, convert the selected rigidity level to a target pressure value using an adjustment curve, compute a gauge pressure value using at least the target pressure value, and control inflation or deflation of the inflatable member using the gauge pressure value.

Abstract: An implantable medical device may include an inflatable member. An implantable medical device may include a fluid reservoir. An implantable medical device may include a pressure sensor connected to the fluid reservoir. An implantable medical device may include an electronic pump device including a controller configured to execute operations, including receiving a signal with pressure readings during a time interval from the pressure sensor, identifying a portion of the pressure readings within a percentile range, computing an ambient pressure value based on the portion of the pressure readings, and updating an ambient pressure based on the ambient pressure value.

Abstract: An implantable medical device that includes an inflatable member, a fluid reservoir, a first pressure sensor connected to the fluid reservoir, a second pressure sensor connected to the inflatable member, an accelerometer configured to detect an acceleration of the implantable medical device along three orthogonal directions, and an electronic pump device. The electronic pump device includes a controller that is configured to execute operations that include receiving a first signal with pressure readings from the first pressure sensor and computing an ambient pressure value based on the pressure readings. The operations further include detecting an inflation pressure of the inflatable member using the second pressure sensor, receiving a second signal with acceleration data from the accelerometer, computing a gauge pressure based on the ambient pressure, the acceleration data, and the inflation pressure, and controlling inflation or deflation of the inflatable member based on the gauge pressure.

Abstract: Disclosed are medical devices with an acceleration sensor configured to generate acceleration data, a processor, and a memory. The memory, which may be a non-transitory computer readable medium, contains computer-executable instructions that, when executed by the processor, causes the processor to perform the following: obtain the acceleration data from a first range of time and a second range of time different from the first range, generate heart sound data based on the acceleration data, and determine that the medical device has flipped in orientation during the second range of time by comparing the heart sound data obtained during the first range of time with the heart sound data obtained during the second range of time.

Abstract: Disclosed are medical devices with an acceleration sensor for generating acceleration data, at least two electrodes for generating electrocardiogram (ECG) data, a processor, and memory. The memory, which may be a non-transitory computer readable medium, contains computer-executable instructions that, when executed by the processor, causes the processor to perform the following: obtain the acceleration data and the ECG data from a first range of time and a second range of time different from the first range, generate respiration data based on the acceleration data, and determine that the medical device has flipped in orientation during the second range of time by comparing the respiration data and the ECG data of the first range of time with the respiration data and the ECG data of the second range of time.

Abstract: A medical device system includes an ambulatory medical device and a second device. The ambulatory medical device includes one or more physiologic sensors configured to output sensor data and a communication circuit to transmit the sensor data to another device. The second device includes another communication circuit configured to receive the sensor data from ambulatory medical device, and processing circuitry. The processing circuitry is configured to determine patterns of the sensor data consistent with hemodialysis treatments of the patient, identify a change in the patterns of the sensor data indicative of a change in the hemodialysis treatments, and produce an alert associated with the hemodialysis treatments in response to the determining the change in the patterns of the sensor data.

Abstract: A medical device includes a processor, an acceleration sensor, and memory. The acceleration sensor is configured to generate acceleration data that comprises a plurality of acceleration measurements. The memory comprises instructions that when executed by the processor, cause the processor to: obtain the acceleration data from the acceleration sensor; and determine, based on the acceleration data, that the medical device has flipped.

Abstract: An ambulatory medical device includes a multi-axis posture sensor and processing circuitry. The multi-axis posture sensor is configured to provide an electrical posture sensor output representative of alignment of respective first, second, and third non-parallel axes of the ambulatory medical device with the gravitational field of the earth. The processing circuitry is configured to determine that the subject avoids lying on their left side using the posture sensor output, and compute a metric predictive of one or both of orthopnea and trepopnea in response to determining that the subject avoids lying on their left side.

Abstract: Systems and methods for monitoring and staging sleep using cardiac and respiration information are disclosed. An exemplary system comprises a storage device to store a trained hybrid sleep detection and classification model that comprise a plurality of trained machine-learning models each trained to map input cardiac and respiratory data into one of multiple distinct model-specific awake or sleep classes, and a trained regression model to combine the model-specific awake or sleep classes to a composite awake or sleep classification. A sleep detector applies patient cardiac and respiratory information to the trained hybrid sleep detection and classification model to determine a composite awake or sleep classification for the patient. The composite awake or sleep classification is used to diagnose medical conditions including sleep apnea.

Abstract: Embodiments herein relate to body vibration analysis systems and methods. In an embodiment, a body vibration analysis system is included having a first light source configured to illuminate a surface of the body from a first angle with a first set of lighted features and a second light source configured to illuminate a surface of the body from a second angle with a second set of lighted features, wherein the second set of lighted features are optically distinguishable from the first set of lighted features. The system further includes a camera configured to detect light reflected from the surface of the body and a control circuit configured to receive an input from the camera and assess spatial vibration as a function of location on the surface of the body. Other embodiments are also included herein.

Abstract: Systems and methods for recognizing and classifying breathing patterns based on spatial analysis of chest wall or abdominal movement or acceleration are described. A medical-device system comprises a receiver circuit to receive respiration information of a patient, and a breath analyzer circuit to determine from the respiration information two or more spatial respiration components, such as accelerations of chest wall or abdominal movement in respective directions along the anatomical axes. The breath analyzer circuit can classify a breathing pattern as one of either chest breathing or diaphragmatic breathing based on the determined spatial respiration components. The classified breathing pattern can be used for detecting a physiological event such as worsening heart failure or for assessing the patient's risk of having metabolic disorders.

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 to are disclosed to determine a sleep disordered breathing parameter of a patient, including receiving respiration information of the patient and temperature information of the patient and to determine the sleep disordered breathing parameter of the patient using the received respiration information and temperature information of the patient.

Abstract: A medical device includes a processor, an acceleration sensor, and memory. The acceleration sensor is configured to generate acceleration data that comprises a plurality of acceleration measurements. The memory comprises instructions that when executed by the processor, cause the processor to: obtain the acceleration data from the acceleration sensor; and determine, based on the acceleration data, that the medical device has flipped.

Abstract: Systems and methods for calibrating an orientation of an implantable device in a patient is described. An exemplary system includes a calibration circuit that can receive acceleration information sensed from an implantable medical device (IMD) implanted in a patient, and receive reference acceleration information sensed from a reference device associated with the patient. The acceleration information and the reference acceleration information are acquired when the patient assumes a first posture or in a first position. The calibration circuit determines a spatial relationship between an orientation of the IMD and a reference orientation of the reference device using the received acceleration information and the received reference acceleration information, and calibrate subsequent acceleration information sensed from the IMD using the determined spatial relationship to correct for the orientation of the IMD.

Abstract: Disclosed are medical devices with an acceleration sensor for generating acceleration data, at least two electrodes for generating electrocardiogram (ECG) data, a processor, and memory. The memory, which may be a non-transitory computer readable medium, contains computer-executable instructions that, when executed by the processor, causes the processor to perform the following: obtain the acceleration data and the ECG data from a first range of time and a second range of time different from the first range, generate respiration data based on the acceleration data, and determine that the medical device has flipped in orientation during the second range of time by comparing the respiration data and the ECG data of the first range of time with the respiration data and the ECG data of the second range of time.

Abstract: Disclosed are medical devices with an acceleration sensor configured to generate acceleration data, a processor, and a memory. The memory, which may be a non-transitory computer readable medium, contains computer-executable instructions that, when executed by the processor, causes the processor to perform the following: obtain the acceleration data from a first range of time and a second range of time different from the first range, generate heart sound data based on the acceleration data, and determine that the medical device has flipped in orientation during the second range of time by comparing the heart sound data obtained during the first range of time with the heart sound data obtained during the second range of time.

Abstract: Embodiments of the present disclosure relate to detecting implantable medical device orientation changes. In an exemplary embodiment, a medical device having a processor, comprises an acceleration sensor and memory. The acceleration sensor is configured to generate acceleration data that comprises a plurality of acceleration measurements. The memory comprises instructions that when executed by the processor, cause the processor to: obtain the acceleration data from the acceleration sensor; and determine, based on the acceleration data, that the medical device has flipped.

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.