2345 results about "Blood flow" patented technology

A system for monitoring hemodynamic status of a patient can include a transducer, an adapter and one or more monitor devices. The adapter may be in communication with the transducer and the one or more monitor devices. The adapter can be configured to receive and process data from the transducer such as unprocessed physiological data. The adapter can be configured to transmit data to the monitor device(s) such as processed and / or unprocessed physiological data. The adapter can be configured to generate, and transmit to the monitor devices(s), user interface data for rendering interactive graphical user interfaces to display information such as physiological information relating to a hemodynamic status of the patient. The adapter can be configured to receive and process, from the monitor device(s) user commands or instructions to control an operation of the system or its components.

Set forth are vascular valves and servovalves and methods of using the same that may be positioned in the circulatory system without interrupting blood flow to facilitate solid organ transplantation so as to reduce graft organ anoxia and degradation before and after harvesting and storage, thereby minimizing late-term cardiac allograft vasculopathy as a major cause of graft failure. Along the urinary tract, bypassing bladder-generated urge sensation by diverting urine directly from the ureters to a neobladder or collection bag alleviates intractable incontinence, nocturia, urethral syndrome, overactive bladder, dysuria, or frequency. Where the lower tract is missing, a prosthesis can thwart disease and preclude the degenerative metaplastic transition to carcinoma risked when gut is used to construct a conduit for urine, a neobladder, and / or high-maintenance stoma. Druglines to valves and servovalves can directly pipeline-target medication to nidi, anastomoses, or any other trouble spots.

A medical device with an implantable blood pump and a control and sensing unit configured to determine the flow rate generated by the blood pump when driven by an electric motor, wherein the flow rate is determined using peak-to-peak current data generated by the electric motor and, in some cases, associated heart rate data. In some embodiments, the validity of pulsatility of the resulting blood flow is determined and, if out of predetermined limits, an alarm may be actuated.

The invention provides an acute cerebral apoplexy early-stage intelligent screening and early warning method and system based on deep learning, and relates to the technical field of medical imaging and artificial intelligence, and the method comprises the steps: obtaining a multi-temporal angiography image of the brain of a patient through a pulse-type dynamic imaging scheme, extracting hemodynamic features through a double-flow feature extraction network, and obtaining a multi-temporal angiography image of the brain of the patient; and constructing a vasculopathy risk distribution diagram by combining a vascular structure analysis model, and marking a potential embolism risk area. Furthermore, in combination with tissue perfusion parameters obtained by multispectral imaging and brain tissue function parameters obtained by electroencephalogram signals, an ischemic penumbra region is identified by using a self-adaptive threshold segmentation model. And finally, based on the ischemic penumbra area, the tissue perfusion parameters and the brain tissue function parameters, calculating a risk level by using a hierarchical decision model with a space-time attention mechanism, and generating a corresponding clinical intervention scheme. According to the invention, the early accurate screening and risk early warning of acute cerebral apoplexy can be realized, and the clinical intervention efficiency is improved.

The invention relates to a line device (105) for conducting a blood flow for a heart support system. The heart support system has a head unit and an outlet unit. The line device (105) has a main part (205). The main part (205) has, at a first end, a first attachment section (210) for attaching the line device (105) to the head unit and, at a second end, a second attachment section (215) for attaching the line device (105) to the outlet unit. Furthermore, the main part (205) has a mesh section (220) between the attachment sections (210, 215), wherein the mesh section (220) has a mesh structure (230) formed from at least one mesh wire (225). In addition, the main part (205) has an inlet section (235), arranged in the first attachment section (210), for introducing the blood flow into the main part (205).

A blood pump comprises a pump section and a flow cannula. A proximal end portion of the flow cannula is connected to the pump section such that blood can enter the blood flow inlet, and a distal end portion of the flow cannula includes at least one blood flow-through opening for blood to enter the flow cannula. The distal end portion comprises an enlarged diameter portion, with at least a major portion of the blood flow-through opening being disposed in the enlarged diameter portion. The blood pump further comprises a sleeve overlapping the enlarged diameter portion. The sleeve has a structure that prevents its distal end from bending radially inwards into the blood flow-through openings.

The invention discloses a liver disease image recognition processing method based on multi-modal fusion, a medium and equipment. The method comprises the following steps: acquiring multi-modal medical data in a liver disease diagnosis process; performing cross-modal feature extraction on the multi-modal medical data to obtain blood flow-image associated features; constructing a physiologically constrained space-time alignment model according to the blood flow-image correlation features, and outputting a synchronous mapping relationship between the blood vessel geometric topology network and the blood flow dynamic parameters; inputting the synchronous mapping relation into a liver disease grading classifier to generate a liver disease grading prediction result; and according to a prediction result, generating output content of multi-modal data visualization and displaying the output content. According to the method, effective fusion and collaborative analysis of multi-modal medical data are realized, and the accuracy and clinical practicability of liver disease grading are further improved.

Systems and methods are disclosed for diagnosis, risk assessment, and / or virtual treatment assessment of visceral ischemia and related disorders. One method includes receiving a patient-specific anatomic model of a patient's visceral vasculature, including visceral vasculature of the patient's visceral organs and bowel; determining a location in the patient-specific anatomic model of the patient's visceral vasculature; determining, for the location in the patient-specific anatomic model, a blood flow characteristic of blood flow through the location in the patient-specific anatomic model of the patient's visceral vasculature; determining a tissue region of the patient's bowel proximate the location in the patient-specific anatomic model of the patient's visceral vasculature; and generating an assessment of blood supply adequacy to the tissue region of the patient's bowel or generating a risk score for risk of disease for the patient's bowel, based on the determined blood flow characteristic and an expected blood flow characteristic associated with the tissue region of the patient's bowel.

Systems and methods are disclosed for diagnosis, risk assessment, and / or virtual treatment assessment of visceral ischemia and related disorders. One method includes receiving a patient-specific anatomic model of a patient's visceral vasculature, including visceral vasculature of the patient's visceral organs and bowel; determining a location in the patient-specific anatomic model of the patient's visceral vasculature; determining, for the location in the patient-specific anatomic model, a blood flow characteristic of blood flow through the location in the patient-specific anatomic model of the patient's visceral vasculature; determining a tissue region of the patient's bowel proximate the location in the patient-specific anatomic model of the patient's visceral vasculature; and generating an assessment of blood supply adequacy to the tissue region of the patient's bowel based on the determined blood flow characteristic and an expected blood flow characteristic associated with the tissue region of the patient's bowel.

The present disclosure pertains to head-mounted dual-sided photoplethysmography (PPG) systems and methods for blood flow measurement. In one embodiment, a system comprises a frame designed to be worn on a user's head, integrating a first PPG device positioned on the first side of the user's nose and a second PPG device on the opposite side. Each PPG device includes a light source and photodetector, enabling the capture of optical signals indicative of blood flow within the nasal tissue. A computer is operatively connected to both PPG devices, responsible for obtaining first and second signals from each side and processing these signals to calculate comprehensive measurements of the user's blood flow. This dual-sided configuration enhances measurement accuracy and reliability by mitigating motion artifacts and improving signal quality compared to traditional single-sided PPG systems.

Systems and methods are disclosed for simulation of occluded arteries and / or optimization of occlusion-based treatments. One method includes obtaining a patient-specific anatomic model of a patient's vasculature; obtaining an initial computational model of blood flow through the patient's vasculature based on the patient-specific anatomic model; obtaining a post-treatment computational model by modifying portions of the initial computational model based on an occlusion-based treatment; generating a pre-treatment blood flow characteristic using the initial computational model or computing a post-treatment blood flow using the post-treatment computational model; and outputting a representation of the pre-treatment blood flow characteristic or the post-treatment blood flow characteristic.

A blood pump for supporting a patient's heart includes a flow cannula having a distal portion including a distal end and a proximal portion including a proximal end opposite the distal end, the distal end of the flow cannula configured to be connected to the patient's heart or a blood vessel to establish fluid communication between the blood pump and the patient's heart and blood vessel, respectively. The flow cannula further includes an intermediate portion attached to the distal portion and the proximal portion, wherein the intermediate portion allows twisting thereof with a lower force than the distal portion and the proximal portion. The intermediate portion can be fully occluded by twisting it. At least a portion of the intermediate portion either alone or in combination with the distal portion is adapted to be permanently attached to the patient's heart or a blood vessel.

The invention relates to the technical field of blood pressure measurement, in particular to a cuff-free blood pressure continuous monitoring method based on ICG, PPG and ECG multi-mode physiological signals. According to the method, deep mining and fusion are carried out based on multi-modal physiological signals such as a chest impedance signal ICG, a photoelectric volume pulse wave signal PPG and an electrocardiosignal ECG of a tested object synchronously collected by multi-modal hemodynamics monitoring equipment, and a richer multi-modal feature matrix related to blood pressure changes is constructed; after deep learning fusion training is carried out on the constructed cuff-free blood pressure prediction model, prediction output of a cuff-free blood pressure prediction result can be directly carried out according to ICG, PPG and ECG multi-mode physiological signals of a to-be-detected tested object by means of the cuff-free blood pressure prediction model, the generalization ability and monitoring precision of continuous monitoring of the cuff-free blood pressure can be effectively improved, and the accuracy of continuous monitoring of the cuff-free blood pressure can be improved. The continuous, non-invasive and high-precision blood pressure monitoring requirements are met, and the clinical application value is more remarkable.

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 are disclosed for assessing the effect of musculoskeletal activities on disease and / or clinical events, the method comprising: receiving a patient-specific vascular and musculoskeletal model of a patient's anatomy, including at least one vessel of the patient; receiving at least one characteristic of the patient's musculoskeletal activity; generating or updating a computational anatomic vascular and musculoskeletal model of the patient's anatomy based on the received at least one characteristic of musculoskeletal activity; performing at least one of a computational fluid dynamics analysis or a structural mechanics simulation on the computational anatomic vascular and musculoskeletal model; and estimating at least one of the patient's risk of disease or clinical events based on the performed computational fluid dynamics analysis and / or structural mechanics simulation. Systems and computer readable media for executing these methods are also disclosed.

The invention discloses a diabetic foot assessment method based on wound image recognition. The method comprises the following steps: processing a foot infrared thermal imaging image to generate a temperature anomaly graph; fusing the foot wound image and the temperature anomaly graph to generate a fused image; constructing a foot blood flow analysis model, extracting a blood flow influence factor, and correcting the fused image through the blood flow influence factor; and constructing a joint assessment model, taking the corrected fusion image and historical data of the diabetic foot patient as input of the joint assessment model, predicting a risk assessment level of the diabetic foot, and outputting a disease assessment result of the diabetic foot patient according to the risk assessment level. According to the method, multi-modal medical image fusion analysis is realized, the accuracy of wound area positioning and pathological state expression is improved, the accuracy of lesion area recognition is improved, the illness worsening risk can be predicted in advance, clinical decision can be assisted, the risk of serious complications such as amputation of a patient is reduced, and the prognosis and life quality of the patient are improved.

The invention discloses a thyroid intraoperative real-time navigation method and a thyroid intraoperative real-time navigation system based on multi-mode optical fusion. The thyroid intraoperative real-time navigation method comprises the following steps: outputting visible light through an endoscope and coupling light waves of a narrow-band multispectral light source to irradiate an operative field, exciting parathyroid glands to generate near-infrared fluorescence, and receiving reflected visible light, split light, near-infrared fluorescence and laser speckle signals through an endoscope probe. And separating the composite optical signal into four channels, and respectively generating an anatomical structure color image, a blood vessel spectroscopic image, a parathyroid gland near-infrared fluorescence image and a laser speckle image. Performing decorrelation processing on the laser speckle image to generate a blood flow dynamic pseudo-color decorrelation speckle image; an anatomical structure, a blood vessel center line, a parathyroid gland contour and blood flow dynamic feature points are extracted through a multi-modal registration technology, after affine transformation space alignment is conducted, a comprehensive imaging map containing the anatomical structure, blood vessel distribution and parathyroid gland function marking information is generated through a wavelet fusion algorithm, and intraoperative multi-dimensional real-time tissue navigation is achieved.

A method and apparatus for vascular assessment are disclosed. The apparatus, in some embodiments, receives, from a medical imaging device, a medical image of a coronary vessel tree of a subject and calculates a plurality of geometric measurements associated with individual portions of a vascular segment of the coronary vessel tree. The apparatus also determines a plurality of resistances associated with the plurality of geometric measurements associated with the individual portions of the vascular segment and determines a plurality of pressure drops across the individual portions of the vascular segment based on the determined resistances and a calculated or estimated blood flow. The apparatus further calculates based on the plurality of pressure drops, a functional index indicative of a presence or an absence of a stenosis within the vascular segment.

The invention relates to the field of medical image analysis, in particular to a deep learning prediction system and method based on multi-modal thyroid cancer lymph node metastasis, and the system comprises a data collection module, a preprocessing module, a nodule segmentation module, a feature extraction module, a feature fusion module, a metastasis prediction module, an interpretability analysis module and a result display module. An ultrasonic image, an elastic imaging image, an ultra-micro blood flow image and clinical index data of a patient are integrated, an improved U-Net algorithm is used for precise segmentation of a thyroid nodule region, a multi-branch deep network is used for extracting multi-modal features, a dynamic weight fusion algorithm is used for integrating the features, and the accuracy of the thyroid nodule region is improved. According to the method, the thyroid cancer lymph node metastasis state (non-metastasis, central region metastasis or lateral neck metastasis) is predicted, meanwhile, a two-dimensional interpretability framework of Grad-CAM activation diagram and SHAP value contribution degree analysis is introduced, an intuitive prediction basis is provided for doctors, and the thyroid cancer lymph node metastasis prediction accuracy is remarkably improved.

The invention belongs to the technical field of medical informatization, and provides an anesthesia medication management system with biological recognition, comprising: a biological recognition module verifies the identities of medical staff and patients through a vein recognition technology; the multi-source data acquisition module acquires vital sign data and equipment parameters of a patient in real time to obtain multi-source data; the intelligent drug management module authorizes to store and take drugs according to the biological recognition result and generates an electronic anesthesia prescription; the processing decision module receives the multi-source data and generates a medicine adjusting instruction through a preset rule and an algorithm in combination with an electronic anesthesia prescription; the execution control module carries out secondary confirmation on the medicine adjusting instruction through biological recognition and then sends the medicine adjusting instruction to anesthetic infusion equipment to be executed; according to the method, through the electroencephalogram double-frequency index, the entropy index and the hemodynamic parameters, in combination with the anesthesia depth evaluation result and the personalized drug metabolism and effect model, the medication scheme is dynamically adjusted, the optimal infusion rate is generated, the anesthesia depth control is more accurate, and the fluctuation range is narrowed.

The invention relates to a multi-parameter integration and AI fusion postpartum hemorrhage intelligent monitoring, prevention and control method and system. The method comprises the following steps: acquiring blood flow data; the blood flow data comprises blood loss volume and blood flow velocity, and the blood flow data is obtained through measurement of an optical fiber sensor; acquiring vital sign information; the vital sign information comprises blood pressure, heart rate and oxyhemoglobin saturation, and the vital sign information is obtained through continuous monitoring of a vital sign patch; according to the blood flow data, the vital sign information and the medical history information, a bleeding risk grade evaluation result is calculated in real time through an AI risk evaluation model, and the AI risk evaluation model is used for dynamically evaluating the bleeding risk; and triggering corresponding grading early warning according to the bleeding risk grade evaluation result, wherein the grading early warning is used for indicating bleeding risk processing. By adopting the method, the early warning accuracy and treatment efficiency of postpartum hemorrhage can be remarkably improved, and complications and death risks of pregnant and lying-in women are effectively reduced.

The invention relates to the technical field of medical care informatics, and discloses an intelligent post-stroke cognitive impairment assessment method based on brain network dynamic reconstruction, which comprises the following steps: acquiring multi-modal brain image data of a patient, dynamically compensating the difference between haemodynamic delay and white matter conduction velocity through a nerve-blood vessel coupling model, and calculating the post-stroke cognitive impairment; precise space-time alignment of function and structure signals is realized; a pulse neural network dynamic entropy change model is constructed based on the alignment data, functional connection strength change is coded into a pulse distribution sequence, and Gamma wave band synchronization enhancement and other compensatory features are extracted; constraining rationality of brain network reconstruction by adopting an energy optimal transmission model, and generating a compensatory thermodynamic diagram; and real-time calculation of the edge end is realized through pulse time sequence compression coding. The limitation of traditional static analysis is avoided, the algorithm achieves microsecond response on embedded equipment through the pulse coding technology, and a reliable stroke rehabilitation evaluation tool is provided for primary hospitals.

A method and apparatus for calculating the blood flow rate in a coronary artery, an electronic device and a storage medium. The method for calculating the blood flow rate in a coronary artery comprises the following steps: S1, acquiring an angiography image of the coronary artery, segmenting the angiography image of the coronary artery by using deep learning, and obtaining segmented images of a main vessel (S1); S2, calculating the length of the main vessel in each segmented image frame on the basis of the segmented images of the main vessel (S2); and S3, obtaining the blood flow rate in the main vessel on the basis of the calculated change of the lengths of the main vessel with time (S3). By using the method and apparatus for calculating the blood flow rate in a coronary artery and the electronic device, the automation of the calculation of the blood flow rate in a coronary artery is achieved, the calculated blood flow rate in the coronary artery is more accurate, and the calculation method is simple.

Provided herein are dry powder formulations comprising epinephrine alone or in combination with at least one enabling agent suitable for nasal application. Also provided are unit dose forms and devices comprising such formulations and methods of using such formulations for the treatment of various conditions including anaphylaxis, anaphylactoid reaction, respiratory conditions, hemodynamic collapse, and for administration during cardiopulmonary arrest and other life-threatening conditions.

The invention provides a first-aid tourniquet pressure monitoring and automatic alarm system, and relates to the technical field of pressure monitoring. The system comprises a biological reaction monitoring module, a pressure adjustment analysis module, a real-time pressure adjustment module, a safety threshold detection module and an emergency response activation module. According to the invention, through real-time monitoring of biological reactions, changes of micro blood flow, skin electrical impedance and tissue morphology of a patient after the patient uses the tourniquet are captured, so that monitoring of individual reactions is more comprehensive, the safety and effect of pressure are evaluated in combination with the actual physiological state of the patient, monitoring is more dynamic and personalized, and the monitoring accuracy is improved. Through the combination of pressure real-time adjustment and emergency response, it is ensured that when the pressure exceeds a safety range, pressure adjustment is conducted rapidly, warning is given out through an alarm, secondary injury caused by improper pressure is avoided, the use safety and response speed of the tourniquet are improved, tissue injury of a patient can be more accurately prevented, and the patient can be more accurately protected. And the real-time effectiveness and safety in the emergency treatment process are ensured.

This disclosure relates to systems, methods, and devices for plaque analysis, vessel and fluid flow analysis, and / or risk determination or prediction thereof. Some embodiments relate to determining fractional flow reserve (FFR) values. Some embodiments relate to determining FFR values using 3D-printed models. Some embodiments relate to identifying thin cap fibroatheroma based on analysis of computed tomography (CT) imaging. Some embodiments relate adjusting calcified plaque thresholds for CT images to address effects of calcium blooming.

The present disclosure relates to balloon assemblies designed to permit blood flow through a central perfusion channel, at least when blood flows in a proximally-oriented direction. Such a balloon assembly can include one or more toroid balloons, each defining a cavity that can be independently fed by one or more inflation tubes coupled thereto to inflate the balloon. When the toroid balloons are inflated within a patient lumen or a prosthetic device, such as a prosthetic heart valve, blood is allowed to flow through the perfusion lumen. A balloon assembly can further include a flexible valve configured to regulate blood flow when the balloon assembly is inflated, to allow proximally directed flow through a channel formed in a flexible funnel thereof, and prevent backflow in the opposite direction.

The invention discloses a temperature self-adaptive control system for organ perfusion, and belongs to the technical field of temperature control, and the system comprises a sampling unit which is used for converting analog signals of temperature, flow velocity and pressure of one or more target nodes in perfusion blood circulation into digital signals to form an initial data set; the calculation unit is used for performing wavelet transformation and moving average processing on the initial data set to construct a feature matrix, and establishing a temperature change prediction model based on the feature matrix so as to determine a temperature compensation amount in combination with dynamic correction; and the temperature control unit is used for adjusting the temperature control power by adopting a progressive strategy based on the temperature compensation amount and synchronously adjusting the blood flow rate so as to dynamically optimize the control parameters according to the temperature control effect. Through the scheme of the invention, the real-time regulation and control precision can be improved, and the quick response capability to temperature mutation is enhanced.

The invention relates to the technical field of medical care, and provides a patient risk dynamic assessment system in medical care teaching, which comprises a data acquisition module used for acquiring multi-modal image data of a postoperative gastric organ anastomosis area of a patient; the data processing module is used for preprocessing the multi-modal image data, establishing a three-dimensional model of organs around the anastomotic stoma and analyzing edge features of the anastomotic stoma; and the risk assessment module is used for constructing an anastomotic stoma state assessment model and outputting comprehensive scores of an anastomotic stoma blood perfusion condition, a tissue metabolism abnormal probability, an anastomotic stoma leakage risk, anastomotic stoma scar hyperplasia and healing trend prediction. A quantum dot fluorescence image, a Raman spectrum image, a CT image and an intraoperative high-definition white light image are enhanced through the system and evaluated, a nursing scheme is obtained in combination with opinions of medical staff, and compared with manual evaluation of the medical staff, the accuracy is higher, the feasibility of the nursing scheme is higher, and medical nursing use is facilitated.

The invention discloses a brain health monitoring and cerebral infarction early warning method and system for old people. The method comprises the steps that electroencephalogram, electrocardio, blood oxygen and cerebral blood flow velocity multi-mode physiological signal data are collected; adopting a characteristic mode decomposition method to decompose the multi-mode physiological signal data; the method comprises the following steps: introducing a KAN network into an MATE structure, carrying out nonlinear mapping and feature reconstruction, and constructing a KAMATE model; an improved Bayesian optimization algorithm is obtained based on the Bayesian optimization algorithm in combination with a dynamic balance strategy; the improved Bayesian optimization algorithm is combined with the characteristic mode decomposition method to achieve characteristic decomposition of the multi-mode physiological signals, and parameters of the KAMATE model are optimized; dividing the brain health state into four grades according to a prediction result output by the KAMATE model; according to the invention, real-time early warning of abnormal cerebral blood supply, cognitive decline and cerebral infarction high-risk states of the elderly can be realized, intelligent support is provided for health management of the elderly, and the method has important application value.