22 results about "Atrial fibrillation" patented technology

The present invention provides a long non-coding RNA (lncRNA) biomarker composition in serum exosomes, comprising LOC105377989, LOC105375434, LOC107986997, and LOC101927073, for diagnosing atrial fibrillation on the basis of the results of profile analysis of lncRNA in serum exosomes of patients with atrial fibrillation. When used, the lncRNA biomarker composition enables non-invasive in-vitro diagnosis, and exhibits an excellent effect in atrial fibrillation diagnosis, and thus is highly applicable as a useful diagnostic biomarker for atrial fibrillation.

This invention provides a method and system for predicting atrial fibrillation (AF) load based on intermittent PPG signals, belonging to the field of data processing technology. The method includes: training a first neural network using a first PPG signal with known AF results to obtain an AF probability prediction model; using the AF probability prediction model to predict the AF probability of a second PPG signal within a target time period and mapping it to an AF risk value; determining the AF probability at any given time based on the risk values ​​of two adjacent second PPG signals, integrating to obtain the total AF time, and thus obtaining the AF load; training a second neural network using historical AF loads from multiple time periods to obtain an AF load prediction model, used to predict the AF load for multiple future time periods. This invention achieves quantitative assessment and future trend prediction of AF load from discrete PPG signals to continuous AF load.

The application discloses a kind of dabigatran bleeding risk prediction methods based on machine learning, it is related to computer-aided drug risk management technical field, the method is by obtaining patient baseline and follow-up data, multiple imputation method is handled missing value;With HAS-BLED score as the basis, candidate variables are screened from potential risk factors using LassoCV algorithm, and anemia, insulin use and antifungal agent use are determined as new prediction variables through clinical correlation analysis to construct a set of prediction variables;Finally, a random forest or gradient boosting algorithm is used to train the model to output the bleeding risk assessment results of the individual to be tested.The application combines machine learning algorithm, improves the prediction accuracy of dabigatran bleeding risk in Chinese non-valvular atrial fibrillation patients, solves the problem of insufficient prediction accuracy of traditional HAS-BLED score, and provides a more reliable basis for clinical individualized anticoagulant therapy decision.

The present disclosure pertains to cardiac pacing methods and systems, and, more particularly, to cardiac resynchronization therapy (CRT). In particular, the present disclosure pertains to determining whether a patient is experiencing atrial fibrillation (AF). If the patient is experiencing AF, the efficacy of CRT is determined. A signal is sensed in response to a ventricular pacing stimulus. Through signal processing, a number of features are parsed from the signal and a determination is made as to whether the ventricular pacing stimulus evoked a response from the ventricle.

This invention discloses a targeted adjuvant influenza vaccine composition for atrial fibrillation patients with atrial fibrosis. The vaccine antigen components are selected from the surface antigens of currently prevalent influenza virus strains, such as hemagglutinin (HA) and neuraminidase (NA). High-purity influenza virus antigens are prepared through cell culture or recombinant DNA technology. For example, influenza virus is cultured using Madin-Darby canine kidney (MDCK) cells, and purified through centrifugation, filtration, and chromatography to obtain high-purity HA and NA antigens. After injection into the human body, the influenza virus antigens (HA and NA) are taken up and processed by antigen-presenting cells (such as macrophages and dendritic cells). The antigen-presenting cells present antigen peptides to T lymphocytes and B lymphocytes, activating a specific immune response. B lymphocytes differentiate into plasma cells with the help of T lymphocytes, producing specific antibodies that recognize and bind to the influenza virus, preventing it from infecting host cells and thus preventing influenza virus infection.

RNA interference (RNAi) agents for inhibiting the expression of Factor XI (FXI) are provided, as are pharmaceutical compositions comprising one or more FXI RNAi agents together with one or more excipients capable of delivering the RNAi agent(s) to a liver cell in vivo. Delivery of the FXI RNAi agent(s) to liver cells in vivo provides for inhibition of FXI gene expression and can provide for treatment of myocardial infarction, atrial fibrillation (AFib), deep vein thrombosis, pulmonary embolism, ischemic stroke, transient ischemic attack, retinal artery occlusion, mesenteric ischemia, renal vein thrombosis, cerebral venous sinus thrombosis, venous thromboembolism due to deep vein thrombosis, and peripheral artery disease, as well as diseases and disorders associated with angioedema, thrombosis, and / or coagulation.

Provided herein are compositions and methods for the inhibition of nerve growth factor (NGF) and the treatment / prevention of atrial fibrillation. In particular, inhibitors of NGF expression are administered to the myocardial tissue of a subject to treat or prevent atrial fibrillation and / or autonomic nerve sprouting in the atria.

This invention discloses a method, system, and storage medium for atrial fibrillation detection based on a stacked waterfall plot of heartbeats on electrocardiograms, belonging to the field of biomedical signal processing and machine learning technology. The method extracts heartbeat waveform data using the R-wave position as an anchor point, performs individualized grayscale normalization using the voltage range of the PR segment as a reference, and stacks multiple normalized heartbeat waveforms vertically in chronological order to generate a two-dimensional grayscale waterfall plot image. Then, it achieves dense prediction per heartbeat through multiple independent sigmoid output nodes of a two-dimensional convolutional residual network. On a multi-center independent test set of approximately 5.9 million heartbeats, the method achieved an F1 score of 0.9944 and a recall rate of 99.88%. This invention preserves the original waveform morphology information, has good multi-device compatibility, and is suitable for electrocardiogram acquisition devices with various lead configurations.

RNA interference (RNAi) agents for inhibiting the expression of Factor XI (FXI) are provided, as are pharmaceutical compositions comprising one or more FXI RNAi agents together with one or more excipients capable of delivering the RNAi agent(s) to a liver cell in vivo. Delivery of the FXI RNAi agent(s) to liver cells in vivo provides for inhibition of FXI gene expression and can provide for treatment of myocardial infarction, atrial fibrillation (AFib), deep vein thrombosis, pulmonary embolism, ischemic stroke, transient ischemic attack, retinal artery occlusion, mesenteric ischemia, renal vein thrombosis, cerebral venous sinus thrombosis, venous thromboembolism due to deep vein thrombosis, and peripheral artery disease, as well as diseases and disorders associated with angioedema, thrombosis, and / or coagulation.

This invention discloses a method, apparatus, device, and medium for detecting atrial fibrillation heart sounds in a small sample. The method includes: preprocessing heart sound signals, constructing a source domain dataset and a heart sound feature extraction network, training the heart sound feature extraction network using labeled data to obtain pre-trained weights; using heart sound data diagnosed with atrial fibrillation as target domain small sample data, freezing the shallow parameters in the heart sound feature extraction network, and employing an imbalanced learning strategy to obtain a fine-tuned model adapted to the target domain; using the fine-tuned model to predict unlabeled or weakly labeled heart sound data; calculating confidence based on the obtained atrial fibrillation prediction probability, selecting heart sound data with confidence higher than a preset confidence threshold, and generating pseudo-labels; using labeled data, target domain small sample data, and heart sound data with pseudo-labels to form a mixed training set, iteratively retraining the heart sound feature extraction network to obtain an atrial fibrillation heart sound recognition model, and using this model to predict atrial fibrillation in detected heart sound signals.

The application provides a sheath tube of an adjustable bending guide sheath, a sheath seat and a bonding method, and is mainly applied to an adjustable bending guide sheath in the field of atrial fibrillation ablation treatment or the field of atrial fibrillation left atrial appendage occlusion. In the application, the structure of a sheath seat fixing mechanism and a sheath tube clamping mechanism is systematically designed, and the bonding method of the sheath seat fixing mechanism and the sheath tube clamping mechanism is exemplarily described. The problems of low qualified rate and time-consuming in the bonding process can be solved, and the qualified rate and efficiency of the bonding of the adjustable bending sheath tube and the sheath seat are improved.

The application provides an atrial stent with a defibrillation function, and relates to the technical field of medical devices.The stent comprises a ball cage and a defibrillation catheter; the ball cage is installed in an atrium; one end of the defibrillation catheter is arranged around the ball cage, and the other end is connected with a defibrillation power supply; and a plurality of electrodes are arranged at intervals on the defibrillation catheter around the ball cage.In the embodiment of the application, when a patient has atrial fibrillation, the defibrillation catheter is electrified, the atrial nerves of the patient are ablated through the electrodes, the patient can be defibrillated in time and effectively, and the life safety of the patient is ensured.

This invention discloses a smart bracelet for atrial fibrillation early warning based on multimodal biosignal fusion and its analysis method. The bracelet includes a ring-shaped main body, adapted to fit the user's wrist, made of biocompatible material. The main body contains cavities and mounting structures to accommodate and fix various functional modules, and exposes the optical window of the PPG signal acquisition module and the electrode contacts of the ECG signal acquisition module. Each functional module further includes a motion sensor module, a signal processing unit, a storage unit, a wireless communication module, and a power management unit. This invention relates to the field of smart bracelet technology. This smart bracelet and analysis method for atrial fibrillation early warning, through the fusion of dual-modal data from PPG and ECG, combined with the artifact removal capabilities of motion sensor data, overcomes the limitations of single signals. The PPG signal provides continuous hemodynamic information and is sensitive to early and subtle changes in heart rate and rhythm.

A catheter with a planar end effector having elongated ablation electrodes configured to provide electrical signals to achieve intravascular resection (IRE) in target tissue is presented. The planar end effector is alignable along the longitudinal axis of the catheter and configured to flex away from the longitudinal axis upon contact with tissue. Bipolar electrical signals can be applied between the elongated ablation electrodes in various combinations to achieve partial invasive ablation (PFA). The end effector may also include diagnostic electrodes configured to receive electrical signals from tissue to map the tissue, paired tissue contact electrodes for determining which portions of the end effector are in contact with the tissue, or reference electrodes configured to measure blood voltage.

A catheter is presented having a planar end effector with elongated ablation electrodes configured to provide electrical signals to achieve IRE in target tissue. The planar end effector can be aligned along a longitudinal axis of a shaft of the catheter and configured to flex away from the longitudinal axis when making contact with tissue. Bipolar electrical signals can be applied between the elongated ablation electrodes in various pair combinations to achieve PFA. The end effector may also include diagnostic electrodes configured to receive electrical signals from tissue to map tissue, pairs of tissue contact electrodes to determine which portions of the end effector are in contact with tissue, or reference electrodes configured to measure blood voltage.

This invention discloses a method and system for detecting atrial fibrillation (AF) on electrocardiograms based on the fusion of time-series and waterfall plot models, belonging to the fields of biomedical signal processing and deep learning technology. This method simultaneously constructs two complementary data representations of the same electrocardiogram signal: a fixed-duration one-dimensional time-series segment and a two-dimensional heartbeat stacked grayscale waterfall plot aligned with the R-wave. These are respectively input into independently trained one-dimensional and two-dimensional convolutional residual networks for classification. Finally, the outputs of the two models are aligned at the heartbeat time granularity, and the final AF detection result is obtained through a configurable fusion strategy (intersection, union, or weighted voting). The time-series model excels at capturing abnormal heart rate rhythms, while the waterfall plot model excels at identifying abnormal waveform morphology; the two are significantly complementary in boundary cases. In 2,433,594 heartbeat tests with balanced distribution of AF and NAF samples (AF accounting for 43.7%), the false alarm rate decreased from 4.30% to 1.30% and the missed alarm rate decreased from 1.07% to 0.59% after adopting the intersection fusion strategy. The prediction conflict rate between the two models was only 2.43%, which proves that the two-dimensional fusion has a significant complementary gain effect under neutral distribution conditions.

The current methods and compositions relate to treatment of atrial fibrillation with bucindolol in patients, including patients with heart failure, after being determined to be homozygous Arg389 in the β1 adrenergic receptor gene.

A method is provided. The method is implemented by a detection engine embodied in processor executable code stored on a memory and executed by at least one processor. The method includes modeling a vector velocity field that measures and quantifies a velocity of electrocardiogram data signals that pass through a local activation time. The method further includes determining codes for each point in plane to provide a color code vector field image; detecting focal and rotor indications by using kernels to scan the color coded vector field image; and classifying the focal and rotor indications into perpetuators.

This invention relates to a management platform and its implementation path for elderly atrial fibrillation (AF) patients in rural areas, primarily aimed at addressing the heavy management burden and uneven distribution of medical services for AF patients. AF has high disability and mortality rates, increasing the risk of stroke, heart failure, and sudden death, especially in the rapidly aging rural areas of Chengdu, where the management burden is particularly prominent. This invention achieves this through the following technical solutions: First, it conducts routine opportunistic screening for AF based on government-led rural public health check-up programs, incorporating diagnosed patients into digital grid management units; second, it creates digital data on high-risk AF patients, achieving grid-based and information-based management; the expected results include realizing a digital grid-based AF management cloud platform for "decision sharing" between doctors and patients, standardizing the comprehensive management of AF patients in rural areas, forming a theoretical framework for a "rural elderly AF management model" with Chengdu characteristics, and providing a scientific basis for policy formulation.