Method and systems provide for reliable, convenient, and cost-effective personalized assessment of hemodynamic status in the ambulatory heart failure patient. The method and apparatus use pulse contour analysis of data obtained through observation of the patient for determination of hemodynamic status, and for determination of day-to-day changes in hemodynamic status. Observational assessment of the patient includes monitoring during activities of daily living including sleeping, sitting and standing. These activities create changes in venous return that are used to evaluate cardiac function or changes in cardiac function. The method and system infer body position by using position and motion information obtained by the system. Changes in cardiac function over time or due to changes in body pose are evaluated for the assessment of hemodynamic status, with a focus on changes resulting from fluid overload.

Method and systems provide for reliable, convenient, and cost-effective personalized assessment of hemodynamic status in the ambulatory heart failure patient. The method and apparatus use pulse contour analysis of data obtained through observation of the patient for determination of hemodynamic status, and for determination of day-to-day changes in hemodynamic status. Observational assessment of the patient includes monitoring during activities of daily living including sleeping, sitting and standing. These activities create changes in venous return that are used to evaluate cardiac function or changes in cardiac function. The method and system infer body position by using position and motion information obtained by the system. Changes in cardiac function over time or due to changes in body pose are evaluated for the assessment of hemodynamic status, with a focus on changes resulting from fluid overload.

An acoustic sensing apparatus and method are disclosed for acoustically surveying the chest area of a subject, and in particular the rib cage. In use the apparatus is placed on the chest, and it includes an arrangement of one or more sound sensors for sensing acoustic signals received from inside the chest. Based on the signal intensities picked up at a plurality of different locations across the chest, the different locations are each classified by a controller as either rib-aligned or intercostal space-aligned. The controller is further adapted to identify one or more sound intensity hotspots (42) within the signal intensity distribution to locate one or more anatomical objects or regions of interest within the chest, such as the heart mitral valve, the heart tricuspid valve, heart aortic valve, and the pulmonary artery as key areas for an auscultation procedure.

A hospitalization management system including a heart failure analyzer that receives diagnostic data including at least sensor data representative of one or more physiological signals sensed from a hospitalized patient using one or more sensors and assesses risk of rehospitalization for the patient using the diagnostic data. The outcome of the risk assessment is used during and following the patient's hospitalization for reducing the risk of rehospitalization.

Systems and methods to determine an indication of patient dehydration are disclosed, including receiving first and second physiologic information of a patient, the first physiologic information including heart sound information of the patient and the second physiologic information different than the first physiologic information, and determining the indication of patient dehydration using the received first and second physiologic information.

Systems and methods to determine an indication of patient dehydration are disclosed, including receiving first and second physiologic information of a patient, the first physiologic information including heart sound information of the patient and the second physiologic information different than the first physiologic information, and determining the indication of patient dehydration using the received first and second physiologic information.

A security platform architecture is described herein. A user identity platform architecture which uses a multitude of biometric analytics to create an identity token unique to an individual human. This token is derived on biometric factors like human behaviors, motion analytics, human physical characteristics like facial patterns, voice recognition prints, usage of device patterns, user location actions and other human behaviors which can derive a token or be used as a dynamic password identifying the unique individual with high calculated confidence. Because of the dynamic nature and the many different factors, this method is extremely difficult to spoof or hack by malicious actors or malware software.

A security platform architecture is described herein. A user identity platform architecture which uses a multitude of biometric analytics to create an identity token unique to an individual human. This token is derived on biometric factors like human behaviors, motion analytics, human physical characteristics like facial patterns, voice recognition prints, usage of device patterns, user location actions and other human behaviors which can derive a token or be used as a dynamic password identifying the unique individual with high calculated confidence. Because of the dynamic nature and the many different factors, this method is extremely difficult to spoof or hack by malicious actors or malware software.

In an approach to smart joint monitoring for bleeding disorder patients, one or more sets of data are received from a smart joint monitor, where the smart joint monitor includes one or more sensors. One or more criticalities are detected, where the one or more criticalities are detected by an artificial intelligence engine based on the one or more sets of data and a global knowledge base. One or more suggestions are determined, where the one or more suggestions are determined by the artificial intelligence engine based on the one or more criticalities and the global knowledge base.

System and method for monitoring vital signs of a subject, such as a sleeping patient. A health monitoring device includes a thermal camera such as an uncooled microbolometer array, to monitor breathing, pulse, core temperature, and other vital signs. An audio sensor, e.g., microphone, may be used for monitoring patient respiratory sounds and other sounds. Further information such as pulse rate, PRV, blood pressure, breathing rate and oxygenation level are derived from these signals. The health monitoring device utilizes acquired signals and higher order data in analyzing patient conditions and behaviors. Higher order data include visual data based upon thermal camera signals and audio data based upon audio sensor signals. A processor is configured to output a health determination relating to one or more health parameters of the patient by inputting one or both of the visual data and the audio data into one or more machine learning models.