68 results about "Heart arrhythmia" patented technology

Systems and Methods are disclosed for detecting acute coronary syndrome (ACS) events, arrythmias, heart rate abnormalities, medication problems such as non-compliance or ineffective amount or type of medication, and demand / supply related cardiac ischemia. The system may have both implanted and external components that communicate with a Physicians's programmer, and smart-devices for monitoring and alerting to detected medically relevant events or states. At least one processor provides event detection using statistical threshold criteria calculated upon at least a portion of a patient's data / distributions and set for a patient or based upon what a doctor determines as abnormal for a patient. Cardiovascular condition is tracked using histogram, trend, and summary information related to heart rate and / or cardiac features such as S-T segment measures of heartbeats. Heartbeats with elevated rates, and below a “high” range, provide medically relevant detections including medication non-compliance. Novel methods of power management and patient monitoring are disclosed.

Computer-implemented methods of predicting the QTc of a subject in response to administration of QTc prolonging drugs, especially those that are dose adjusted for renal function, such as antiarrhythmic drugs. Included is a method of administering an antiarrhythmic drug to a subject, comprising: providing as inputs into a treatment management application i) Baseline QTc and ii) at least a Creatinine Clearance, Weight, Age, Sex, or Heart Rate; the treatment management application providing as an output one or more predicted QTc or predicted QTc range for the subject expected from administration of a 1-5 hour IV dose, alone or followed by one or more oral doses, of an antiarrhythmic drug to the subject; and upon the one or more QTc or QTc range being within an acceptable range, administering the 1-5 hour IV dose to the subject optionally followed by administering one or more of the oral doses to the subject.

A novel catheter is disclosed comprising an electrode array that is capable of switching between a sensing configuration for sensing electrical signals of biological tissue and an ablation configuration for delivery of ablation energy at a region of interest. Irrigation ports are interlaced within the electrode array to vent irrigant during an ablation procedure to; prevent excessive heating, charring of tissue, coagulation of blood, and allow for efficient delivery of ablation therapy for maximum therapy efficacy. The novel catheter includes a plurality of splines with linear portions wherein the electrodes of the electrode array are disposed. The splines are connected by connectors which include one or more bends capable of storing potential energy when the bends are elastically deformed, enabling collapse and expansion of the catheter in a sheath. Software logic associated with this catheter analyzes sensing signals to diagnose critical regions of the biological rhythm disorder, and enables directional guidance to move the catheter to critical regions for therapy.

The present invention includes systems, devices and methods for treating and / or diagnosing a heart arrhythmia, such as atrial fibrillation. Specifically, the present invention provides a system including a diagnostic catheter and an ablation catheter. The diagnostic catheter includes a shaft, multiple dipole mapping electrodes and multiple ultrasound transducers. The ablation catheter is slidingly received by the diagnostic catheter shaft.

The invention discloses an electrocardiogram arrhythmia classification method and system based on a residual shrinkage network, and relates to the technical field of arrhythmia classification. According to the method, efficient electrocardiogram arrhythmia classification is achieved through multi-link cooperation, and a fine preprocessing, data balance strategy and multi-attention mechanism fusion model is designed; preprocessing provides high-quality input through wavelet denoising, precise R-wave detection and the like; the under-sampling-over-sampling mixed strategy is used for solving class imbalance and improving minority class recognition; the ResTCL-Net is fused with CNN, GRU, RCA, TSA and CLA modules, and signal features are mined in multiple dimensions; the optimization training strategy gives consideration to efficiency and stability, and is matched with comprehensive evaluation to guarantee performance. According to the scheme, the classification accuracy and generalization ability are remarkably improved, and abnormal heart beat recognition is enhanced.

The invention relates to the field of heart rate and heart rhythm real-time monitoring methods, in particular to a dynamic arrhythmia early warning system and method based on wearable equipment, and the method comprises the steps: 1, actually measuring an electrocardiogram of a user target in real time through the wearable equipment; step 2, the wearable device receives an active positioning signal in the medical place in real time, generates a movement track of a user target, and judges whether internal interference factors in the medical place exist on the movement track or not; 3, when the internal interference factors exist, interference marking is conducted on the electrocardiogram through the wearable device, and when the internal interference factors do not exist, abnormity judgment is conducted on the electrocardiogram through the wearable device, and early warning information is sent to the background when it is judged that the electrocardiogram is abnormal; the system comprises wearable equipment for monitoring an electrocardiogram and a background for wirelessly receiving the electrocardiogram, the wearable device collects the electrocardiogram of the target user in real time, and carries out early warning according to the early warning method. According to the invention, the interference condition in the activity process can be accurately identified.

The invention provides a multi-task electrocardiogram analysis method and system based on deep learning and a medium, and the method comprises the following steps: S1, receiving to-be-analyzed electrocardiogram data sent by a client, and preprocessing the to-be-analyzed electrocardiogram data to obtain preprocessed to-be-analyzed electrocardiogram data; s2, performing arrhythmia recognition processing on the preprocessed to-be-analyzed electrocardiogram data by using the trained multi-task electrocardiogram detection model to obtain a recognition result; and S3, transmitting an identification result to the terminal equipment. According to the method, a bimodal fusion module fusion method based on attention mechanism guidance is adopted, information fusion among different tasks is achieved, a saliency map of diagnosis information is highlighted, the problem that electrocardiosignal diagnosis is poor in interpretability is effectively solved, meanwhile, an auxiliary task based on feature point positioning is adopted, and the diagnosis accuracy is improved. The problems in the aspects of stability and robustness of the model are solved, and the effect of reducing the sensitivity to noise and data distribution change is achieved.

The invention discloses an intelligent arrhythmia classification device based on deep learning. The intelligent arrhythmia classification device comprises a data set construction module, a data preprocessing module, an intelligent arrhythmia classification network construction training module and an analysis module, the data set construction module is used for constructing a heart rhythm sample data set, the data preprocessing module is used for expanding the data set by applying a wavelet denoising method and randomly sampling the heart beat type data set with more data distribution by utilizing an undersampling principle, and the arrhythmia intelligent classification network construction training module is used for constructing an arrhythmia intelligent classification network based on a DenseNet-201 network. And carrying out model training by adopting an Adam optimizer and a learning rate attenuation strategy, and classifying the arrhythmia data set. And the analysis module explains a model classification result by utilizing a plurality of methods such as HiResCAM, LIME and SHAP. According to the method, the electrocardiogram can be rapidly analyzed, and the basis for model type judgment can be visually displayed.

The invention discloses an arrhythmia recognition method and system based on electrocardio waveform dynamic feature reconstruction, and the method comprises the steps: obtaining an electrocardiogram of a user, extracting the electrocardio potential of each cardiac blog in the electrocardiogram, and calculating the deformation rate vector of each cardiac blog according to the electrocardio potential; according to the deformation rate vector, calculating a heart rhythm transition value between the heart blogs as a heart rhythm transition fingerprint, calculating heart beat form difference energy between the heart blogs, and generating a form fluctuation index of each heart blog according to the heart beat form difference energy; and acquiring a change acceleration of the form fluctuation index between heart blogs, mapping the change acceleration, the form fluctuation index and the cardiac rhythm transition value into a discrete symbol, and inputting the discrete symbol into a diagnosis synthesizer to output an arrhythmia identification result.

The invention provides a self-supervised learning method and system for evaluating arrhythmia. The method comprises the steps that S1, electrocardiogram signals collected by different devices are resampled to a preset number of sampling points; s2, performing residual block configuration on input and output of different dimensions by using a convolutional neural network; s3, automatically extracting hidden features of the electrocardiogram signal by using a feature extractor; s4, a data enhancement method is used for converting the input electrocardiosignals; and S5, establishing a pre-training framework based on the data enhancement method, and obtaining a feature extractor. Under the support of an unmarked data set, the workload of clinicians can be effectively reduced; compared with an existing method, the method has the advantages that about 25% of mark data is used, and better evaluation performance is achieved in the aspect of the average accuracy rate of 99.0%.

The invention discloses a multi-modal electrocardiosignal and arrhythmia recognition system and method. The system comprises a signal acquisition module, a preprocessing module, a space-time alignment module, a feature extraction module, a self-adaptive fusion module, a multi-modal fusion module, a classification risk assessment module and a visual report module. The recognition method comprises the following steps: S1, synchronously acquiring an electrocardiosignal and a heart sound signal, and preprocessing the electrocardiosignal and the heart sound signal; s2, establishing a time corresponding relation between the electrical activity and the mechanical activity; s3, calculating a mechanical shrinkage efficiency index; s4, evaluating the quality of the electrocardiosignal and the heart sound signal in real time, and dynamically adjusting contribution weights of the electrocardiosignal and the heart sound signal in a fusion process according to the quality; s5, adopting a multi-head attention mechanism to generate a joint feature vector for classification; s6, inputting the joint feature vector into a classification network model, and outputting an arrhythmia type and a quantitative risk level at the same time by the classification network model; and S7, generating a visual atlas and a structured diagnosis report.

The invention provides a compound shown in a formula I or pharmaceutically acceptable salts, stereoisomers, isotope derivatives, solvates (such as hydrates), prodrugs, metal chelates, crystal forms or metabolites of the compound and application of the compound in the field of medicine. The compound can be used for treating and / or preventing psoriasis diseases, especially propafenone. The invention also finds that under the condition of the same administration dosage, the effect of smearing administration on treating psoriasis diseases is better than that of injection administration. Compared with a flecainib ointment with a similar anti-arrhythmia function, the propafenone ointment disclosed by the invention has a better effect on treating psoriasis diseases.

The invention relates to the technical field of traditional Chinese medicines, in particular to a traditional Chinese medicine composition for treating arrhythmia, which comprises raw rehmannia root, dwarf lilyturf tuber, donkey-hide gelatin, ginseng, raw licorice root, Chinese date, Chinese angelica, cassia twig, ginger, polygala root and tuckahoe. According to the Qianjin pulse restoring granules prepared from the traditional Chinese medicine composition, the three-in-one treatment rule of nourishing yin and blood, warming yang and promoting coronary circulation and tonifying qi and soothing the nerves is put forward, and the core pathogenesis of arrhythmia of yin-yang deficiency and heart-vessel malnutrition is focused on that yin-blood deficiency causes heart-vessel malfunction, yang-qi deficiency causes agitation and weakness, the yin-blood deficiency and the yang-qi deficiency cause causes and effects of each other, and palpitation, pulse stagnation and the like are caused. The traditional Chinese medicine composition breaks through the limitation of'partial yin tonifying 'or'partial yang tonifying' of the traditional prescription, and by regulating yin and yang and tonifying both qi and blood, 'sufficient yin blood and filled pulse, and recuperating yang qi and dredging pulse ', not only is the root cause of deficiency of yin and blood solved, but also the symptom of deficiency of yang qi is improved, and the technical effect of'treating both symptoms and root causes' is achieved.

The invention relates to an intelligent grading early warning method, device and equipment for an electrocardio critical value and a storage medium, and the method comprises the steps that an obtained electrocardio signal of a user is analyzed and processed, and arrhythmia features are determined; based on a preset multi-level grading standard, carrying out danger level judgment on the arrhythmia features, and determining a target danger level; according to the target danger level, a visual report is generated, and the visual report comprises a heart rate time sequence diagram and target guidance information associated with the target danger level; compared with the prior art, according to the technical scheme, the arrhythmia features can be determined by analyzing the electrocardiosignals, the danger level is judged according to the multi-level standard, and finally the visual report containing the target guidance information is generated, so that the problem of confusion after detection of a user can be effectively solved, a health management closed loop from detection to intervention is realized, and the user experience is improved. And meanwhile, the understanding and coping efficiency of the user on the electrocardio result is improved.

This invention discloses an ECG data classification method based on continuous test-time adaptation. This method improves the model's generalization ability during testing without modifying the source model's training process, accessing the source data, or requiring target domain data labels. This allows the model to adapt to constantly changing testing environments. The proposed continuous test-time adaptation ECG data classification method mitigates catastrophic forgetting by restoring some model parameters to their original source parameters during the test-time adaptation process, without affecting model performance. The ECG data preprocessing method used in this invention is simple and does not require noise filtering or feature extraction. Traditional ECG data preprocessing methods heavily rely on the researcher's experience and are ineffective. Due to suboptimal extracted features, the model is highly sensitive to noise signals during training.

This disclosure presents systems and methods for baroreflex activation therapy (BAT) to regulate inflammation by modulating autonomic nervous system activity. Electrical stimulation is delivered to one or more baroreceptors, and real-time physiological signals are monitored, including inflammatory biomarkers (e.g., TNF-α, IFN-γ, IL-1, IL-6, IL-12, CRP) and autonomic parameters such as heart rate variability (HRV). A closed-loop feedback module analyzes biomarker fluctuations and autonomic balance changes and dynamically modifies stimulation parameters, including amplitude, pulse width, frequency, and duty cycle, to suppress systemic inflammation and restore autonomic balance. In certain embodiments, multi-channel stimulation architectures and AI-driven algorithms or machine learning models analyze biomarker trends and historical patient response patterns to optimize therapy. The disclosed BAT systems and methods may be used to treat inflammatory diseases, autoimmune disorders, cancer progression, chronic inflammatory pain conditions, arrhythmias associated with inflammation, and metabolic dysfunction.

The invention relates to a zebrafish model for screening arrhythmia drugs and application thereof, and belongs to the technical field of biological medicines. According to the transgenic zebrafish provided by the invention, an appropriate arrhythmia zebrafish model can be screened out through a fluorescence intensity IOD value, the fluorescence intensity is in positive correlation with the transgenic expression quantity, the transgenic expression level can be quickly judged according to the fluorescence intensity, and an appropriate individual can be selected for subsequent experiments. Isoprenaline is an anti-arrhythmia drug which is widely used clinically at present, an isoprenaline treatment experiment verifies the effectiveness of the model for screening the anti-arrhythmia drug, and the model is not only suitable for researching the pathogenesis of hereditary arrhythmia diseases, but also suitable for researching the pathogenesis of the hereditary arrhythmia diseases. Technical support is also provided for research and development of arrhythmia treatment medicines, and important theoretical significance and wide application prospects are achieved.

This application discloses a method, device, storage medium, and equipment for predicting the risk of sudden cardiac death due to arrhythmia, relating to the field of biomedical technology. The method includes: acquiring multi-channel cardiac magnetic signals from a subject; performing fidelity enhancement processing on the multi-channel cardiac magnetic signals to extract core features characterizing the cardiac magnetic field; constructing a topological geometric model of the cardiac fiber plexus; extracting topological invariants of the cardiac electrical conduction system based on the core features and the topological geometric model; conducting non-equilibrium phase transition dynamics detection on the topological geometric model of the cardiac fiber plexus to obtain phase transition features reflecting the stability of the cardiac electrical conduction system; inputting the topological invariants and phase transition features into a preset topological neural network to complete a quantitative analysis of the degree of chaos in the cardiac electrical conduction system; and generating a risk score and early warning indicators for sudden cardiac death due to arrhythmia based on the quantitative analysis results. This application can achieve accurate early warning of the risk of sudden cardiac death due to arrhythmia.

Disclosed are various examples and embodiments of systems, devices, components and methods configured to estimate the action potential wave propagation in a patient's heart, and subsequently to detect at least one location or type of at least one source of, or rotational phenomenon associated with, at least one cardiac rhythm disorder using intracardiac electrodes and a modified multi-frame Horn-Schunck algorithm to generate a map corresponding to a spatial map, the map being configured to reveal on a monitor or display to a user the at least one location of the at least one source of the at least one cardiac rhythm disorder.

Described herein are implantable medical devices and systems, and methods for use therewith, for reducing T-wave oversensing and arrythmia undersensing that occur due to inappropriate filtering of a signal indicative of cardiac electrical activity. A method includes obtaining a signal indicative of cardiac electrical activity, and using a first bandpass filter to produce a first filtered version thereof, using a second bandpass filter to produce a second filtered version thereof, wherein the first bandpass filter passes frequencies within a first frequency range, and the second bandpass filter passes frequencies within a second frequency range that is wider than the first frequency range. The method also includes selectively changing from using the first filtered version of the signal to monitor for a VS event, to using the second filtered version of the signal to monitor for a VS event, based on first criteria, and vice versa, based on second criteria.

The invention relates to the technical field of electrocardiogram automatic recognition algorithm, and discloses an electrocardiogram automatic recognition algorithm based on a convolutional neural network, comprising: a component database: the database used is an arrhythmia database; preprocessing: preprocessing the electrocardiogram signal of the selected lead; data amplification: data amplification of the heartbeat type with a small sample size by changing the sample mean and variance; the network structure comprises 3 convolutional layers, 3 pooling layers and 3 fully connected layers; the invention proposes an electrocardiogram automatic recognition algorithm based on a convolutional neural network, the invention has multiple recognition types and high recognition accuracy.

The invention relates to an ointment formula based on qi and blood tonifying and heart and kidney dredging and regulating and a preparation method, and belongs to the technical field of traditional Chinese medicine, the ointment is prepared from ginseng, astragalus membranaceus, five-prepared rehmannia glutinosa, Chinese yam, poria cocos, deer-horn glue, tortoise plastron, donkey-hide gelatin, dogwood, fructus lycii, semen cuscutae and other medicinal materials according to a specific ratio. The preparation method comprises the following steps: grinding part of the medicinal materials into powder, decocting the prepared rhizome of rehmannia firstly, decocting a plurality of sub-medicinal materials together, melting the glue medicinal materials by heat, mixing with other medicinal material decoctions, and concentrating to obtain the ointment. Through the synergistic effect of the medicinal materials, the comprehensive effects of reinforcing qi and nourishing yin, warming yang and promoting diuresis, tonifying kidney and replenishing essence and promoting circulation of heart and kidney are achieved, and the traditional Chinese medicine composition has the advantages of being comprehensive in curative effect, small in side effect and sufficient in component retention for consumptive disease, premature senility, chronic heart failure and arrhythmia caused by deficiency of qi and blood, yang deficiency and water flooding and heart and kidney disharmony.

The application discloses a method and device for arrhythmia analysis based on heart beat classification, equipment and medium, wherein the method comprises: generating a morphology amplitude coding vector of a target heart beat segment as a target morphology amplitude coding vector, the target heart beat segment being any one of the heart beat segment time series set; performing inner product calculation on the target morphology amplitude coding vector and each heart beat template vector in a preset heart beat template vector set to obtain an inner product value set; determining a target heart beat type corresponding to the target heart beat segment according to the inner product value set; and performing arrhythmia analysis on each target heart beat type corresponding to the heart beat segment time series set to obtain an arrhythmia analysis result. The application avoids the technical problems that the traditional method may have a large amount of calculation, ignores the amplitude difference of the waveform and easily ignores the morphology difference of the waveform when the amplitude is low, has simple steps and small calculation amount, and is thus suitable for real-time monitoring scenes.

The invention discloses a peptide-magnesium compound as well as a preparation method and application thereof, and belongs to the technical field of biological medicines. The peptide-magnesium compound is prepared from the following raw materials in parts by mass: 6 to 18 parts of deer heart peptide, 35 to 60 parts of oligopeptide, 21 to 34 parts of organic acid magnesium salt, 0.01 to 0.1 part of vitamin and 60 to 115 parts of water. According to the compound, peptide serves as a carrier and is chelated with organic acid magnesium salt, a thermodynamically stable compound is formed, the absorption rate of magnesium is increased, meanwhile, release of inflammatory factors can be reduced, synthesis of bone matrixes can be promoted, the deer heart peptide and magnesium act synergistically, generation of ATP is promoted, vitamin serves as a coenzyme to optimize magnesium metabolism, and the components act synergistically, so that the effect of improving the magnesium absorption rate is achieved. The peptide-magnesium compound has the effects of improving heart failure, myocardial ischemia, arrhythmia and palpitation, preventing metabolic disorder, improving sleep and preventing and treating osteoporosis and diabetes.

Provided are a novel sodium channel modulator compound and a use thereof. The sodium channel modulator has a completely new structure as shown in formula I, and exhibits excellent in vitro inhibitory effects against Nav 1.8. The compound or a pharmaceutically acceptable salt thereof can be used for treating sodium channel-related diseases, including diseases such as pain, multiple sclerosis, Charcot-Marie-Tooth disease, incontinence, pathological cough, or arrhythmia.

Systems and methods for declaring cardiac activity pauses include a memory for storing specific executable instructions and a convolutional neural network (CNN) model including a global average pooling (GAP) layer. The one or more processors are configured to execute particular executable instructions to obtain a device-classified arrhythmia (DCA) dataset generated by an implantable medical device (IMD) for a corresponding candidate pause episode announced by the IMD. The DCA data set includes one or more pulsated cardiac activity (CA) signals sensed by the IMD. The processor (s) applies the CNN model to the DCA data set to identify a valid subset of the DCA data set that correctly characterizes the corresponding CA signal. The display is configured to present information about a valid subset of the DCA data set.

To provide pharmaceutical compositions comprising an antiarrhythmic agent for treatment of a heart condition via inhalation, and methods for treatment.SOLUTION: Methods for treating a heart condition include the step for administering by inhalation of an effective amount of at least one antiarrhythmic pharmaceutical agent to a patient in need thereof. Nebulized drug product and kits are also disclosed.SELECTED DRAWING: Figure 23A

The present disclosure relates to a medicinal composition and related methods using Lawsone (2-hydroxy-1,4-naphthoquinone) as a key active ingredient for treating pain associated with chemotherapy-induced palmar plantar erythrodysesthesia (Hand-Foot Syndrome). The medicinal composition may be administered topically as a gel, ointment, cream, lotion, suspension, spray, transdermal patch or liquid alone or in combination with other topical steroids, topical NSAIDS, antiarrhythmics, moisturizers, capsaicin, emollients, herbal remedies and essential or carrier oils. The medicinal composition eliminates the pain and burning sensation experienced with palmar-plantar erythrodysesthesia and allows patients to carry on with normal daily activities after a session of chemotherapy.

Embodiments of the invention are broadly drawn to methods for determining an optimum dose of an antiarrhythmic drug, for example sotalol. In particular, the method involves titrating the dose of the drug gradually to determine the optimum plasma concentration for a patient, whether the patient has normal or abnormal renal function.

A power generator is disclosed for generating ablating energy deliverable to a catheter for treatment of heart rhythm disorders. The power generator includes a first output port configured to deliver ablation energy through a first conductive wire of a catheter and a second output port configured to receive a sensing signal from a thermocouple junction formed at a catheter electrode. The generator includes a first power driver for producing waveforms suitable for radiofrequency ablation (RFA) and a second power driver for generating pulsed waveforms suitable for pulsed field ablation (PF A). A switching circuit selectively couples one of the power drivers to the first output port based on a selected ablation modality. A control circuit receives an input indicating the selected modality and controls the switching circuit accordingly. The system enables dual-modality ablation using a shared catheter interface, facilitating seamless transition between RFA and PF A without requiring hardware reconfiguration.