540 results about "Cardiac cycle" patented technology

There are provided methods and systems for training and using machine learning (ML) models to determine suitability of a given patient for an endovascular aortic repair (EVAR) intervention and to monitor the given patient after the EVAR intervention. The pre-EVAR ML models are trained on training datasets comprising strain maps having been generated based on a multiphase image stack of the aorta of each respective patient during a cardiac cycle, measures of aortic weakness in the aorta of each respective patient, geometric features of the aorta of the respective patient, and outcomes of the EVAR intervention on the respective patient. The post-EVAR ML models are trained on pre-EVAR strain maps, post-EVAR strain maps having been generated after the EVAR intervention, and a respective outcome of the EVAR intervention.

The invention relates to the technical field of heart sound signal processing, and discloses a heart sound feature recognition method based on wavelet spectral analysis. The method comprises the following steps: collecting heart sound signal data and carrying out signal filtering and segmentation processing to obtain segmented cardiac cycle signals; performing n-level discrete wavelet transform decomposition to obtain an approximation coefficient and n detail coefficients; performing multi-dimensional statistical feature calculation to obtain a multi-dimensional feature vector; performing principal component analysis dimension reduction processing to obtain a dimension reduction feature vector; fitting feature distribution by using a Gaussian mixture model and introducing a dynamic adjustment factor to obtain an adaptive classification threshold; the hidden Markov model is constructed through the dimension reduction feature vectors, the likelihood probability is calculated through a forward algorithm, the likelihood probability is compared with a self-adaptive classification threshold value, and the heart sound feature recognition result is output. The time-frequency features of the heart sound signals are fully utilized, the feature distinction degree and the recognition accuracy are improved, and the recognition accuracy is improved. And meanwhile, the method has good robustness and generalization ability.

The invention relates to the technical field of medical and industrial cross, in particular to a method and device for generating a dynamic cardiac electrical excitation diagram, and the method comprises the steps: carrying out the phase alignment of the electrical excitation diagram and the cardiac image data of a preset mode, and obtaining time domain alignment data; on the basis of the time domain alignment data, aligning the heart models reconstructed in different modes according to the anatomical form to obtain space domain alignment data; and projecting an electrical mapping result to a corresponding anatomical structure of the heart based on the time domain alignment data and the spatial domain alignment data, and constructing a dynamic heart model of individualized electrical anatomical mapping of the target patient so as to display propagation of the electrical excitation diagram in the whole cardiac cycle on the dynamic heart model according to the conduction velocity in one cardiac cycle. According to the method, the dynamic heart model of the individualized electroanatomical mapping of the specific patient can be constructed by using the cardiac electrophysiology and anatomical structure data, the dynamic cardiac electrical excitation diagram of the human body is reconstructed, and the catheter ablation treatment of the tachycardia patient is guided by using the dynamic cardiac electrical excitation diagram.

This electronic apparatus may comprise: a video obtainment unit that obtains a first blood vessel video and a second blood vessel video obtained by recording a target blood vessel at a plurality of positions; and a processor that, for each of the first blood vessel video and the second blood vessel video, selects, from among a plurality of frame images included in a corresponding blood vessel video, a reference frame image of the corresponding blood vessel video by using a score for the analyzability of the target blood vessel shown in each frame image, and determines, on the basis of information associated with a cardiac cycle of each reference frame image, a correspondence relationship between a reference frame image of the first blood vessel video and a reference frame image of the second blood vessel video.

Method and systems are described that create a 3D reconstruction of a vessel of interest that represents a subset of a coronary tree that includes a lesion; calculate at least one of pressure parameters or anatomical parameters based at least in part on a portion of the 3D reconstruction that includes the lesion; calculate a wall shear stress (WSS) descriptor, based on the 3D reconstruction, for a segment of a surface of the vessel that includes the lesion, wherein the WSS descriptor includes information regarding an amount of variation in contraction or expansion applied at surface elements within the segment during at least a portion of a cardiac cycle; and calculate a myocardial infarction (MI) index based on the WSS descriptor and the at least one of the pressure or anatomical parameters, the MI index representing a likelihood that the lesion will result in an MI.

The invention provides a four-dimensional cardiac function imaging method and device based on a biological magnetic signal. The method comprises the following steps: acquiring a magnetocardiogram signal of a to-be-detected object and dynamic structure information of a target trunk part in a full cardiac cycle; wherein the target trunk part at least comprises double lungs, a trunk, a heart cavity of the trunk and a pericardium structure, and the dynamic structure information comprises a contour structure and a multi-frame dynamic image; performing spatial registration on the dynamic structure information and the sensor for acquiring the magnetocardiogram signal to obtain coordinates of the sensor in a coordinate system of the dynamic structure information; according to the dynamic structure information, the coordinate of the sensor and the magnetocardiogram signal, calculating and reconstructing cardiac electrical excitation activity to obtain a calculation and reconstruction result; and converting the calculation reconstruction result into a four-dimensional visual image. According to the method, heart magnetic imaging and heart movement are combined, on the basis of obtained dynamic structure information and heart magnetic signals, the characteristics of biological magnetic signals are fully utilized, and the signal processing technology is integrated through space registration, so that accurate reconstruction of four-dimensional representation of the heart and visual display of functional activities are realized; therefore, the obtained four-dimensional visual image can completely represent the dynamic electrophysiological activities of the whole heart (including epicardium, endocardium and intrawall tissues) in a cardiac cycle, and a technical scheme with different concepts is provided for non-invasive imaging of cardiac electrical excitation activities.

The invention provides a free breathing heart fat fraction and multi-relaxation parameter simultaneous quantitative magnetic resonance imaging method, a free breathing heart fat fraction and multi-relaxation parameter simultaneous quantitative magnetic resonance imaging device, a terminal and a medium. The method comprises the following steps: scanning a plurality of imaging layers on heart tissues of a detected object in a free breathing state to obtain a double-echo image of each cardiac cycle corresponding to each imaging layer and an electrocardio trigger signal; simulating an evolution process of a magnetization vector based on a Bloch equation and an electrocardio trigger signal, and establishing a dictionary; on the basis of the double-echo image after image processing, water-fat separation operation based on mixed multi-echo is executed, and a water signal image and a fat fraction graph are obtained; and obtaining a relaxation parameter group diagram of the detected object in a mode of matching the water signal image with the dictionary. Collection is carried out when the detected object freely breathes, the burden of the detected object is relieved, and the fat fraction quantification precision and the water-fat separation accuracy are guaranteed.

The invention provides a self-adaptive control method and device. The method comprises the steps that multiple pumping flows of a ventricular assist device during operation at a first rotating speed in a first period are obtained; first duration and second duration are recorded, the first duration is the duration of the interval between the adjacent first pumping flow, the second duration is the duration from the first pumping flow to the pumping flow smaller than a first flow threshold value in the first duration, and the first pumping flow is the peak value of the pumping flow of the ventricular assist device; if the first rotating speed is adjusted according to the target ratio, the target ratio is the ratio of the second duration to the first duration. The cardiac cycle of the user and the low flow value of the ventricular assist device can be determined according to the first duration and the second duration respectively, and the rotating speed of the ventricular assist device is adaptively adjusted according to the ratio of the second duration to the first duration, so that the pumping flow of the ventricular assist device can meet the requirements of the user in real time; abnormalities of the ventricular auxiliary device are reduced, and therefore the safety of a user is improved.

The invention discloses a vascular access lesion recognition method and system based on target detection, and relates to the technical field of medical image processing, and the method comprises the steps: carrying out the cardiac cycle phase division according to an electrocardiogram signal, calculating a displacement vector field between adjacent frames of a blood vessel DSA image sequence, constructing a motion compensation model, and generating a stable DSA sequence; segmenting the stable DSA sequence into binary vascular mask images through a U-Net segmentation model, tracking motion displacement of contrast agent particles in continuous frames by using a particle image velocimetry algorithm, generating a blood flow velocity vector field, and calculating an eddy current intensity feature map; and carrying out channel cascading on the binarized blood vessel mask image and the vortex intensity feature map to generate a blood vessel feature tensor, and generating a lesion detection result by improving a YOLOv7 model. According to the method, the accuracy, robustness and clinical applicability of vascular disease recognition are improved, and a technical closed loop from multi-modal data processing to automatic diagnosis report generation is realized.

A prosthetic heart valve for treatment of a diseased heart valve having native anterior and posterior leaflets that move between an open configuration and a closed position to regulate blood flow through the heart valve during a cardiac cycle of a heart. The prosthetic heart valve having a crescent shaped stent, at least one prosthetic leaflet mounted on an inner surface of the stent, and at least one prong structure coupling a portion of the at least one prosthetic leaflet to a lower ventricular portion of the stent frame. The prosthetic heart valve further having systems for anchoring the upper flared portion of the stent to a posterior portion of the native valve annulus.

The invention provides a coronary vessel deformation calculation method and device in a cardiac cycle, a medium and equipment, and the method comprises the steps: obtaining image data, selecting a frame of image as a key frame from the image data, and enabling the image data to comprise coronary vessel image data of the whole cardiac cycle; positioning a blood vessel section used for deformation analysis in the key frame as a reference analysis section; selecting a plurality of analysis frames from the image data, and positioning a blood vessel section corresponding to the reference analysis section in each analysis frame as a comparison analysis section; and carrying out contour segmentation and registration on the reference analysis section and each comparison analysis section so as to calculate deformation of each position in the blood vessel section to be analyzed. Deformation of each position in a to-be-analyzed blood vessel section is calculated, so that the problem that blood vessel deformation preprocessing is complex is solved, and the simplicity and accuracy of coronary artery diameter change detection are improved.

The invention provides a ventricular assist device control device and method, a ventricular assist system and electronic equipment, and relates to the field of medical instrument control. The control device comprises a time sequence judgment module, a characteristic flow calculation module and a motor control module. The time sequence judgment module is used for dividing the target cardiac cycle into a systolic stage and a diastolic stage; the characteristic flow calculation module is used for dividing the real-time flow of the ventricular assist device in the target cardiac cycle into systolic period flow in a systolic period stage and / or diastolic period flow in a diastolic period stage, and calculating the characteristic cardiac output of the ventricular assist device in the target cardiac cycle according to the systolic period flow and the diastolic period flow; the motor control module is used for adjusting motor rotation speed. By using the control device provided by the embodiment of the invention, the cardiac output of the ventricular auxiliary device can better conform to the physiological law of the heart, and stable control of the cardiac output is realized.

The exemplified methods and systems facilitate the quantification of cardiac cycle-variability as a metric of signal quality of an acquired signal data set and the rejection, based on that quantification, of said acquired signal data set from one or more subsequent analyses that can predict and / or estimate a metric associated with the presence, non-presence, severity, and / or localization of abnormal cardiovascular conditions or disease, including, for example, but not limited to, coronary artery disease, abnormal left ventricular end-diastolic pressure disease (LVEDP), pulmonary hypertension and subcategories thereof, heart failure (HF), among others as discussed herein. The quantification of levels of cycle-variability assessed noise such as skeletal-muscle-related-signal contamination and muscle-artifact-noise contamination, and other asynchronous-noise contamination in an acquired signal can be subsequently used for the automated rejection of such asynchronous noise from measurements of biophysical signals.

A control device (100) for controlling the rotational speed (nVAD(t)) of a non-pulsatile ventricular assist device, VAD, (50) uses an event-based within-a-beat control strategy, wherein the control device is configured to alter the rotational speed of the VAD within the cardiac cycle of the assisted heart and to synchronize the alteration of the rotational speed with the heartbeat by at least one sequence of trigger signals (σ(t)) that is related to at least one predetermined characteristic event in the cardiac cycle. Further, a VAD (50) for assistance of a heart comprises the control device (100) for controlling the VAD, wherein the VAD is preferably a non-pulsatile rotational, for example catheter-based, blood pump.

The invention discloses a PET / MR (positron emission tomography / magnetic resonance) all-in-one machine-based dynamic attenuation correction and respiratory and cardiac dual motion correction method. The method comprises the following steps of: generating a dynamic mu graph of a respiratory cycle; mR cardiac function movie sequence scanning of the cardiac cycle; accurately segmenting the cardiac muscle; 6, performing tissue segmentation on the dynamic mu graph; clustering the PET data; pET data space-time registration is carried out; merging PET data of the same time phase; performing frame-by-frame dynamic attenuation correction; respiratory movement correction; correcting a partial volume effect; carrying out myocardial MR image space standardization on different time phases of the cardiac cycle; and carrying out spatial standardization on the myocardial PET image of different time phases in the cardiac cycle. According to the method, the mu graph of the respiration and cardiac cycles is reconstructed through time-phase sharing and is accurately registered with the PET data, so that the high-quality attenuation correction of the heart PET image is realized and the motion correction is completed at the same time.

The invention provides an artificial valve leaflet fatigue life evaluation method, system and device and a medium. The method comprises the steps that stress load spectrums borne by artificial valve leaflet surface fatigue failure risk points in a plurality of cardiac cycles are obtained; obtaining the number of load sequence segments of the stressed load spectrum of any cardiac cycle after the trend of the borne load tends to be stable, and the alternating stress, the average stress and the cycle number of each segment of load sequence; calculating the fatigue failure cycle index of the corresponding artificial valve leaflet material standard sample piece under each section of load sequence; calculating the ratio of the cycle number to the fatigue failure cycle number under each section of load sequence to calculate the fatigue damage under the section of load sequence; and obtaining the sum of the fatigue damages under all the load sequences, and obtaining the reciprocal of the fatigue damages as the expected fatigue life. The method has the advantages of being short in time consumption, low in cost, low in difficulty, high in accuracy, high in precision and few in limitation.

The invention discloses an atlas segmentation method, and particularly relates to a nuclear magnetic multi-time sequence image atlas segmentation method and device and electronic equipment, and the method comprises the steps: carrying out the data splitting of nuclear magnetic multi-time sequence image data, and obtaining first data and second data, the nuclear magnetic multi-time-sequence image data comprises a time sequence dimension, a position dimension, an image height dimension and an image width dimension, the first data comprises the time sequence dimension, the image height dimension and the image width dimension, and the second data comprises the position dimension, the image height dimension and the image width dimension; carrying out cardiac cycle position regression based on the first data to obtain a cardiac cycle position of the image data; performing relative spatial position regression based on the second data to obtain a relative spatial position of the image data; and based on the cardiac cycle position and the relative spatial position of the image data, performing map segmentation on the image data to obtain a map segmentation result. According to the method, a better map segmentation effect can be realized.

The invention provides a control method and system of an in-aorta balloon counterpulsation system, and relates to the technical field of medical system control. According to the method provided by the invention, through the pre-trained neural network model, the target cardiac cycle of the target user can be quickly and accurately determined according to the historical electrocardiogram monitoring data of the target user under the condition that the target user has arrhythmia or the electrocardiogram signal quality is poor; according to the embodiment of the invention, the target cardiac cycle of the IABP system is obtained, and then inflation and deflation control of the air bag of the IABP system is realized according to the target cardiac cycle, compared with a mode of controlling the IABP system through electrocardio triggering in related technologies, the method provided by the embodiment of the invention can effectively improve the safety and effectiveness of the IABP system, and the use risk of a user is reduced.

Planning cardiac surgery is a complex task. Current heart models are mostly static and provide no functional information or personalization apart from structural information from imaging modalities like MRI, CT etc. The embodiments of present disclosure addresses unresolved problem of generating a personalized four dimensional cardiac model that integrates blood flow velocity, pressure profile and volume on three-dimensional cardiac structure, providing a comprehensive tool for pre or post-surgical planning and analysis. Unlike existing techniques, which often rely on separate assessments of cardiac anatomy and hemodynamics, using invasive methods, the present disclosure provides a 4D cardiac model that captures the person specific dynamic interaction between cardiac structures and blood flow throughout the cardiac cycle. Further, the 4D cardiac model enables clinicians to visualize and quantify complex flow patterns and pressure distributions within the region of interest in the heart, facilitating precise surgical planning and outcome prediction especially in pediatric heart surgery.

In some examples, a medical aspiration system is configured to control medical aspiration based on a cardiac cycle of a patient. For example, a medical aspiration system can include a suction source configured to apply a suction force to a catheter to remove fluid from the catheter, and control circuitry configured to control the suction force applied by the suction source to the catheter based on a cardiac cycle of a patient.

A system is provided for generating and displaying a sequence of three-dimensional (3D) graphics that illustrate motion of the heart over a cardiac cycle. The system generates a start heart wall mesh and an end heart wall mesh that represent a start geometry and an end geometry of a heart wall derived from a start 3D image and an end 3D image. The system then generates one or more an intermediate heart wall 3D meshes based on an intermediate geometry of the heart wall. An intermediate geometry is interpolated based on the start geometry and the end geometry factoring a start time of a start heart wall mesh, an end time of the end heart wall mesh, and an intermediate time for the intermediate heart wall mesh. The system then displays in sequence representations the heart wall 3D meshes to illustrate the motion.

The invention relates to the technical field of medical image processing, in particular to an aortic valve automatic segmentation method based on a multi-temporal CTA image. The method comprises the following steps: identifying a laminar flow dark area and a vortex bright area on a cross section of an aortic sinus area; according to the first feature size of the laminar flow dark area and the second feature size of the vortex bright area, the valve leaflet-sinus wall spacing is determined; determining a first deviation index according to the change trend of the valve leaflet-sinus wall spacing in the cardiac cycle; determining a second deviation index according to a difference characteristic between the CT value of the laminar flow dark area and the CT value of the eddy current bright area; if the first deviation index and the second deviation index both exceed the corresponding threshold values, judging that the data is in a to-be-corrected time phase; correcting the spacing by using the correction weight calculated by the second deviation index; and extracting key parameters of each time phase on the longitudinal section, and associating the corrected valve leaflet-sinus wall spacing to construct a valve three-dimensional dynamic model, thereby facilitating the three-dimensional dynamic model to output more accurate valve motion data.

The invention relates to a heart health state detection method and device and electronic equipment, and the method comprises the steps: determining a plurality of first feature sets and a plurality of second feature sets in a short-time feature set based on a to-be-detected heart sound signal, each first feature set being determined based on the signal amplitude of the heart sound signal in a corresponding window at each sampling point, and each second feature set being determined based on the signal amplitude of the heart sound signal in the corresponding window at each sampling point; each second feature set is determined based on the duration of a first heart sound interval, a systolic period, a second heart sound interval and a diastolic period included in each cardiac cycle in the heart sound signal in the corresponding window; based on the heart sound signal to be detected, a time domain feature set, a frequency domain feature set and a Poincare map related parameter set in the long-time feature set are determined, the time domain feature set is determined based on the duration of each cardiac cycle, the frequency domain feature set is determined based on signal power, and the Poincare map related parameter set is determined based on a Poincare map generated based on the duration of each cardiac cycle; and inputting the short-time feature set and the long-time feature set into a set heart health state detection model to obtain a heart health state result.

The invention discloses an aortic valve function evaluation device which comprises a processor and a memory, and the memory stores programs or instructions capable of running on the processor. When the program or the instruction is executed by the processor, the following steps are realized: acquiring a first echocardiogram of a target object corresponding to a final systole and a second echocardiogram of a target object corresponding to a final diastole in a cardiac cycle, and acquiring medical record data of the target object; determining a first mask pattern corresponding to the first echocardiogram and a second mask pattern corresponding to the second echocardiogram according to the first echocardiogram, the second echocardiogram and an aortic valve segmentation model; determining an aortic valve morphological index of the target object according to the first mask pattern and the second mask pattern; determining aortic valve functional indexes of the target object according to the medical record data of the target object; and determining and outputting an aortic valve function evaluation result of the target object according to the first mask pattern, the second mask pattern, the aortic valve morphological index and the aortic valve functional index.

Systems and methods and devices are provided for treating conditions such as heart failure and / or pulmonary hypertension by at least partially occluding flow through the superior vena cava for an interval spanning multiple cardiac cycles. A catheter with an occlusion device is provided along with a controller that actuates a drive mechanism to provide at least partial occlusion of the patient's superior vena cava, which reduces cardiac filling pressures, and induces a favorable shift in the patient's Frank-Starling curve towards healthy heart functionality and improved cardiac performance. The occlusion device may include a lumen obstructed by a relief valve that may permit fluid flow through the occlusion device to release an excessive build-up of pressure.

The invention provides a heart sound anomaly detection method and device, electronic equipment and a storage medium. An original heart sound signal is acquired and preprocessed into a standard heart sound signal, a plurality of cardiac cycles are divided to form a periodic heart sound signal, and corresponding Mel filter bank coefficient features and Mel frequency cepstral coefficient features are extracted; fusing the Mel filter bank coefficient features and the Mel frequency cepstrum coefficient features, inputting the fused Mel filter bank coefficient features and Mel frequency cepstrum coefficient features into an encoder in a pre-trained MobileNetV2 network, capturing a long-distance dependency relationship in the periodic heart sound signals by using a self-attention mechanism, and outputting a potential space representation vector; and inputting the potential space representation vector into a classifier of the MobileNetV2 network, and outputting a prediction result through a Softmax function. According to the method, the model complexity can be greatly reduced while the model precision is guaranteed, effective features can be extracted while low calculation overhead is kept, and the recognition capability and generalization performance of the model on abnormal heart sounds can be enhanced.

The invention discloses a conversion model for generating an ECG signal from a PPG signal, which comprises a period sensing module, a Transform extraction framework and an adaptive aggregation module, and is characterized in that the period sensing module is used for identifying and extracting a periodic component in an originally input PPG signal, determining a frequency related to a cardiac cycle, remodeling an input time sequence, and generating an ECG signal in the PPG signal; obtaining a two-dimensional periodic view formed by k different periods; a Transform extraction framework divides a two-dimensional period view formed by k different periods into a plurality of blocks Patchi corresponding to cardiac periods, and sequentially inputs each block Patchi into an embedding layer and a coding layer for processing, and captures output representation X ''i changing in the periods and between the periods in PPG signal data, and a feature sequence # imgabs0 # matched with the length of the original PPG signal is obtained after remodeling, and the adaptive aggregation module adopts a weight aggregation method to aggregate the feature sequence # imgabs1 # to obtain a reconstructed ECG signal X. According to the method, physiological feature capture is enhanced through signal alignment based on the heart cycle, so that the accuracy of generating the ECG signal is improved.

System for arrhythmia detection and confirmation includes implantable medical device (IMD) having a sensing circuit for sensing cardiac activity (CA) for one or more cardiac cycles and generating one or more CA signals. An implantable pressure sensor (IPS) includes IPS sensing circuit for sensing pressure during the one or more cardiac cycles and generating one or more pressure signals. IMD and IPS include communications circuits for communicating with each other and / or an external device. One or both of IMD or IPS includes memory for storing program instructions and processor(s) for analyzing one of the CA or pressure signals, for one or more cardiac cycles, to detect a candidate arrhythmia. In response to detecting candidate arrhythmia, the processor(s) obtain another one of CA or pressure signals for cardiac cycles corresponding to the one or more cardiac cycles, and confirm or deny candidate arrhythmia based on the other one of the signals.

In one example, a method includes receiving a cardiac signal sensed by electrodes at a tissue location within the heart. A fraction is identified in the cardiac signal. The fraction identified at the tissue location is compared between a first cardiac cycle and a second cardiac cycle of the cardiac signal. Based on the comparison, a likelihood that the tissue location is causing a stable arrhythmia is estimated. Based on the estimated likelihood, the tissue location is indicated to a user as likely causing a stable arrhythmia.

Methods, systems, and devices for cardiovascular health metric determination are described. A system may be configured to receive a photoplethysmogram (PPG) signal representative of a pulse waveform for a user. The pulse waveform may include a first local maximum, a downward slope following the first local maximum, and a curved feature representative of a transition from a systolic phase to a diastolic phase of a cardiac cycle. Additionally, the system may extract one or more morphological features from the pulse waveform and compare the one or more morphological features with one or more features from a plurality of baseline PPG signal morphologies associated with a plurality of chronological ages. The system may determine a cardiovascular health metric that indicates a cardiovascular health of the user relative to a chronological age of the user and cause a graphical user interface to display an indication of the cardiovascular health metric.