Patents
Literature
16 results about "Electrodiagnosis" patented technology
Efficacy Topic
Property
Owner
Technical Advancement
Application Domain
Technology Topic
Technology Field Word
Patent Country/Region
Patent Type
Patent Status
Application Year
Inventor
Electrodiagnosis (EDX) is a method of medical diagnosis that obtains information about diseases by passively recording the electrical activity of body parts (that is, their natural electrophysiology) or by measuring their response to external electrical stimuli (evoked potentials). The most widely used methods of recording spontaneous electrical activity are various forms of electrodiagnostic testing (electrography) such as electrocardiography (ECG), electroencephalography (EEG), and electromyography (EMG). Electrodiagnostic medicine (also EDX) is a medical subspecialty of neurology, clinical neurophysiology, cardiology, and physical medicine and rehabilitation. Electrodiagnostic physicians apply electrophysiologic techniques, including needle electromyography and nerve conduction studies to diagnose, evaluate, and treat people with impairments of the neurologic, neuromuscular, and/or muscular systems. The provision of a quality electrodiagnostic medical evaluation requires extensive scientific knowledge that includes anatomy and physiology of the peripheral nerves and muscles, the physics and biology of the electrical signals generated by muscle and nerve, the instrumentation used to process these signals, and techniques for clinical evaluation of diseases of the peripheral nerves and sensory pathways.
Neuropsychiatric disease electroencephalogram diagnosis method based on iterative polar coordinate attention
The invention belongs to the field of electroencephalogram signal classification detection, and particularly relates to a neuropsychiatric disease electroencephalogram diagnosis method based on iteration polar coordinate attention, which comprises the following steps: acquiring a multi-channel EEG (electroencephalogram) signal and preprocessing the multi-channel EEG signal; inputting the EEG preprocessing signal into a pre-trained improved LaBraM model to obtain a plurality of node features; calculating a Pearson's correlation coefficient matrix and a cosine similarity matrix according to the EEG preprocessing signal, and then constructing a brain function fusion connection matrix as an adjacent matrix through an iteration polar coordinate attention mechanism; according to the method, the large-scale pre-trained EEG model and polar coordinate attention are used for brain graph structure construction for the first time, and collaborative optimization of time feature generalization and space structure modeling capacity is achieved.
Owner:CHONGQING UNIV OF POSTS & TELECOMM
A cascaded anti-interference circuit suitable for an electrocardio monitoring device
ActiveCN120492801Bimprove signal-to-noise ratioSuppress power frequency interferenceMedical automated diagnosisFrequency selective two-port networksEcg signalNoise reduction
The embodiment of the application provides a cascade anti-interference circuit suitable for an electrocardio monitoring device, which comprises a sliding mean filter module, a notch filter module, a lifting wavelet decomposition module, a threshold calculation module, a threshold processing module and a lifting wavelet reconstruction module; while ensuring a small circuit scale, the ECG signal collected by the wearable electrocardio monitoring device is subjected to hierarchical noise reduction processing, and high signal-to-noise ratio ECG signal output is realized; for the ECG signal collected by the wearable electrocardio monitoring device, first, sliding mean filtering is performed to filter out baseline drift noise caused by human respiratory movement and other activities; the power frequency interference caused by the wired and wireless connection of the electromagnetic environment around the device is suppressed by using the notch filter module; finally, wavelet noise reduction is realized by using the lifting wavelet decomposition and reconstruction and threshold noise reduction method, the electromyographic interference caused by the autonomous or unconscious movement of the wearer is suppressed, and high signal-to-noise ratio ECG signal is output, which is used for physiological parameter extraction and electrocardio diagnosis.
Owner:WUHAN KANGNUOXIN SEMICON CO LTD
Electrocardiogram ventricular escape real-time judgment method and system
The invention discloses an electrocardiogram ventricular escape real-time judgment method and system, relates to the technical field of electrocardiograms, solves the problem of lack of multi-dimensional analysis and dynamic characteristic verification of electrocardiogram waveforms, and aims at solving the problem that a time period in which waveform abnormity really exists is focused through continuous analysis of fluctuation points of a to-be-recognized section, so that the accuracy of the electrocardiogram ventricular escape real-time judgment is improved. A symmetric space vector range of a normal P wave is used as a reference, whether a to-be-analyzed waveform contains the P wave is visually judged through matching of the form and the position of a to-be-verified vector, missed judgment caused by low amplitude of the P wave or overlapping of the P wave in a T wave is avoided, and the accuracy of the judgment is improved. A complete analysis chain from electrocardiosignals to clinical diagnosis is constructed through a four-layer logic architecture of pacing point positioning, feature waveform matching, abnormal time capturing and escape pacing mechanism verification, high-precision recognition of ventricular escape pacing is achieved, and the accuracy of ventricular escape pacing recognition is improved through deep fusion of a physiological mechanism and an algorithm. And an interpretable and traceable technical path is provided for automatic electrocardio diagnosis.
Owner:QUZHOU PEOPLES HOSPITAL (QUZHOU CENT HOSPITAL)
Methods and Systems for Evaluating Echo Data Contemporaneous with an Electrodiagnostic Study
PendingUS20260114847A1Ultrasonic/sonic/infrasonic diagnosticsInfrasonic diagnosticsReal time analysisUltrasonic imaging
Systems and methods for ultrasound imaging include obtaining RF data using an ultrasound probe and processing the RF data in-parallel to generate B-mode data and echo intensity data during ultrasound examination of a patient. The RF data is analyzed in real-time to provide a user with live ultrasound image and echogenicity analytics. Based on the echogenicity analytics, the user may reposition the ultrasonic probe to adjust and select an optimal probe angle to ensure reproducible results. Providing live RF data allows the user to assess the health of nerves and muscles in real-time and make dynamic decisions on further exams to perform during the same office visit.
Owner:CADWELL LAB INC
Quick connector with pipe on-off diagnosis function
This invention discloses a quick-connect coupling with pipeline continuity diagnostic function, relating to the field of quick-connect couplings. Key technical features include a quick-connect male coupling, a quick-connect female coupling, and a power-on diagnostic motion assembly. The power-on diagnostic motion assembly includes a movable post, a spring, and a conductive plate. The movable post comprises an embedded section, a middle section, and a connecting section connected in sequence. The conductive plate is sleeved on the connecting section and contacts the end face of the middle section. The spring is sleeved on the connecting section, with one end contacting the conductive plate and the other end contacting the inner wall of the end cap. This invention offers advantages such as improved conductive contact stability and ease of assembly.
Owner:SUZHOU ENDUFA AUTOMOTIVE SYST CO LTD
Electrocardio diagnosis method and system based on large language model
The invention provides an electrocardio diagnosis method and system based on a large language model, and the method comprises the steps: extracting a plurality of electrocardio features from a to-be-diagnosed electrocardio signal based on the knowledge of electrocardio diagnosis diseases; inputting the electrocardiosignal to be diagnosed into a preset electrocardiograph time sequence model for electrocardiograph waveform analysis to obtain a first diagnosis tag and a diagnosis probability corresponding to the first diagnosis tag; searching a historical electrocardiosignal similar to the electrocardiosignal to be diagnosed, and acquiring a second diagnosis tag corresponding to the historical electrocardiosignal and a corresponding similarity; generating an electrocardio diagnosis process prompt based on the electrocardio diagnosis process knowledge and a thinking chain technology; and taking each electrocardio feature, the first diagnosis tag, the diagnosis probability, the second diagnosis tag and the similarity as an electrocardio diagnosis context, and inputting the electrocardio diagnosis context, the electrocardio diagnosis knowledge and the electrocardio diagnosis process prompt into a preset large language model for diagnosis to obtain a diagnosis result output by the large language model. The purpose of improving the electrocardio diagnosis accuracy is achieved.
Owner:UNIV OF SCI & TECH OF CHINA
Calibration Device and Method for an Electrocardiogram Diagnosis and Analysis System
The present invention discloses a calibration device and method for an electrocardiogram diagnosis and analysis system, comprising: a central processing module, a power supply module, a human-computer communication module, a calibration module, a weak signal module and a communication module; the power supply module, the human-computer communication module and the calibration module are all connected to the central processing module; the central processing module is connected to an externally connected electrocardiogram diagnosis and analysis system through the weak signal module; the central processing module is respectively connected to an externally connected intelligent terminal device or an electrocardiogram diagnosis and analysis system through the communication module. The present invention realizes the automation of the calibration process through program design, eliminates problems such as low efficiency and manual errors caused by manual measurement in past calibrations, and greatly improves the calibration efficiency and accuracy of corresponding items; and has an anti-cheating algorithm module, which can prevent manufacturers of bad electrocardiogram diagnosis and analysis equipment from coping with calibration requirements through technical cheating.
Owner:李妙
An alzheimer's disease electroencephalogram diagnosis method based on coherence brain network and scale characteristics, electronic device and computer system
This invention relates to an EEG diagnostic method, electronic device, and computer system for Alzheimer's disease based on coherent brain networks and scale features. The method includes the following steps: S1: Acquire EEG data and extract features to calculate their coherence, using these as sample points to construct a connectivity matrix; S2: Add scale features to the GCN algorithm; use an MLP classifier combined with SHAP values to sort the scale features, selecting strongly correlated scale features as nodes to fill the graph structure; S3: Set thresholds based on the coherent brain network, visualize the brain functional connectivity map, and locate specific brain regions; S4: Classify based on the coherent connectivity matrix and strongly correlated scale features as feature vectors and labels; S5: Output the classification results. The advantages are: effectively using EEG signals as an auxiliary diagnostic tool for early diagnosis of Alzheimer's disease; overcoming the difficulties in diagnosing Alzheimer's disease in existing technologies, and possessing high value for widespread application.
Owner:SHANGHAI UNIV OF MEDICINE & HEALTH SCI +1
An electrocardiogram diagnosis method and device based on artificial rule enhanced neural network
The present invention discloses an electrocardiogram (ECG) diagnosis method based on an artificial rule-enhanced neural network, comprising the following steps: obtaining ECG signal training samples; constructing a training model comprising a deep learning module and a rule-based reasoning module; inputting the ECG signal training samples into the deep learning module to obtain a first abnormality prediction probability vector; inputting the ECG signal training samples into the rule-based reasoning module to obtain a second abnormality prediction probability vector for probabilistically predicting an ECG diagnostic label; fusing the vectors to obtain a final abnormality prediction probability vector for probabilistically predicting an ECG diagnostic label; inputting the ECG signal training samples into the training model; optimizing the training model parameters using a total loss function to obtain a multi-lead ECG signal diagnosis model; and, when applied, inputting the ECG signal into the multi-lead ECG signal diagnosis model to obtain a predicted probability of the ECG diagnostic label for the ECG signal. This method can accurately and quickly diagnose ECG signals.
Owner:海宁市产业技术研究院
Cascade anti-interference circuit suitable for electrocardiogram monitoring equipment
ActiveCN120492801AMedical automated diagnosisFrequency selective two-port networksNoise reductionElectromagnetic environment
The embodiment of the invention provides a cascade anti-interference circuit suitable for electrocardiogram monitoring equipment. The cascade anti-interference circuit comprises a sliding mean filtering module, a notch filtering module, a lifting wavelet decomposition module, a threshold calculation module, a threshold processing module and a lifting wavelet reconstruction module. While a small circuit scale is ensured, hierarchical noise reduction processing is carried out on ECG signals collected by wearable electrocardiogram monitoring equipment, and ECG signal output with a high signal-to-noise ratio is achieved. The method comprises the following steps: firstly, carrying out sliding mean filtering on an ECG signal collected by wearable ECG monitoring equipment, and filtering baseline drift noise caused by activities such as human respiratory movement and the like; a notch filtering module is used for inhibiting power frequency interference caused by wired and wireless connection of an electromagnetic environment around the equipment; and finally, wavelet noise reduction is realized by using a method for improving wavelet decomposition and reconstruction and threshold noise reduction, and myoelectricity interference caused by autonomous or unconscious movement of the wearer is inhibited, so that an ECG signal with a high signal-to-noise ratio is output and is used for physiological parameter extraction and electrocardio diagnosis.
Owner:WUHAN KANGNUOXIN SEMICON CO LTD
Perceptron-based EMG processor for neuropathy and myopathy diagnosis
The present invention provides a hardware-friendly framework for implementing a point-of-care diagnosis hardware tool for practical end-user convenience, power saving and resource utilization. The hardware tool is non-invasive and comfortable for the patient, as a primary means of differential diagnosis between two neuromuscular diseases such as neuropathy and myopathy. The provided hard-ware tool comprises a feature extractor configured to receive electrodiagnostic signals (preferably EMG signals) of a patient and extract one or more features from the collected signals; and a classifier configured to receive the extracted features and classify a neuromuscular disease for the patient based on the extracted features. The classifier is a single layer machine-learning perceptron trained with datasets consisted of electrodiagnostic signals of patients to perform a linearly separable binary classification.
Owner:CITY UNIVERSITY OF HONG KONG
Electrocardio diagnosis method, model training method and device
The invention provides an electrocardio diagnosis method and device and a model training method and device, and relates to the field of artificial intelligence and medical diagnosis. The electrocardio diagnosis method comprises the steps that original features, local morphological features and global dependency features are extracted from electrocardio data of a target object, the original features, the global dependency features and the local morphological features are fused, and electrocardio fusion features are obtained; metadata features are extracted from metadata of the target object, the metadata features and the electrocardio fusion features are mutually modulated, and enhanced metadata features and enhanced electrocardio fusion features are obtained; on the basis of the enhanced metadata features and the enhanced electrocardio fusion features, the disease category of the target object is predicted, and a diagnosis result is obtained.
Owner:AEROSPACE INFORMATION RES INST CAS
Channel attention based anti-photoelectric isolation noise electrocardio monitoring system and method
The application discloses an anti-opto-isolated noise electrocardiogram monitoring system and method based on channel attention. The system comprises an opto-isolated acquisition module, a data preprocessing module, a data enhancement module, an intelligent processing module and a diagnosis output module. The method is as follows: first, an intelligent processing module is constructed, including a fractional Fourier transform layer and a one-dimensional convolutional neural network, and the one-dimensional convolutional neural network is trained using a data set; then, multi-lead electrocardiogram signals are collected through the opto-isolated acquisition module, the collected signals are preprocessed through adaptive length alignment and standardization, and the collected signals are data enhanced using an opto-spreading noise model; then, the enhanced signals are input into the intelligent processing module for feature extraction; finally, based on the extracted features, an electrocardiogram diagnosis result is output. The application improves the accuracy and robustness of electrocardiogram diagnosis in a real noise environment while ensuring electrical safety, and improves the diagnosis efficiency of cardiovascular diseases.
Owner:NANJING UNIV OF SCI & TECH
Method and system for automatically generating dynamic electrocardiogram diagnosis report
The invention belongs to the technical field of electrocardiogram and data processing, and discloses a method and system for automatically generating a dynamic electrocardiogram diagnosis report. The system receives an external detection result and maps the external detection result into a model-independent intermediate representation, constructs an event association graph (EAG) to describe association between events and global parameters, and applies a clinical relationship consistency rule. Compiling the EAG and the parameters into a grammar constraint specification of an entries conclusion line, and generating a first draft of the diagnosis report conclusion line by the LLM under the specification; then performing automatic auditing and local repairing on illusion sentences, logic conflicts, evidence-free sentences and term misuse through consistency judgment and sentence-level correction; and then providing context association for each conclusion, and outputting a clinical consistency score. According to the method, on the premise of not depending on upstream model details, cross-device / cross-supplier integration is achieved, report logic conflicts are remarkably reduced, and context verifiability is improved.
Owner:CHONGQING KOANRULER SCI TECH CO LTD
Electrocardio diagnosis system and device, storage medium and program product
The invention provides an electrocardio diagnosis system and device, a storage medium and a program product. The system comprises an electrocardio data acquisition device; the diagnosis terminal equipment is used for realizing the following functions: an AI diagnosis module used for performing AI diagnosis on a to-be-diagnosed person according to the acquired electrocardiogram data and outputting an acquired quality analysis conclusion, a disease diagnosis conclusion and corresponding two-dimensional basic confidence; the dynamic confidence coefficient calculation module is used for determining the dynamic confidence coefficient matched with the current scene according to the output of the AI diagnosis module; and the flow control module is used for comparing the dynamic confidence coefficient with a confidence coefficient threshold value preset for the current scene by each processing flow, and triggering the corresponding processing flow when the dynamic confidence coefficient is greater than or equal to the confidence coefficient threshold value preset for the current scene. By means of the technical scheme, the dynamic confidence coefficient and the confidence coefficient threshold value based on clinical scene adaptation are achieved, the accuracy of the AI diagnosis result and the processing timeliness and efficiency are improved, and the false positive rate is reduced.
Owner:纳龙健康科技股份有限公司
Multimodal electrocardiogram diagnosis large model architecture and training method
This invention discloses a multimodal ECG diagnostic large-scale model architecture, belonging to the field of machine learning technology, to solve the problem of inaccurate text-image understanding of existing ECG data. The architecture includes: an ECG encoder, an image encoder, a feature alignment module, and a large-scale language model. The ECG encoder encodes the input ECG time-series signal into a first feature representation; the image encoder encodes the input ECG image into a second feature representation; and the feature alignment module connects the ECG encoder and the image encoder. This invention uses contrastive learning to enable the model to understand the relationship between signals and text, ensuring the medical accuracy of the generated content.
Owner:HANGZHOU MINGXIN MEDICAL ARTIFICIAL INTELLIGENCE TECHNOLOGY CO LTD