14 results about "Left ventricular Stroke volume" patented technology

The invention relates to the technical field of clinical decision support and medical data intelligent analysis, in particular to a critical patient individualized liquid resuscitation decision support system, which is characterized in that a data acquisition unit acquires pulse pressure variation waveform and multi-dimensional physiological data of each stroke volume; a volume benefit analysis channel of the dynamic decision-making unit segments a respiratory cycle, extracts pulse pressure fluctuation characteristics, outputs a per-stroke volume increase probability value through a machine learning classifier, an organ injury early warning channel calculates a blood lactic acid and creatinine clearance rate change rate, and generates an acute kidney injury risk sign in combination with inferior vena cava image verification; the execution control unit sends an infusion control or limit instruction according to the combined state; and the feedback optimization unit adjusts the weight of the model according to the actual value of blood lactic acid removal, and recalculates the probability value, so that individualized precise resuscitation, balance capacity benefit and organ protection are realized, and the treatment safety and effectiveness are improved.

The present application relates to the medical technical field, especially relate to a kind of noninvasive continuous assessment of ejection fraction method, system and storage medium, the method includes: through monitoring device obtains the multiple physiological parameters of the person to be assessed, wherein, multiple physiological parameters include: the stroke volume of the person to be assessed, left ventricular pre-ejection period and pre-ejection period;Then according to formula calculates the ejection fraction of the person to be assessed;Through relevant monitoring device obtains the multiple physiological parameters of the person to be assessed, specifically, stroke volume, left ventricular pre-ejection period and pre-ejection period, then, the ejection fraction of the person to be assessed can be conveniently calculated and obtained according to the formula provided by the present application, since the related parameters for evaluating ejection fraction in the present application can be continuously obtained by noninvasive method, thus the present application provides a kind of noninvasive continuous ejection fraction evaluation method.

The present invention discloses a non-invasive, accessible and cost-effective system for monitoring health parameters of a user. The system relies on extracting RGB signals from a sequence of images of a region of the user's body, which is used to generate PPG signals. The generated PPG signals are used in combination with the weighted average of model (WAM) along with the user's height, body weight and age in order to determine the health parameters. These health parameters may be cardiac parameters of the user, such as the stroke volume, cardiac output and cardiac index. AIML techniques are used to analyse data and provide actionable insights to healthcare professionals, enabling early detection of health issues and timely intervention. The health data of the user is presented in an easy to understand and interactive format. The system may also be used to provide tailored dietary advice and recommendations to the user.

Devices, systems, and methods provide measurements of continuous cardiac output (CCO). A pulmonary artery (PA) catheter—for example, a Swan-Ganz catheter—can be utilized to obtain multiple pressure measurements simultaneously from different locations within the circulatory system, such as in a pulmonary artery, right atrium, right ventricle, vena cava, etc. Continuous pressure measurements from multiple points can provide estimates of heart rate and stroke volume allowing computation of cardiac output along with each beat of the heart without the need for thermodilution.

An apparatus and method for estimating one or more hemodynamic parameters (e.g., cardiac output or stroke volume). Embodiments are based on the idea of incorporating information about vascular tone into hemodynamic parameter estimation to improve accuracy. More specifically, embodiments use measurements of the duration of travel of a blood pulse from the heart along a particular length of an arterial path as a proxy measure for vascular tone and incorporate it into hemodynamic parameter estimation. Embodiments also account for changes in vascular tone between different parts of the circulatory system based on incorporating vascular tone proxy measurements for multiple different arterial paths.

The disclosed concepts are directed to providing protocols, ideas, concepts, designs, methods and systems related to determining vascular compliance of a subject. In particular, blood pressure and arterial flow of first and second arteries (corresponding arteries on the same or contralateral limb) are measured (e.g., as a function of arterial diameter and / or velocity at which blood travels through the arteries). The pulse pressure can be determined from the blood pressure and the pulse quantity can be determined from the arterial flow. Vascular compliance can be determined from the pulse pressure and the volumetric pressure. Therefore, a direct and accurate vascular compliance estimation result can be obtained in a non-invasive manner. Also disclosed is using the determined vascular compliance in a transfer function to obtain accurate hemodynamic parameter estimates (e.g., cardiac output and stroke output) of a subject.

The invention provides a method, equipment and a system for determining an intravascular blood flow velocity field. The method for determining the blood flow velocity field in the blood vessel comprises the following steps: calculating a specific flow curve of a patient relative to an average blood flow waveform under the condition of keeping the blood flow in each blood vessel unchanged so as to determine a time weight coefficient of each to-be-detected cardiac moment; according to a cross-frame image in a sliding window based on a cardiac cycle, a cross-frame blood flow velocity field calculation result is obtained by using an optical flow method, and a cross-frame optical flow guide item energy function is constructed; constructing a time coupling term energy function for constraining the blood flow acceleration according to the multiple groups of adjacent frame images in the sliding window; and determining the blood flow velocity field of the current frame in the sliding window according to the time weight coefficient, the cross-frame optical flow guide item energy function and the time coupling item energy function.

This invention discloses a parameter identification method for a lumped parameter model of systemic circulation, belonging to the field of lumped parameter model technology. The method includes: constructing the state equation of the lumped parameter model of systemic circulation based on Kirchhoff's voltage and current laws to obtain the systemic circulation control equation; calculating the duration ratio of systolic to diastolic phases and stroke volume based on routine clinical measurement data, constructing classic aortic pressure and flow waveforms, and performing registration processing; calculating central venous pressure and flow based on routine clinical measurement data; and using the registered aortic inlet pressure and flow, central venous pressure and flow, and systemic circulation control equations to calculate the values ​​of each parameter in the parameter model. This invention, by periodically stretching the classic reference waveform, matches the waveform extreme values ​​with the patient's measured blood pressure and cardiac output, indirectly reconstructing the aortic inlet pressure and flow curve reflecting individual characteristics under non-invasive conditions, significantly improving the model's individualization and clinical compatibility.

A wearable, non-invasive, and non-intrusive hemodynamic monitoring device is disclosed for continuous monitoring of left ventricular (LV) hemodynamic waveforms and associated cardiovascular parameters. The device includes a flexible body with laterally extending electrode wings and a central rigid housing containing signal acquisition and transmission electronics. In various embodiments, the device includes either two or three wings configured for placement along the midsternal region and over the carotid arteries to enable simultaneous acquisition of electrical and mechanical signals via bioimpedance, ECG / EKG, and accelerometer sensors. Each wing incorporates tetrapolar bioimpedance electrode arrays, current injection electrodes, voltage sensing electrodes, and accelerometers to capture thoracic and cervical physiological signals necessary for estimating parameters such as left ventricular end diastolic pressure, extracellular fluid, left ventricular ejection fraction, cardiac out, stroke volume and QRS measures. The sensor signals are routed through flexible interconnects or magnetic mating connectors to the central housing. The system includes a wireless transmitter module supporting Bluetooth, Wi-Fi, or other wireless standards, a power supply and power management circuitry, and is constructed on ultra-thin, stretchable substrates composed of biocompatible flexible polymers. The modular design also includes user-serviceable magnetic connectors and optional adhesive layers for improved skin contact, thereby enabling continuous, real-time cardiovascular monitoring suitable for ambulatory and remote healthcare environments.

A wearable, non-invasive, and non-intrusive hemodynamic monitoring device is disclosed for continuous monitoring of left ventricular (LV) hemodynamic waveforms and associated cardiovascular parameters. The device includes a flexible body with laterally extending electrode wings and a central rigid housing containing signal acquisition and transmission electronics. In various embodiments, the device includes either two or three wings configured for placement along the midsternal region and over the carotid arteries to enable simultaneous acquisition of electrical and mechanical signals via bioimpedance, ECG / EKG, and accelerometer sensors. Each wing incorporates tetrapolar bioimpedance electrode arrays, current injection electrodes, voltage sensing electrodes, and accelerometers to capture thoracic and cervical physiological signals necessary for estimating parameters such as left ventricular end diastolic pressure, extracellular fluid, left ventricular ejection fraction, cardiac out, stroke volume and QRS measures. The sensor signals are routed through flexible interconnects or magnetic mating connectors to the central housing. The system includes a wireless transmitter module supporting Bluetooth, Wi-Fi, or other wireless standards, a power supply and power management circuitry, and is constructed on ultra-thin, stretchable substrates composed of biocompatible flexible polymers. The modular design also includes user-serviceable magnetic connectors and optional adhesive layers for improved skin contact, thereby enabling continuous, real-time cardiovascular monitoring suitable for ambulatory and remote healthcare environments.

The application relates to the technical field of medical artificial intelligence, and particularly discloses a heart mechanical efficiency evaluation method based on a strain-blood flow coupling model, which comprises the following steps: synchronously collecting electrocardio, heart sound and photoelectric volume pulse wave signals, adopting master-slave clock synchronization and R wave triggering alignment to realize multi-modal signal timing calibration; extracting myocardial strain rate, stroke volume and systolic energy consumption coefficient based on the calibrated signals, and constructing a strain-blood flow coupling efficiency index; dynamically calibrating the coupling efficiency index through a double-parameter self-calibration mechanism of heart rate drift and heart rate change rate; and finally combining multi-scale feature extraction and a gradient boosting decision tree model to output a heart mechanical efficiency grade and an ischemia risk probability; the application solves the problems of missing dynamic load evaluation, isolated multi-modal parameters and insufficient individual difference adaptability in the prior art, and realizes early myocardial ischemia detection sensitivity and wearable device-level real-time monitoring capability.

A stroke volume variation inference apparatus according to an embodiment comprises a memory for storing at least one instruction; and a processor, wherein as the at least one instruction is executed by the processor, central venous pressure (CVP) waveform information is obtained from a catheter inserted into a patient's body, and the central venous pressure waveform information is provided to a pre-trained inference model configured to infer stroke volume variation (SVV) in the heart, such that information about the stroke volume variation for the patient is obtained.

The disclosure relates to a method for assessing fluid responsiveness of a patient (3) connected to a breathing apparatus (2) providing mechanical ventilation to the patient (3). The method comprises the steps of initiating a fluid responsiveness assessment [FRA] period for assessing a degree of fluid responsiveness of the patient (3), determining a pulse pressure variation [PPV] and / or a stroke volume variation [SVV] of the patient (3) during the FRA period, and presenting information indicative of the fluid responsiveness of the patient (3) to an operator of the breathing apparatus (1) based on the determined PPV and / or SVV. The method further comprises the steps of determining a heartrate [HR] or pulse rate [PR] of the patient (3) during baseline ventilation of the patient (3) prior to the FRA period, calculating recommended FRA ventilation settings for the FRA period based on the determined HR and / or PR, wherein the recommended FRA ventilation settings comprises a recommended respiratory rate [RRFRA] and / or a recommended inspiratory-expiratory ratio [I:EFRA], and ventilating the patient (3) using the recommended FRA ventilation settings during the FRA period.