7563 results about "Cardiology" patented technology

An auto-occlusion safety device is provided for use in preventing rupture of infusion components during rapid infusion procedures. An occlusion valve is disclosed having a threshold pressure that is less than a rupture tolerance of the infusion system components. As the fluid pressure of the infusion system increases beyond the threshold pressure of the occlusion valve, the occlusion valve is automatically activated thereby occluding fluid flow upstream from a vulnerable infusion component. An accumulator is further disclosed for use in combination with the safety device to compensate for time delays in full activation of the occlusion valve.

The present disclosure relates to a method for detecting a state of wear of a cardiac support system. The method comprises a read-in step and a determination step. During the read-in step, a sensor signal representing an operating state of the cardiac support system is read in. During the determination step, a wear signal is determined using the sensor signal and a comparison rule. The wear signal represents the wear condition.

Methods and apparatus for determining a position of an intracardiac blood pump in a patient are described. The method includes receiving from at least one capacitive sensor associated with a cannula of the intracardiac blood pump, at least one capacitive signal, determining a position of the intracardiac blood pump in the patient based, at least in part, on the at least one capacitive signal, and providing an indication of the position of the intracardiac blood pump on a user interface of the circulatory support device.

A noninvasive blood pressure monitor. The noninvasive blood pressure monitor may include an inflatable cuff, a pressure transducer, one or more air pumps, and a processor. The processor may control the air pump(s) so as to initiate inflation of the cuff. The processor may also identify an oscillometric signal in an output of the pressure transducer, and may determine an envelope of the oscillometric signal. The processor may also determine one or more characteristics of the envelope of the oscillometric signal, and may control the air pump(s) so as to stop inflation of the cuff based on the one or more characteristics of the envelope of the oscillometric signal.

The present disclosure provides an intelligent decision reasoning method for type-based diagnosis and treatment of a cardiovascular disease, a device, and a product, and relates to the medical field. The present disclosure adopts a risk factor mining model of a cardiovascular disease and a drug attribute association mining model of the cardiovascular disease to extract relevant information from cardiovascular data, achieving precise prediction of a fine-grained cardiovascular disease type and effectively promoting precision medicine. Based on a clinical diagnostic dataset and a clinical symptom diagnosis knowledge system of the cardiovascular disease, a type-based auxiliary diagnosis model of the cardiovascular disease is constructed, and intelligent decision reasoning is performed to obtain an association rule. This achieves efficient integration of type-based decision support of the cardiovascular disease and a medical convalescence knowledge base of the cardiovascular disease, and enhances quality of a cardiovascular medical convalescence association rule set.

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).

The invention relates to a method for determining a flow rate of a fluid flowing through an implanted vascular assist system (1), said method comprising the following steps: a) carrying out a first pulsed Doppler measurement at a first pulse repetition rate by means of an ultrasonic sensor (2) of the assist system (1); b) carrying out a second pulsed Doppler measurement at a second pulse repetition rate by means of the ultrasonic sensor (2) of the assist system (1), wherein the second pulse repetition rate differs from the first pulse repetition rate; c) determining the flow rate using measurement results of the first pulsed Doppler measurement and the second pulsed Doppler measurement.

The invention relates to the field of heart rate monitoring, and discloses a millimeter wave radar breath and heart rate synchronous monitoring method and system, and the method comprises the steps: transmitting a linear frequency modulation continuous wave signal according to a millimeter wave radar, and collecting original echo data reflected by a target region; baseband signal demodulation and phase information extraction are carried out on the original echo data to obtain original phase time sequence data, and the original phase time sequence data comprise thoracic cavity micro-motion features; and according to a Butterworth band-pass filter, preprocessing the original phase time sequence data through human body physiological signal frequency band characteristics to obtain a breathing frequency band signal and a heart rate frequency band signal. According to the method, the apnea event triggering threshold value and the arrhythmia early warning index are updated in real time through Kalman filtering and extended Kalman filtering, so that the monitoring system can dynamically adjust the health parameters, which means that the monitoring system can be optimized in real time and the abnormal health event can be accurately responded in different physiological states.

The invention relates to the technical field of image classification, in particular to a fetal heart monitoring image classification method and system based on a neural network. The method comprises the following steps: acquiring a fetal heart monitoring image, generating a standard monitoring image through Gaussian noise elimination and spatial domain normalization, then performing multi-channel convolution on the standard image to extract image convolution features, obtaining standard fetal heart features through compression regular optimization, performing morphological reconstruction to generate a fetal heart dynamic model, and finally obtaining the fetal heart dynamic model. Baseline features are identified based on historical data, then periodic variation quantification and safe floating range derivation are performed on fusion features, and finally a multi-scale discrimination framework is constructed to realize intelligent classification of fetal heart monitoring images. The fetal heart monitoring image classification method is more stable and more accurate.

The invention provides a heart multi-mode digital twinning simulation method and system, electronic equipment and a medium, and belongs to the technical field of digital twinning. The method comprises the following steps: S1, collecting multi-modal data of a heart; s2, preprocessing the acquired multi-modal data to obtain heart digital data; s3, based on the heart digital data, constructing a multi-modal digital twinborn model of the heart and optimizing the multi-modal digital twinborn model; s4, performing real-time simulation on the electrophysiological activity of the heart by using the optimized multi-modal digital twin model and using a Runge-Kutta method in combination with a PSO (Particle Swarm Optimization) algorithm; s5, based on the optimized multi-mode digital twinborn model and the simulation result, simulation and planning of virtual cardiac surgical treatment are carried out; and S6, dynamically evaluating the multi-modal digital twin model, and monitoring the state change of the heart in real time. According to the heart multi-mode digital twinborn simulation method and system, the electronic equipment and the medium, efficient simulation and real-time monitoring of the heart state can be achieved.

The invention relates to a method for operating an implanted, ventricular assist system (2), comprising the following steps: a) determine a first impedance parameter at a first point in time by means of the assist system (2), b) determine a second impedance parameter at a second point in time by means of the assist system (2), c) at least determine a change of the impedance parameter using the first impedance parameter and the second impedance parameter, or compare at least the first or second impedance parameter to a threshold value.

An intravascular heart pump assembly can include a rotor with at least one impeller blade, and a cannula. The present application describes various cannulas that can be manufactured from multiple layers of material to improve flexibility, manufacturability, and durability without increasing an outer diameter of the cannula. In one embodiment, the cannula includes an inflow section having a sheet formed of a shape memory material embedded within a polymer and having at least one lateral hole or aperture in the inflow section. The at least one lateral hole is defined by a first hole in the sheet and a second hole in the outer polymer layer of the cannula. The first hole and the second hole overlap so that blood can enter the cannula through the holes.

The invention concerns a control device for controlling a blood flow of an intravascular blood pump for percutaneous insertion into a patient's blood vessel, the blood pump comprising a pump unit with a drive unit for driving the pump unit and configured to convey blood from a blood flow inlet towards a blood flow outlet, wherein the control device is configured to operate the blood pump in a selectable zero-flow control mode, wherein a blood flow command signal is selected, and the control device comprises a first controller and a second controller, wherein the first controller is configured to control the blood flow by adjusting a speed command signal for the drive unit, and the second controller is configured to control a drive speed of the drive unit.

A transport container and methods for preserving a heart at a hypothermic temperature. The transport container can maintain the heart at a temperature of 6-8° C. for improved results after transplantation. The preservation of the heart within this range can improve transplantation outcomes.

Systems and methods for determining the positioning of intracardiac devices, such as intracardiac blood pump assemblies, using electrical sensors configured to sense electrical potential as it propagates through the heart. In one example, the present technology provides an intracardiac device with one or more electrical sensors mounted thereon, and a controller configured to determine the absolute or relative location of the intracardiac device based on the timing, shape, and / or amplitude of the electrical signals received from the one or more sensors.

An intravascular blood pump for percutaneous insertion into a patient's blood vessel is provided. The blood pump comprises a pump casing and an impeller arranged in the pump casing. The blood pump further comprises a drive unit for rotating the impeller, the drive unit comprising a plurality of posts. Each of the posts has an impeller-side end pointing towards the impeller with a front surface facing the impeller. A coil winding is disposed around each of the posts so as to create magnetic field lines running through the front surface of each of the posts. The front surface of at least one of the posts comprises a concavity in which the front surface is inclined downwards towards a central area of the front surface so as to concentrate at least a part of the magnetic field lines running through the front surface.

The invention relates to a heart rate prediction and model training method and system, wearable equipment and a medium. The training method comprises the following steps: acquiring a training sample set and a corresponding label set; wherein each training sample of the training sample set comprises a photoelectric volume pulse wave sequence and a corresponding acceleration sequence, and the label set is a real heart rate; preprocessing each training sample to obtain a corresponding photoelectric volume pulse wave frequency spectrum sequence and an acceleration frequency spectrum sequence; all the photoelectric volume pulse wave frequency spectrum sequences and the acceleration frequency spectrum sequences are input into a heart rate prediction model to be trained, and corresponding predicted heart rates are obtained; and calculating the difference degree between the predicted heart rate and the corresponding real heart rate, and updating parameters of the heart rate prediction model based on the difference degree to obtain a trained heart rate prediction model. According to the method, the problems of high signal processing cost and high calculation complexity caused by the use of a complex adaptive filtering process in the prior art are solved, and the heart rate prediction accuracy can be remarkably improved.

The invention relates to the technical field of medical information, in particular to an intelligent prediction model and method for postoperative complications of anesthetized patients, and the method comprises the steps: collecting preoperative to postoperative complete-cycle clinical data of a patient through a medical data interface; analyzing operation codes to generate risk features, extracting vital sign dynamic features, and establishing a complication probability mapping relation through a multi-modal fusion network; combining the complication probability and pharmacokinetic parameters to construct an optimization model, and solving an individualized anesthetic dosage interval by using a gradient descent algorithm; vital signs are dynamically monitored in the operation, a dose re-optimization mechanism is triggered, the infusion rate is adjusted, and a closed-loop control link is formed; and generating a visual decision report. According to the method, through deep integration of complete-cycle clinical data and multi-modal feature modeling, preoperative physiological parameters, operation coding semantic information and intraoperative vital sign dynamic modes are subjected to fusion analysis, a nonlinear mapping relation between dosage and complication probability is constructed, and the risk prediction precision and individualized adaptability are remarkably improved.

A medical apparatus for a patient comprises an external system and an implantable system. The external system is configured to transmit one or more transmission signals, each transmission signal comprising at least power or data. The implantable system is configured to receive the one or more transmission signals from the external system, and to deliver stimulation energy to the patient. Methods of delivering stimulation energy are also provided.

The invention provides a reflux valve supporting remote monitoring of the Internet of Things. The reflux valve comprises a valve body provided with a fluid inlet, a fluid outlet and an internal flow channel, and an electric actuating mechanism is configured for controlling the opening degree of the valve; a microprocessor and a memory are arranged in the control unit, and the control unit processes data of the sensor, calculates a fluid density correction coefficient and a pressure correction coefficient, corrects original flow data collected by the flow sensor and generates an actual flow value; the control unit further identifies the current fluid type and adaptively adjusts the countercurrent detection threshold value of the upstream and downstream pressure difference based on the relationship between the flow and the pressure data; when the pressure difference exceeds the adjusted threshold value, the electric executing mechanism executes emergency turn-off operation; meanwhile, a wireless communication unit is arranged, real-time data transmission is supported, control parameters issued by external monitoring equipment are received, and intelligent control and remote management are achieved; the intelligence and the operation efficiency of the reflux valve can be effectively improved, and the reflux valve is suitable for safety protection and operation optimization under the complex fluid working condition.

The invention provides an intelligent anesthesia depth monitoring method and system. A plurality of physiological parameter sensors are used for synchronously collecting composite physiological signals of a patient, and meanwhile brain wave signals of the patient in the anesthesia process are obtained; analyzing and processing the anesthesia state by fusing an electroencephalogram spectrum analysis algorithm and a nonlinear kinetic model to obtain a consciousness state map of anesthesia depth and consciousness edge fluctuation; performing real-time evaluation on the current anesthesia depth by using an adaptive threshold algorithm in combination with a Bayesian reasoning framework, and performing prediction processing on the trend change of the anesthesia depth in a future short time by using a long-short term memory neural network to obtain an evaluation result and a prediction trend; the anesthetic infusion rate is automatically adjusted so as to maintain the ideal anesthesia depth, meanwhile, potential risks are subjected to intelligent grading early warning processing, and an anesthesia management strategy is generated. According to the technical scheme provided by the invention, the safety and personalized management level of the anesthesia process are improved.

Apparatus and methods are described including a ventricular assist device that includes a frame having struts that define a plurality of cells. In its non-radially-constrained configuration, the frame includes a generally cylindrical portion. A tube defines blood outlet openings, and a portion of the tube is disposed outside the frame and is coupled to the generally cylindrical portion of the frame, such that the portion of the tube conforms with a structure of struts of the frame. An inner lining is coupled to an inside of the generally cylindrical portion of the frame, such as to provide the generally cylindrical portion of the frame with a smooth inner surface. An impeller is disposed at least partially inside the generally cylindrical portion of the frame and is configured to pump blood through the tube and out of the one of more blood outlet openings. Other applications are also described.

The invention relates to the technical field of medical instrument control, in particular to a lung biopsy sampling needle stabilizing method and system based on dynamic respiration compensation. The stabilizing method comprises the following steps: acquiring a respiratory movement signal of a patient in real time through a multi-source biosensor, wherein the multi-source biosensor comprises an optical fiber strain sensor array, a diaphragm myoelectricity sensor and a respiratory airflow sensor which are deployed at the chest and abdomen. According to the method, millimeter-microsecond-level accurate and stable control over the lung biopsy sampling process is achieved by establishing a cooperation mechanism of a breathing phase-displacement nonlinear mapping model and a macro-micro composite driving framework. The biological rationality of displacement prediction is improved through deep coupling of multi-mode breathing signals, and the chest wall non-uniform deformation gradient is analyzed in space based on cross topology deployment of an optical fiber strain sensor in an intercostal space area in combination with cross-scale feature fusion of myoelectricity and airflow sensing.

The invention relates to a bearing device (100) for a cardiac support system. The bearing device (100) comprises a stand unit (105) and an impeller (110). The stand unit (105) is designed to support the impeller (110) such that it can rotate. The impeller (110) is designed to rotate during an operation of the cardiac support system in order to convey a pump fluid flow (115). The impeller (110) is designed to enclose at least one subsection (120) of the stand unit (105) in the assembled state of the bearing device (100), wherein an intermediate space (125) for guiding a flushing fluid flow (130) is provided between the subsection (120) and the impeller (110). At least one flushing outlet (135) is formed in the impeller (110). The flushing outlet (135) is designed to discharge the flushing fluid flow (130) from the intermediate space (125) by means of centrifugal force when the cardiac support system is in operation.

Systems and methods are disclosed for creating an interactive tool for determining and displaying a functional relationship between a vascular network and an associated perfused tissue. One method includes receiving a patient-specific vascular model of a patient's anatomy, including at least one vessel of the patient; receiving a patient-specific tissue model, including a tissue region associated with the at least one vessel of the patient; receiving a selected area of the vascular model or a selected area of the tissue model; and generating a display of a region of the tissue model corresponding to the selected area of the vascular model or a display of a portion of the vascular model corresponding to the selected area of the tissue model, respectively.

The present disclosure provides a method and system for analyzing unipolar electrophysiological (EP) signals acquired by a multi-electrode catheter placed in a ventricle of a patient's heart. The method includes receiving unipolar EP signals, extracting unipolar far-field signals from the unipolar EP signals, and analyzing the extracted unipolar far-field signals to estimate the distribution of scar regions across a thickness of wall tissue of the ventricle. Using the estimated distribution, a unipolar far-field EP map showing the scar regions is generated. The method further includes displaying the unipolar far-field EP map including the scar regions to a user. The system comprises a display device and a processor configured to perform the steps of the method.

Various aspects of the present disclosure are directed towards apparatuses, systems, and methods that may include a blood pump. The blood pump may include a flexible distal tip having a distal end segment, an intermediate segment, and a proximal segment, each segment having various shapes and / or hardness. The blood pump may include a cannula and a can element coupling the flexible distal tip to the cannula.

The invention relates to a blood oxygen and heart rate monitoring system and method based on PPG signals and motion data, and relates to the technical field of medical health and intelligent wearable equipment. The system comprises a PPG signal acquisition module, a motion sensor module, a signal preprocessing module, a dynamic signal segmentation and quality evaluation module, an oxyhemoglobin saturation calculation module, a heart rate calculation module, a motion state recognition module, a self-adaptive Kalman filtering module and an output display module. The method and the device have the effects of realizing a function of identifying the motion state by the wearable equipment, improving the signal interference suppression capability and widening the application scene.

The invention belongs to the technical field of medical image processing, and particularly relates to a double-encoder semi-supervised heart MRI double-ventricle segmentation method based on improved SAM. A teacher model and a student model which are used both comprise double encoders, prompt encoders and mask decoders, each double encoder comprises a ViT branch and a CNN-Mama branch which are parallel, parameter fine tuning of the ViT branch is realized through a position adapter and a feature adapter, the CNN-Mama branch mainly comprises a convolution fusion Mama block and a second-order dimension attention block, and the CNN-Mama branch is used for realizing fine tuning of parameters of the CNN-Mama block. The convolution fusion Mama block introduces an enhanced convolution block on the basis of a VSS block, and the second-order dimension attention block uses a covariance matrix to mine second-order statistical information of data; carrying out weighted summation on the output features of the ViT branch and the CNN-Mama branch to obtain the output features of the double encoders; the output features of the double-encoder and the prompt encoder are input into a mask decoder to be decoded, and a segmentation result is obtained; and performing joint training on the teacher model and the student model based on interpolation consistency regularization semi-supervision, and using the trained student model as a segmentation model for double-ventricle segmentation of heart MRI. The segmentation model has strong feature extraction capability, can effectively extract the edge information of the ventricles and the boundary information of the double-ventricle connection region, and improves the segmentation precision.

A method of automatically determining a calcium score for at least one coronary artery is disclosed. The method comprises receiving cardiac non-contrast CT data indicative of a cardiac non-contrast CT scan carried out on a patient, analysing the cardiac non-contrast CT data in a calcified components identifier to detect candidate coronary artery calcified components, and analysing cardiac non-contrast CT data associated with the candidate coronary artery calcified components using a radiomics analyser to determine radiomic characteristics of the candidate coronary artery calcified components. The method also comprises applying machine learning to the determined radiomic characteristics associated with each candidate coronary artery calcified component to identify any calcifications that are located on a coronary artery, analysing the cardiac non-contrast CT data to identify at least one body component in the cardiac non-contrast CT data not associated with a coronary artery of the patient, and using the identified at least one body component in the cardiac non-contrast CT data to remove or avoid misclassification of calcifications on a coronary artery that are located on the at least one identified body component.