The invention disclosed herein relates to improvements in the collection personal health data. It further relates to a Personal Health Monitor (PHM), which may be a Personal Hand Held Monitor (PHHM), that incorporates a Signal Acquisition Device (SAD) and a processor with its attendant screen and other peripherals. The SAD is adapted to acquire signals which can be used to derive one or more measurements of parameters related to the health of a user. The computing and other facilities of the PHM with which the SAD is integrated are adapted to control and analyse signals received from the SAD. The personal health data collected by the SAD may include data related to one or more of blood pressure, pulse rate, blood oxygen level (SpO.sub.2), body temperature, respiration rate, ECG, cardiac output, heart function timing, arterial stiffness, tissue stiffness, hydration, blood viscosity, blood pressure variability, the concentration of constituents of the blood such as glucose or alcohol and the identity of the user.

Devices, systems and methods useable for useable for monitoring a physiological variable in a target tissue or body fluid located within the thorax of a subject by optical spectroscopy.

Systems and methods and devices are provided for treating conditions such as heart failure and/or pulmonary hypertension by at least partially occluding flow through the superior vena cava for an interval spanning multiple cardiac cycles. A catheter with an occlusion device is provided along with a controller that actuates a drive mechanism to provide at least partial occlusion of the patient's superior vena cava, which reduces cardiac filling pressures, and induces a favorable shift in the patient's Frank-Starling curve towards healthy heart functionality and improved cardiac performance. The occlusion device may include a lumen obstructed by a relief valve that may permit fluid flow through the occlusion device to release an excessive build-up of pressure.

Systems, methods, devices, and techniques for estimating a heart disease prediction of a mammal. An electrocardiogram (ECG) procedure is performed on a mammal, and a computer system obtains ECG data that describes results of the ECG over a period of time. The system provides a predictive input that is based on the ECG data to a predictive model, such as a neural network or other machine-learning model. In response, the predictive model processes the input to generate an estimated heart disease predictive characteristic of the mammal. The system outputs the estimated heart disease prediction of the mammal for presentation to a user.

A method for measuring cardiac pressure includes positioning a fluid-filled catheter and a pressure wire sensor at a cardiac pressure calibration location. A first pressure measurement is acquired from the fluid-filled catheter and a second pressure measurement is acquired from the pressure wire sensor. A set of equalization parameters is identified to apply to the first pressure measurement to reduce an error between the first pressure measurement and the second pressure measurement. The equalization parameters include a frequency correction parameter and a damping correction parameter to correct for frequency and damping of oscillations in the first pressure measurement. A third pressure measurement is acquired from the fluid-filled catheter. The set of equalization parameters is applied to equalize the third pressure measurement.

The present invention relates to a blood vessel image processing method, a blood vessel image processing apparatus, a computer storage medium, and an imaging device. The method includes: obtaining blood vessel geometric structure information of a blood vessel segment of interest; obtaining vital feature information of the blood vessel segment; establishing an association relationship between the blood vessel geometric structure information and the vital feature information; and displaying the blood vessel geometric structure information and the vital feature information in the same image in a mutual fusion manner by using the association relationship as a reference. In this way, work efficiency of users can be improved by the solution.

A system and method for cardiac function and myocardial strain analysis include techniques and structure for classifying a set of cardiac images according to their views, detecting a heart range and valid short-axis slices in the set of cardiac images, determining heart segment locations, segmenting heart anatomies for each time frame and each slice, calculating volume related parameters, determining key physiological time points, calculating myocardium transmural thickness and deriving a cardiac function measure from the myocardium transmural thickness at the key physiological time points, estimating a dense motion field from the key physiological time points as applied to the set of cardiac images, calculating myocardial strain along different myocardium directions from the dense motion field, and providing the cardiac function measure and myocardial strain calculation to a user through a user interface.

Apparatus, systems, and methods for monitoring a sensor module mounted in a sensor platform, wherein the sensor platform includes an adhesive side and a pocket, wherein the pocket is designed to receive the sensor module, to facilitate sensing by the sensor module of physiological attributes, and to allow insertion and removal of the sensor device from the pocket.

Novel tools and techniques for assessing, predicting and/or estimating effectiveness of hydration of a patient and/or an amount of fluid needed for effective hydration of the patient, in some cases, noninvasively.

A method and apparatus for monitoring a subject's autoregulation function state is provided. The method includes: a) continuously sensing a tissue region of the subject with a tissue oximeter, the sensing producing first signals, and determining frequency domain tissue oxygen parameter values; b) continuously measuring a blood pressure level of the subject using a blood pressure sensing device, the measuring producing second signals, and determining frequency domain blood pressure values; c) determining a coherence value indicative of the subject's autoregulation state in each of a plurality of different frequency bands; and d) determining a peak coherence value indicative of the subject's autoregulation state based on the determined coherence value from each of the plurality of different frequency bands.