Abstract: Systems and methods to provide remote patient monitoring for viral-respiratory symptoms, including coronavirus or COVID-19 symptoms are disclosed, including a signal receiver circuit configured to receive first and second physiologic information of a patient, the first physiologic information comprising respiration rate information of a patient and the second physiologic information different than the first physiologic information, and an assessment circuit configured to determine an indication of patient viral-respiratory disease using the received first and second physiologic information.

Abstract: Systems and methods to detect pneumonia in cardiovascular patients are disclosed, including receiving physiologic information of a patient from an ambulatory medical device (AMD), the physiologic information comprising respiration information of the patient, and determining a pneumonia score of the patient using the received respiration information.

Abstract: Systems and methods for detecting heart sound information from a subject's head are described. A system embodiment includes a headgear to be worn on the subject's head, and first and second sensors to sense respectively first and second physiologic signals each representing vibration, motion, or displacement conducted through patient body tissue. The sensed physiologic signals contain heart sound information. At least one of the first or the second sensor is included in the headgear, and placed at a head location to sense a physiologic signal indicative of heart sounds. The system includes a processor to generate a composite signal using the sensed first and second physiologic signals. The system may generate a heart sound metric using the composite signal, and detect a cardiac event such as an arrhythmia or worsening heart failure.

Abstract: Systems and methods for assessing a cardiac arrhythmia risk of a patient, such as a risk for developing atrial fibrillation, are disclosed. An exemplary medical-device system includes a risk stratifier circuit configured to, in an absence of prior and present atrial arrhythmia, determine a composite risk of the patient developing a future atrial arrhythmia using a trained machine-learning model and a plurality of features of physiological information sensed from the patient and an arrhythmia monitor circuit configured to adjust an arrhythmia monitoring parameter based at least in part on the composite risk and to detect an atrial arrhythmia event using the adjusted arrhythmia monitoring parameter.

Abstract: Systems and methods for assessing a cardiac arrhythmia risk of a patient, such as a risk for developing atrial fibrillation, are disclosed. An exemplary medical-device system includes an arrhythmia predictor circuit configured to receive physiologic information of a patient, and in an absence of atrial tachyarrhythmia in the patient, determine a risk of the patient developing future atrial tachyarrhythmia using the physiologic information. In accordance with the arrhythmia risk indication, the system can generate an alert, or initiate more aggressive monitoring of a patient identified as having a high atrial tachyarrhythmia risk.

Abstract: Systems and methods are disclosed to determine a measure of patient weight using existing medical device sensors, comprising receiving acceleration information of a patient and, if a value of the acceleration information exceeds an activity threshold over a measurement window, detecting patient steps in the measurement window using the acceleration information, determining a patient step rate over the measurement window using the detected patient steps, determining a measure of patient step force for the measurement window, and determining a measure of patient weight using the determined patient step rate and measure of patient step force.

Abstract: Systems and methods for monitoring a heart failure (HF) patient and forecasting the patient's future HF status are discussed. A system includes a HF predictor circuit to generate a monitored sensor trend using sensor data collected up to a prediction time from the patient. The HF predictor circuit can generate a projected sensor trend for the patient over a forecast period of time in future beyond the prediction time using the monitored sensor trend of the patient and sensor trends collected from a plurality of patients. The projection can be based on a non-parametric predictor or a parametric model. A trajectory of the projected sensor trend may be displayed as a visual forecast of the patient's HF status.

Abstract: Systems and methods to provide remote patient monitoring for viral-respiratory symptoms, including coronavirus or COVID-19 symptoms are disclosed, including a signal receiver circuit configured to receive first and second physiologic information of a patient, the first physiologic information comprising respiration rate information of a patient and the second physiologic information different than the first physiologic information, and an assessment circuit configured to determine an indication of patient viral-respiratory disease using the received first and second physiologic information.

Abstract: Systems and methods to detect pneumonia in cardiovascular patients are disclosed, including receiving physiologic information of a patient from an ambulatory medical device (AMD), the physiologic information comprising respiration information of the patient, and determining a pneumonia score of the patient using the received respiration information.

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: Systems and methods for monitoring patients for risk of worsening heart failure (WHF) are discussed. A patient management system includes a receiver to receive patient respiration measurement. A respiratory pattern analyzer circuit measures respiratory pattern indicative of rapid-shallow breathing pattern from the received respiration measurement, and determine a respiratory pattern variability indicator. A risk analyzer circuit determines patient WHF risk using the respiratory pattern variability indicator. The system may use the WHF risk to guide WHF event detection, or to deliver or adjust a heart failure therapy.

Abstract: Systems and methods for assessing a cardiac arrhythmia risk of a patient, such as a risk for developing atrial fibrillation, are disclosed. An exemplary medical-device system includes an arrhythmia predictor circuit configured to receive physiologic information of a patient, and in an absence of atrial tachyarrhythmia in the patient, determine a risk of the patient developing future atrial tachyarrhythmia using the physiologic information. In accordance with the arrhythmia risk indication, the system can generate an alert, or initiate more aggressive monitoring of a patient identified as having a high atrial tachyarrhythmia risk.

Abstract: Systems and methods for detecting heart sound information from a subject's head are described. A system embodiment includes a headgear to be worn on the subject's head, and first and second sensors to sense respectively first and second physiologic signals each representing vibration, motion, or displacement conducted through patient body tissue. The sensed physiologic signals contain heart sound information. At least one of the first or the second sensor is included in the headgear, and placed at a head location to sense a physiologic signal indicative of heart sounds. The system includes a processor to generate a composite signal using the sensed first and second physiologic signals. The system may generate a heart sound metric using the composite signal, and detect a cardiac event such as an arrhythmia or worsening heart failure.

Abstract: Systems and methods for monitoring patients for risk of worsening heart failure (WHF) are discussed. A patient management system includes a receiver to receive patient respiration measurement. A respiratory pattern analyzer circuit measures respiratory pattern indicative of rapid-shallow breathing pattern from the received respiration measurement, and determine a respiratory pattern variability indicator. A risk analyzer circuit determines patient WHF risk using the respiratory pattern variability indicator. The system may use the WHF risk to guide WHF event detection, or to deliver or adjust a heart failure therapy.

Abstract: Systems and methods for monitoring patients for risk of worsening heart failure (WHF) are discussed. A patient management system includes a receiver circuit to receive a heart failure phenotype of the patient including patient demographic information, The system may include a classifier circuit to classify the patient into one of a plurality of phenotypes based on the received heart failure phenotype. The plurality of phenotypes are each represented by multi-dimensional categorized demographics. A detector circuit may detect a WHF event from a physiologic signal using the classified phenotype. The system may include a therapy circuit to deliver or adjust a heart failure therapy in response to the detected WHF 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: A method and system for providing an indication of delivery of a neural stimulation therapy is disclosed. In an example, a method may include identifying current timing of an intermittent neural stimulation (INS) programmed in an implantable medical device (IMD) where the programmed INS includes alternating stimulation ON and stimulation OFF times and a timing for delivering stimulation bursts of a plurality of stimulation pulses during the stimulation burst ON times. An indication of the current timing of the INS may be provided using an INS indicator of an external device.

Abstract: A method and system for providing an indication of delivery of a neural stimulation therapy is disclosed. In an example, a method may include identifying current timing of an intermittent neural stimulation (INS) programmed in an implantable medical device (IMD) where the programmed INS includes alternating stimulation ON and stimulation OFF times and a timing for delivering stimulation bursts of a plurality of stimulation pulses during the stimulation burst ON times. An indication of the current timing of the INS may be provided using an INS indicator of an external device.