253 results about "Hemodynamics" patented technology

The invention provides an early-stage automatic identification method and system for acute kidney injury related to cardiac surgery, and relates to the technical field of physiological parameter detection. The method comprises the following steps: acquiring average arterial pressure, cardiac blood discharge volume, central venous pressure and blood oxygen saturation, regularly recording and extracting data of adjacent time points, calculating a variation range, screening a mutation region, judging whether a reference range is exceeded or not, analyzing a multi-parameter synchronous variation condition, and marking a hemodynamics abnormal state. According to the method, abnormal changes of hemodynamics and urine metabolism are accurately recognized through real-time monitoring and multi-parameter analysis, the urine flow rate and the metabolite excretion rate are combined, misjudgment of a single index is avoided, the fineness of renal function change analysis is improved, the high-risk time period is accurately positioned through time cross comparison, the diagnosis accuracy is improved, and the diagnosis accuracy is improved. Trend analysis and risk grade division enable the change of the illness state to be more visual, and a real-time early warning system effectively monitors the fluctuation trend, optimizes clinical management and improves the timeliness of medical response.

The invention relates to a coronary artery fractional flow reserve non-invasive evaluation method fused with hemodynamics, and belongs to the technical field of medical detection, and the method comprises the following steps: obtaining coronary artery CT image data, carrying out preprocessing, and extracting a coronary artery three-dimensional geometric model; constructing a neural network fused with hemodynamics, and adding a residual term of a Navier-Stokes equation and a residual term of a Murray law into a loss function; collecting a real training sample, and generating numerical simulation data as a training data set; s4, training and optimizing the neural network fused with hemodynamics to minimize an error between an output result of the network and an FFR training value, and satisfying constraint conditions of a Navier-Stokes equation and a Murray law at the same time; and S5, processing the coronary artery CT image data by using the trained network model fused with hemodynamics to obtain a predicted FFR value.

The invention relates to the technical field of medical image processing and medical aid decision making, in particular to an internal arteriovenous fistula intelligent planning method and system based on haemodynamic simulation, and the method comprises the steps: firstly obtaining three-dimensional space anatomical data of arteriovenous blood vessels of a patient, and constructing a blood vessel tree three-dimensional model; and inputting the blood vessel parameter data and the hemodynamic parameter data at different blood flow rates into a deep learning model to obtain dynamic shear force data of the anastomotic stoma, and comparing the dynamic shear force data of the anastomotic stoma with preset optimal anastomotic angle data to determine an optimal anastomotic angle. And performing internal arteriovenous fistula operation type three-dimensional modeling on the three-dimensional model of the vascular tree by combining the optimal anastomosis angle to obtain a three-dimensional internal arteriovenous fistula model, and performing a virtual operation based on the model to obtain virtual operation process data and a postoperative hemodynamic state evaluation result. The success rate of one-time operation of internal fistula can be increased to 85%-90% from 60%-65% in the prior art.

The invention discloses an AI robot assisted esophageal ultrasonic detection system and method. The system comprises a control type mechanical arm and a multi-mode sensing probe. The AI robot control module is configured to control the insertion depth, the deflection angle and the contact pressure of the multi-mode sensing probe through the control type mechanical arm; the signal processing module is used for carrying out synchronous acquisition and noise reduction processing on the temperature data, the ultrasonic imaging data, the optical image data, the contact force data, the impedance data and the blood flow signals; and the AI engine module is based on multi-modal data fusion, is provided with a pre-trained deep learning model, and is used for generating an esophageal wall structure in real time, extracting hemodynamics and focus features and optimizing an examination path. Through a multi-mode sensing probe, intelligent robot control and a multi-source data fusion AI algorithm, accurate evaluation of the esophageal structure and function is realized. The accuracy, the safety and the efficiency of digestive tract disease diagnosis are remarkably improved by combining adaptive path planning and a lesion automatic classification technology.

The invention provides a multi-modal AI diagnosis and risk grading system, method and device suitable for vascular diseases, a medium and a program product, and provides an innovative method for cardiovascular diagnosis of old people by combining hemodynamics and structural indexes and utilizing a multi-modal deep learning framework. According to the method, the diagnosis accuracy is improved, and the prediction capability is enhanced through operable risk scoring. The method is unique in that double diagnosis of functions and structures is integrated, and compared with a traditional method focusing on single diagnosis, the method provides more comprehensive cardiovascular health assessment. Besides, the system has high applicability and expandability, can be integrated with clinical and wearable equipment, and realizes real-time monitoring and risk assessment. In the future, the system can further enlarge the diagnosis range by incorporating data such as biomarkers and the like, and shows good future adaptability.

The invention discloses an information processing method and device for intracranial aneurysm hemodynamic prediction, equipment and a medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: receiving a three-dimensional medical image containing an intracranial aneurysm, inputting the three-dimensional medical image into a target hemodynamic prediction model, and capturing the comprehensive morphological characteristics of the intracranial aneurysm from the three-dimensional medical image; inputting the blood flow boundary condition into the target hemodynamics prediction model, and performing low-dimensional mapping on the blood flow boundary condition to obtain a first low-dimensional feature vector; receiving a spatial point coordinate and a directional distance corresponding to each sampling point in the CFD model formed in the intracranial aneurysm area, and performing low-dimensional mapping on the spatial point coordinate and the directional distance to obtain a second low-dimensional feature vector; and performing feature fusion on the comprehensive morphological features, the first low-dimensional feature vectors and the second low-dimensional feature vectors through a feature fusion module to predict hemodynamic parameters. And end-to-end hemodynamic parameter prediction is realized.

The invention discloses an external chest compression parameter adjustment method based on thoracic impedance hemodynamics guidance, and belongs to the technical field of external chest compression parameter adjustment. The method comprises the following steps: acquiring a global optimal compression parameter combination through a trained global relationship model to guide initial external chest compression; real-time chest impedance signals are obtained, variational mode decomposition is carried out, and real-time hemodynamic data caused by pressing are determined; performing personalized transfer learning on the global relation model by combining the real-time pressing parameters and the real-time hemodynamic data, and updating a personalized optimal pressing parameter combination; the global relation model is constructed by using an improved Elman neural network, and the improved Elman neural network introduces a physical correction layer for the flow characteristics of blood in deformed blood vessels. The compression parameter adjustment in the actual external chest compression process can be guided to realize optimal compression, and the compression quality is improved; the problems that hemodynamic components are not considered in existing external chest compression, and the compression quality needs to be improved are solved.

The invention relates to the technical field of data analysis, and discloses a data analysis method and system for blood donation service platform supervision, and the method specifically comprises the steps: collecting the dynamic physiological index data of a target blood donor in real time, meanwhile, historical blood donation records, blood donor family health association map data and real-time environment parameters provided by environment monitoring equipment are called from a blood donation service platform database; performing individualized health risk prediction analysis through the deep learning model, and outputting a predicted health risk value; performing multi-dimensional endurance capacity analysis on the high-risk blood donors, and calculating individual tolerance attenuation coefficients; establishing a hemodynamic safety evaluation model, and outputting a blood donation safety value representing a blood donation safety boundary; and generating a three-level response strategy instruction according to the blood donation safety value, and dynamically optimizing the service process of the blood donation service platform. According to the method, the problems of blood quality fluctuation and resource waste caused by blood donation adverse reaction caused by insufficient risk pre-judgment of the blood donors in the prior art are solved.

The invention provides an intelligent decision-making method and system for free flap riser anastomosis based on hemodynamics. According to the method, firstly, the blood flow direction, the flow speed and the blood vessel wall tension parameter of a target blood vessel are collected, and a dynamic correlation model of intravascular fluid mechanics and external tissue deformation is established; a three-dimensional blood flow pressure gradient map is generated based on the model, then, a system automatically screens an anastomosis path meeting a blood flow resistance threshold value and the endothelial cell survival rate requirement, and the optimal anastomosis pose is determined by analyzing the blood vessel wall elasticity matching degree and the turbulence generation probability. Then, guiding the accurate adjustment of the clamping direction of the blood vessel and the suture needle pitch in the operation, ensuring that the pressure of the lumen of the anastomosed blood vessel is kept balanced when the anastomosed blood vessel is axially stretched, meanwhile, effectively inhibiting local vortex, and remarkably improving the long-term smoothness of the anastomosis of the blood vessel. According to the method, mechanical precise matching and blood flow stable control of free flap vascular anastomosis are achieved, and the postoperative risk is remarkably reduced.

A physiological information display apparatus includes a reception unit configured to receive a start signal and an end signal, the start signal indicating a start timing of a treatment for a subject, the end signal indicating an end timing of the treatment, a calculation unit configured to calculate a moving average value of a pulse wave transit time of the subject, a hemodynamic parameter of the subject, using the calculated moving average value, and a change rate of the hemodynamic parameter in a period from the start timing to the end timing, based on the start signal and the end signal received by the reception unit, and a display controller configured to output, to a display, the change rate calculated by the calculation unit.

The invention relates to a method for estimating the fractional flow reserve (FFR) of a vessel, including: - acquiring (ACQ1) a first image from an imaging system; - extracting (EXT1) a first data set (ENS1) defining anatomical descriptors of a first vessel; - acquiring (ACQ2) a second data set (ENS2) including at least the heart rate, the systolic pressure and the myocardial mass; and - generating (GEN1) an output (S1) defining a prediction of a fractional flow reserve (FFR) quantity by executing a first machine learning model (MLA1) to produce an output (S1), the first machine learning model (MLA1) implementing a parameterisable loss function including at least a first factor modelling at least one optimised parameterised physical constraint when training the model (MLA1), the parameterised physical constraint resulting in particular from a digital model of hemodynamic equations (MOD1).

The invention discloses an application of beta-alanine in preparation of a medicine for treating pulmonary arterial hypertension. In-vivo and in-vitro pharmacological experiments prove that beta-alanine can inhibit lactic acid-mediated histone milk acylation modification and hypoxia-induced phenotypic transformation of PASMCs (Polyaspartic Sulfonate Molecules); the hemodynamics and pulmonary artery vascular remodeling of the PAH mouse are improved. The beta-alanine can inhibit phenotypic transformation of PASMCs and reverse pulmonary artery vascular remodeling which is a key pathological change in the pulmonary hypertension generation process, has huge potential in treatment of pulmonary hypertension, and has good application prospects and high clinical application value.

A hemodynamic sensor system can determine a likelihood of effectiveness of the intervention for hypotension of the patient. The system can receive, from a hemodynamic sensor, a test analog hemodynamic sensor signal from the patient and convert, using an analog-to-digital converter, the test analog hemodynamic sensor signal to a test arterial pressure signal waveform. The system can extract from the test arterial pressure signal waveform a plurality of test heart health parameters from a set of available heart health parameters and generate, using a plurality of reference arterial pressure signal waveforms from a plurality of patients, one or more filtered sets of reference heart health parameters. The system can consolidate the filtered sets of reference heart health parameters into corresponding reference feature pools and determine normalized test maximum features from the plurality of test heart health parameters. The system can determine the likelihood of effectiveness of the intervention.

The present disclosure provides novel immunoglobulin proteins that bind to a human natriuretic peptide receptor 1 (NPR1) agonist, preferably an anti-NPR1 antibody. In certain embodiments, the proteins of the disclosure comprise at least one immunoglobulin variable domain that binds to an anti-NPR1 antibody. In certain embodiments, the proteins of the disclosure are useful in blocking and / or reversing the effect of an administered anti-NPR1 antibody. In certain embodiments, the antigen-binding proteins are useful for effective management of blood pressure and hemodynamics in humans.

The invention discloses an image processing method and system for zebra fish flowing blood cell recognition. According to the method, aiming at the problems of cell blurring, stretching and overlapping caused by long-time exposure in microscopic imaging, a complete process including image preprocessing, Transform-based target detection model training and self-adaptive post-processing is constructed. The preprocessing improves the image quality by enhancing the cell edge and the contrast ratio; the detection model performs end-to-end localization on cells by using an improved DETR structure; and in post-processing, an optimal threshold value is automatically selected according to different scenes so as to obtain a stable counting result. According to the method, high recognition precision can be achieved under the complex deformation condition, the good experiment condition generalization ability is achieved, and the method can be used for high-throughput zebra fish hemodynamics research and other scenes.

The invention discloses a brain load assessment method and system based on hemodynamic information and electroencephalogram signals, and relates to the field of brain-computer interface classification systems. The technical problem that how to fuse electroencephalogram signals and hemodynamic information and comprehensively utilize complementary characteristics of the electroencephalogram signals and the hemodynamic information in time and space dimensions to achieve accurate recognition and dynamic evaluation of the mental load state in the prior art is urgently needed to be solved in the current brain-computer interface field is solved. The method comprises the following steps: acquiring EEG data and fNIRS data of a testee; performing preprocessing, selecting a suitable frequency band, removing interference such as high-frequency noise and low-frequency baseline drift, and constructing a corresponding training data set; respectively constructing an EEG single-mode network and an fNIRS single-mode network which are used for extracting related characteristics; and constructing an EEG-fNIRS multi-mode classification network for fusing data of brain imaging modes in the EEG single-mode network and the fNIRS single-mode network, and performing classification evaluation on the hemodynamic information of the subject and the brain power load data of the electroencephalogram by using the EEG-fNIRS multi-mode classification network.

The invention belongs to the technical field of medical image modeling, and particularly relates to a urinary system blood vessel modeling method based on 3D Gaussian splashing and a surgical robot navigation method.The blood vessel modeling method comprises the steps that a data source is preprocessed, and a urinary system blood vessel model is constructed; describing the center line and the section shape of the blood vessel based on a Bezier curve and an NURBS curve, and realizing dynamic 3DGS modeling of the blood vessel; dynamic 3DGS modeling, finite element analysis and computational fluid mechanics are combined, and hemodynamics simulation is achieved through a two-way mapping algorithm of Gaussian parameters and finite element grids. Compared with the prior art, the method solves the problem that in the prior art, due to the fact that a high-precision model for the dynamic characteristics of the blood vessels of the urinary system is lacked, accurate navigation and operation of urinary system interventional operation are difficult. According to the scheme, a high-precision model is constructed for urinary system blood vessels (such as renal arteries and bladder blood vessels) based on the three-dimensional Gaussian sputtering technology, and precise navigation and operation of urinary system interventional operations are effectively assisted.

The invention relates to the technical field of emergency medicine, in particular to an emergency department patient all-dimensional monitoring and emergency treatment system which comprises a patient information management unit, a real-time detection unit, a behavior feature recognition unit, an intelligent early warning and decision support unit and a remote cooperation and communication unit. According to the invention, through a multi-mode monitoring architecture special for trauma and a dynamic anti-interference mechanism, accurate and continuous monitoring of hemodynamics and vital signs of an acute trauma patient is realized, hidden shock and other critical conditions are effectively identified, and non-contact multi-mode perception and intelligent behavior analysis technologies are utilized to realize accurate and continuous monitoring of the acute trauma patient. Behavior characteristics such as the body surface temperature, the body position micro-motion and the voiceprint of the patient are converted into clinical risk indexes, potential risks are warned in advance, multi-dimensional and high-precision monitoring and warning are provided for the emergency treatment trauma patient, and the timeliness and the accuracy of emergency diagnosis are remarkably improved.

The invention provides a multi-mode ultrasonic monitoring method for degradation of a PFO degradable plugging device, and relates to the technical field of cardiovascular ultrasonic medical treatment. The multi-mode ultrasonic monitoring method for degradation of the PFO degradable occluder aims to overcome the technical defects that in the prior art, a single ultrasonic mode cannot achieve degradation progress quantification of the occluder, precise identification of residual shunt and evaluation of the integration degree of surrounding myocardial tissue at the same time. According to the method, three modalities of real-time three-dimensional transthoracic ultrasound (RT-3D TTE), ultrasonic contrast (CEUS) and shear wave elastography (SWE) are cooperatively applied, the form, hemodynamics and tissue elasticity data of the occluder are collected in stages, non-invasive, dynamic and accurate monitoring of the whole degradation process of the occluder is achieved in combination with preset quantitative indexes, and a reliable basis is provided for clinically adjusting a treatment scheme.

A method, system, device and storage medium for measuring and classifying CT-FFR, dividing lesions into different types according to coronary artery computed tomography angiography (CCTA) images, determining lesion lengths at lesion positions according to different lesion types, and determining the lesion lengths at the lesion positions according to different lesion types. Then, the measurement range of computed tomography fractional flow reserve is determined according to the focus lengths of different lesion types, a statistical matrix is established to calculate the numerical values of all computed tomography fractional flow reserve CT-FFR in the measurement range, and finally, hemodynamic classification is conducted on calculation results. According to the CT-FFR evaluation method, the accuracy and the stability of CT-FFR evaluation are enhanced by carrying out pathological change specificity classification on the pathological change in the haemodynamics sense, interference is reduced, and a more reliable solution is provided for clinicians and patients.

This invention discloses a method, device, electronic equipment, and medium for assessing the risk of pulmonary embolism. It relies entirely on collected non-invasive objective data and eliminates subjective judgments based on medical history or physician experience, effectively avoiding risk misjudgments caused by subjective variables in the PESI / sPESI model. This ensures the consistency and reliability of the assessment results. The ratio of Qa to Qb is used as the core assessment indicator. This ratio is a continuous variable, eliminating the need for empirical segmentation of parameters and avoiding significant differences in assessment results among patients with similar conditions. The risk level is assessed based on the ratio of Qa to Qb obtained through hemodynamic simulation. The results perfectly match clinical understanding of the severity of pulmonary embolism, improving assessment accuracy. Simultaneously, it reduces patient examination trauma and avoids high equipment and operational costs.

The invention relates to a blood flow parameter measuring device, equipment, a storage medium, an ultrasonic probe and a system, and belongs to the field of medical instruments. The blood flow parameter measuring device comprises a first obtaining module used for obtaining a first measuring parameter obtained by a first transducer group in an imaging mode; the second acquisition module is used for acquiring a second measurement parameter acquired by the second transducer group in the imaging mode or the Doppler blood flow detection mode; the first measurement parameter and the second measurement parameter both comprise a blood vessel position, a blood vessel depth, a blood vessel diameter and a Doppler included angle; the correction module is used for performing combined calculation on the first measurement parameter and the second measurement parameter and correcting the blood vessel diameter and the Doppler included angle; and the monitoring module is used for monitoring hemodynamic parameters of the target object according to the corrected blood vessel diameter and Doppler included angle. According to the technical scheme, the stable hemodynamics evaluation result can be output.

The invention relates to the technical field of medical image early warning, and discloses a cerebral apoplexy early warning method based on a cerebrovascular image representation group. The method comprises the following steps: acquiring a cerebrovascular image sequence, and constructing multi-modal information containing a vascular structure and hemodynamics; based on this, a multi-level representation network is constructed, and a dynamic time-varying risk representation graph is generated through node interaction and space-time modulation. Then performing multi-scale grid segmentation on the risk map to obtain a plurality of local evaluation units, and synchronously screening out candidate units with abnormal evolution according to a preset risk dynamics model; and aggregating the candidate unit features to generate a global risk evolution path, backtracking and positioning to a high-risk frame set in the original image, and outputting an early warning signal after feature decoupling and recombination. According to the method, quantitative tracking and early-stage accurate positioning of the dynamic evolution process of the stroke risk in the space-time space are realized.

A flexible wristband system for monitoring hemodynamics and recognizing gestures, relating to the technical field of medical health monitoring and chalcogenide integrated photonics, and comprising: a wristband apparatus (3), an electric pulse generating apparatus (1), a signal light generating apparatus (2), a control device (4), and an information receiving, processing and display device (5), wherein a signal output end of the electric pulse generating apparatus (1) is electrically connected to a signal input end of the wristband apparatus (3), a signal output end of the signal light generating apparatus (2) is connected to the signal input end of the wristband apparatus (3) by means of an optical fiber, and signal input ends of the electric pulse generating apparatus (1), of the signal light generating apparatus (2) and of the information receiving, processing and display device (5) are all connected to a signal output end of the control device (4). The flexible wristband system can improve detection sensitivity and the capability of detecting weak signals.

A neural network is trained for estimating patient hemodynamic data using a plurality of extravascular imaging data sets and a plurality of intravascular imaging data sets that are each co-registered to a corresponding extravascular imaging data set. A plurality of hemodynamic data sets are provided, each hemodynamic data set co-registered with the corresponding extravascular imaging data set. The neural network learns what hemodynamic data to expect for a given intravascular imaging data set. An intravascular imaging event is subsequently performed in which an intravascular imaging element is translated within a blood vessel of the patient to produce one or more intravascular images. The neural network uses its training to predict hemodynamic values corresponding to the one or more intravascular images from the intravascular imaging event, and the one or more intravascular images are outputted in combination with the predicted hemodynamic values.

A physiological information display apparatus includes a heart rate acquisition unit configured to acquire a heart rate of a subject, a respiration rate acquisition unit configured to acquire a respiration rate of the subject, a hemodynamics calculation unit configured to calculate a hemodynamic parameter of the subject, and a respiratory variation of the hemodynamic parameter, based on a plurality of the hemodynamic parameters calculated in a predetermined period, and a display controller configured to output the respiratory variation to a display. The hemodynamics calculation unit is configured to calculate a heart rate in one respiration. The display controller is configured to output a setting screen for setting a length of the predetermined period. The hemodynamics calculation unit is configured to acquire setting information, set the length of the predetermined period based on the acquired setting information; and calculate the respiratory variation in the set predetermined period.

A method for providing patient hemodynamic information includes obtaining a three-dimensional electronic model of the patient's coronary artery, obtaining first and second boundary condition model value sets, and performing first and second three-dimensional computational fluid dynamics (CFD) simulations of the model based on the first and second boundary condition model value sets. For each CFD simulation, a first pressure drop between a first location and a second location of the coronary artery is calculated. The method further includes determining, based on the first and second pressure drops, patient-specific parameters, determining an inflow rate boundary condition based on the patient-specific parameters, performing a third three-dimensional CFD simulation of the coronary artery model based on the inflow rate boundary condition, and calculating, according to the third CFD simulation, a third pressure drop for any location in the coronary artery model.

The present disclosure relates to a proximity sensor circuit and related sensing methods. Various embodiments include devices and methods using a proximity sensor. Example devices include: a transducer circuit having a sensor circuit that includes electrodes; an electrical signal sensing circuit; a substrate that supports and at least partially encloses the transducer circuit and the electrical signal sensing circuit; and a communication circuit. The transducer circuit converts a change in capacitance, which is carried by the electrodes and responsive to pressure and / or electric field modulation caused by a hemodynamic or pulse wave event, into an electrical signal. The electrical signal sensing circuit senses an event in response to the electrical signal from the transducer circuit. The substrate may mate with a portion of a user and position the sensor circuit close enough to the user's skin to inductively sense a hemodynamic or pulse wave event. The communication circuit responds to the electrical signal sensing circuit by transmitting data indicative of hemodynamic monitoring.

The utility model relates to the technical field of ultrasonic imaging, in particular to a novel designed probe suitable for newborn lung ultrasonic scanning, which comprises a probe body, a tail section scanning area and a back side scanning area, according to the newborn lung ultrasonic scanning probe, the novel design probe which is similar to a hockey ball and suitable for newborn lung ultrasonic scanning is arranged, and the ultrasonic transducers are arranged in the tail section scanning area and the back side scanning area of the hockey ball probe body; required data can be completely and quietly collected with low disturbance without greatly changing the body position, the examination operation time is greatly shortened, the time deviation is reduced, the blood flow of a child patient is stable, interference factors are reduced, and the consistency of the imaging background of the collected 12-partition image is greatly improved.

The application discloses a blood flow guiding dense mesh stent preoperative prognosis evaluation method and device based on hemodynamics, equipment and a storage medium, which comprises the following steps: constructing a three-dimensional blood vessel geometric model based on medical image data of a patient, performing hemodynamic simulation, obtaining a jet path in a tumor cavity, virtually implanting the blood flow guiding dense mesh stent in the three-dimensional blood vessel geometric model, obtaining a stent center line of the stent located in the tumor cavity, calculating a jet compliance index for prognosis evaluation based on the jet path in the tumor cavity and the stent center line, constructing a jet compliance comprehensive index based on the first jet compliance index, the second jet compliance index and the third jet compliance index, and performing prognosis evaluation on the preoperative curative effect of the blood flow guiding dense mesh stent according to the comprehensive index, so that the reliability of prognosis prediction is improved.