420 results about "Hemodynamics" patented technology

A noninvasive patient-specific method is provided to aid in the analysis, diagnosis, prediction or treatment of hemodynamics of the cardiovascular system of a patient. Coronary blood flow and pressure can be predicted using a 3-D patient image-based model that is implicitly coupled with a model of at least a portion of the remaining cardiovascular system. The 3-D patient image-based model includes at least a portion of the thoracic aorta and epicardial coronaries of the patient. The shape of one or more velocity profiles at the interface of the models is enforced to control complex flow features of recirculating or retrograde flow thereby minimizing model instabilities and resulting in patient-specific predictions of coronary flow rate and pressure. The invention allows for patient-specific predictions of the effect of different or varying physiological states and hemodynamic benefits of coronary medical interventions, percutaneous coronary interventions and surgical therapies.

The invention provides an electromagnetic photoacoustic synchronous integrated brain function imaging method and device, and relates to the field of multi-mode brain function imaging research. According to the invention, electroencephalogram, magnetoencephalogram, functional near infrared spectrum and functional ultrasonic imaging technologies are fused, important advantage complementation is formed in signal specificity and temporal-spatial resolution, and neural activity can be described from the angle of human cranial nerve electrophysiology and neural metabolism can be observed from hemodynamic information at the same time. And electrophysiology and hemodynamic activities of the brain can be synchronously recorded.

The invention discloses an electrophysiology and hemodynamics multi-mode intelligent wearable system and a data evaluation method, and belongs to the technical field of biomedical engineering, the system comprises an optical module, a flexible stretchable electric signal module and a central module; the optical module is used for collecting hemodynamic signals including an oxyhemoglobin change signal, a deoxygenated hemoglobin change signal and a pulse wave signal by combining a near-infrared light signal with hemodynamics; the flexible stretchable electric signal module collects electric signals, including electroencephalogram signals, electromyographic signals, electrocardiosignals and electro-oculogram signals, of all parts through electrodes; the central module is used for digitalizing and preprocessing the hemodynamic signal and the electric signal of each part, fusing multi-modal data, evaluating data quality and predicting a dominant external event influencing the data quality; and meanwhile, data quality and dominant external events are output to the terminal to feed back and adjust acquisition parameters of the optical module and the flexible stretchable electric signal module, so that the effectiveness and practicability of monitoring are remarkably improved.

Anatomical and functional assessment of coronary artery disease (CAD) using machine learning and computational modeling techniques deploying methodologies for non-invasive Fractional Flow Reserve (FFR) quantification based on angiographically derived anatomy and hemodynamics data, relying on machine learning algorithms for image segmentation and flow assessment, and relying on accurate physics-based computational fluid dynamics (CFD) simulation for computation of the FFR.

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.

Computer-implemented methods and systems are provided for quantitative hemodynamic flow analysis, which involves retrieving patient specific image data. A 3D reconstruction of a vessel of interest can be created from the patient specific image data. Geometric information can be extracted from the 3D reconstruction. A lesion position can be determined. Patient specific data can be obtained. Hemodynamic results can be calculated based on the geometric information, the lesion position and the patient specific data.

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 belongs to the technical field of medical instruments, and particularly relates to a dense net support. The dense net support comprises a front fixing section, a blocking section and a rear fixing section, and the blocking section is located between the front fixing section and the rear fixing section. The plugging section is connected with the front fixing section through a front connecting piece, and the plugging section is connected with the rear fixing section through a rear connecting piece; the plugging section is used for plugging an aneurysm position of a blood vessel, the plugging section sequentially comprises an inner layer part, a middle layer part and an outer layer part from inside to outside, the inner layer part adopts an inner layer metal stent, and the outer layer part adopts an outer layer metal stent. The dense net stent can adjust hemodynamics more accurately, and it is ensured that the blood flow of healthy blood vessels is not affected while the aneurysm is closed; the sealing effect of the aneurysm is ensured, and thrombosis is well promoted, so that blocking and healing of the aneurysm are promoted; and the endothelialization process of the stent is facilitated, so that the success rate of fusing the stent into the blood vessel is improved, the effect of completely sealing the aneurysm opening is achieved, and the recurrence risk is reduced.

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 belongs to the technical field of ultrasonic imaging, and particularly relates to a phase distortion correction method for craniocerebral ultrasonic imaging. The method comprises the following steps: acquiring ultrasonic echo data in a skull scene and a B-mode image obtained after beam forming; identifying the skull boundary of the transcranial B-mode image, and constructing a craniocerebral sound velocity model; solving a sound wave travel time matrix under the current sound velocity model on the basis of a ray theory method or an EiKonal equation, and applying the sound wave travel time matrix to beam forming to obtain an image after phase distortion correction; and a transcranial imaging result after beam forming is optimized, including space-time signal filtering processing, Doppler processing, microbubble detection positioning and tracking processing and compensation processing of signal attenuation caused by skull reverberation. According to the method, the axial blood flow velocity estimation precision can be greatly improved, the spatial resolution and saturation of an imaging result are improved, and high-quality skull imaging and hemodynamics and brain function research are facilitated.

A system having a processor obtain a digital hemodynamic data from a hemodynamic sensor, obtain one or more vital sign parameters characterizing vital sign data from the digital hemodynamic data, derive differential parameters based on the one or more vital sign parameters, generate combinatorial parameters using the one or more vital sign parameters and the differential parameters, determine a risk score corresponding to a probability of a future hypotension event for the living subject based on a weighted combination of a plurality of hypotension profiling parameters including the one or more vital sign parameters characterizing vital sign data, the differential parameters and the combinatorial parameters, and invoke a sensory alarm if the risk score satisfies a predetermined risk criterion.

The invention relates to the technical field of medical engineering, in particular to a hemodynamic simulation analysis system for coronary stent implantation. The system comprises a coronary blood vessel anatomical structure aided design module, a coronary stent finite element model design module, a post-implantation hemodynamic simulation analysis module and a pre-implantation and post-implantation blood flow state evaluation module, and can obtain coronary medical image data of a patient and perform blood vessel anatomical structure geometric analysis and blood vessel three-dimensional model aided design. Generating a three-dimensional model of the coronary vessel anatomical structure of the patient; a coronary stent finite element model is designed and generated through a geometric feature set of the coronary stent, a hemodynamic feature parameter set before stent implantation is obtained, blood flow boundary limitation analysis and coronary stent implantation dynamics simulation analysis are carried out, and meanwhile blood flow state evaluation analysis before and after stent implantation is carried out. And generating a blood flow state simulation evaluation report before and after stent implantation. According to the method, the change of the blood flow state after the stent is implanted can be efficiently and accurately analyzed.

The invention discloses a method and a system for visually identifying hemodynamic spatial-temporal heterogeneity in breast tumors, and belongs to the technical field of medical image acquisition and auxiliary detection. The method for visually recognizing the hemodynamic spatial-temporal heterogeneity in the breast tumor comprises the steps that S1, DCE-MRI images of breast benign and malignant tumors are obtained, and region-of-interest sketching is carried out; s2, carrying out TIC automatic classification and coding on each voxel in the tumor by adopting 19 types of TIC curves to obtain a TIC color coding graph; s3, calculating the TIC type and proportion of each focus, and extracting a TIC color coding map to reflect radiomics characteristics of tumor internal heterogeneity; s4, screening the image omics characteristics of the TIC color coding image, and establishing three models including 19 types of TIC curve fusion models; according to the method, the difference of hemodynamics time and space heterogeneity in the breast tumor of the patient can be visually judged and compared, and benign and malignant and biological behaviors of the tumor of the patient are judged.

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.

A method for monitoring peripheral blood flow of a patient using a wearable device includes monitoring peripheral blood flow of the patient under a first physiologic condition and monitoring peripheral blood flow of the patient under a second physiologic condition different than the first physiologic condition. A dimensionless relative index of the monitored peripheral blood flow of the patient i) under the second physiologic condition based on the monitored peripheral blood flow under the first physiologic condition, or ii) under the first physiologic condition based on the monitored peripheral blood flow under the second physiologic condition is generated. An indication of the dimensionless relative index is output.

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 image processing, in particular to a method for determining hemodynamic force for cerebral angiography x-ray examination, which comprises the following steps: acquiring the normal degree of each pixel point in a cerebral angiography image according to the difference between each pixel point in the cerebral angiography image and the corresponding pixel point in the adjacent cerebral angiography image; according to the pixel points around the pixel points, combining the normal degrees of the pixel points and the surrounding pixel points, and obtaining the edge features of the pixel points; further dividing each cerebral angiography image into a plurality of sub-images; and obtaining the possibility that each pixel point in the sub-image is a cerebrovascular edge pixel point according to the edge feature and the gradient value of each pixel point in the sub-image, and endowing each pixel point with a smoothing parameter for denoising. According to the method, by analyzing the relation between the pixel points, the filtering weight between the pixel points is distributed, loss of detail features is reduced, and therefore the accuracy of hemodynamic examination is improved.

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 discloses a method, a device, equipment, a medium and a product for determining hemodynamic indexes of a blood circulation system under the action of an acceleration field, and relates to the technical field of hemodynamics, the method comprises the following steps: constructing a one-dimensional topological model and a 0-dimensional connection model of main artery and vein blood vessel networks, and assigning parameters to obtain a 0-1-dimensional coupling basic model; iteratively solving by combining the simplified model of the basic model, the objective function and the physiological measured data to obtain individualized model parameters of the subject, and assigning the individualized model parameters to the basic model; extracting geometric topology information of the blood vessel network of the concerned part based on iconography information and assigning the geometric topology information to a corresponding position of the 0-1-dimensional model; the acceleration equivalent to the real environment is applied, the individualized 0-1-dimensional model control equation of the subject is solved, the hemodynamic indexes of the blood circulation system under the action of the acceleration field are obtained, and the hemodynamic changes of the arteriovenous system and the blood supply conditions of all important organs of the subject under the action of the acceleration can be accurately and quantitatively evaluated.

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.

Systems and methods for measuring hemodynamic parameters with wearable cardiovascular sensing. An apparatus can include one or more sensors configured to measure an electrocardiogram signal of a user and one or more seismocardiogram (SCG) signals of the user, a memory and a processing system including one or more processors operatively coupled to the memory and the one or more sensors, and configured to receive the electrocardiogram and one or more SCG signals, and generate an assessment of heart health by determining one or more hemodynamic parameters based on the signals. The invention further includes a method for non-invasively monitoring heart health of a user including receiving an electrocardiogram signal from a first sensor of a wearable device, receiving one or more SCG signals from a second sensor of the wearable device, and generating the assessment of the heart health of the user by determining the one or more hemodynamic parameters.

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.

A method is disclosed for monitoring arterial pressure of a patient and identifying nociception of the patient. The method includes receiving, by a hemodynamic monitor, sensed hemodynamic data representative of an arterial pressure waveform of the patient. Waveform analysis is performed by the hemodynamic monitor of the sensed hemodynamic data to calculate a first signal measure and a second signal measure. Both the first and second signal measures are processed by the hemodynamic monitor through a cumulative sum (CUSUM) algorithm to acquire a first CUSUM output for the first signal measure and a second CUSUM output for the second signal measure. A nociception event of the patient is detected when a change in the first CUSUM output overlaps in time with a change in the second CUSUM output. A sensory signal is outputted to a user interface of the hemodynamic monitor to warn medical personnel of the nociception event.