33 results about "Electrocardiographic waveform" patented technology

A system for real-time prediction of heart disease and to support clinical decisions; the system includes: a patient data acquisition module configured to receive multimodal inputs, including physiological signals selected from electrocardiographic waveforms, blood pressure readings, heart rate readings, and oxygen saturation readings, as well as demographic and lifestyle information, including age, gender, cholesterol levels, smoking habits, and family medical history; a preprocessing engine configured to perform data cleansing, imputation of missing values, categorical coding, and feature scaling, so that the input data is normalized and converted into a format suitable for machine learning; a processing core comprising a multi-core CPU / GPU system-on-chip operationally coupled with a secure storage unit, wherein the processing core is configured to execute a variety of pre-trained machine learning models, including Naive Bayes, Random Forest, Logistic Regression and Decision Tree classifiers; a model evaluation unit configured to calculate validation metrics such as precision, recall, F1 score and area under the curve for each of the models and dynamically select the model with optimal performance to generate real-time predictions for the risk of heart disease; a display interface configured to present predictive results in the form of risk probability values, confidence indices, and actionable recommendations that are mapped to clinical treatment guidelines; and a communication interface configured to transmit emergency alerts based on high-risk predictions to remote caregivers, hospitals, and emergency response systems via wireless communication protocols such as WLAN, Bluetooth, and 4G / 5G cellular connections.

A method includes classifying, using a machine learning model, a portion of an electrocardiogram measurement as an artifact. The method further includes normalizing the electrocardiogram measurement except the portion of the electrocardiogram measurement classified as the artifact. The method further includes applying the machine learning model to the normalized electrocardiogram measurement to detect a cardiac event.

The application discloses an ambulance electrocardiogram data transmission method, device, equipment, medium and product, and belongs to the technical field of medical data remote transmission. The method comprises the following steps: an industrial computer in the ambulance receives vital sign monitoring data from a vital sign monitor; the vital sign monitoring data is converted into an electrocardiogram waveform, and the electrocardiogram waveform is converted into coordinate values for storage; an arrhythmia part in the electrocardiogram waveform is identified; in the case that a network state is normal, the converted coordinate values of the electrocardiogram waveform are sent to a cloud server, and the cloud server is used for sending the received electrocardiogram waveform coordinate values to a hospital client; in the case that the network state is abnormal, the coordinate values corresponding to the arrhythmia part in the electrocardiogram waveform are graded and cached and are transmitted in a delayed manner. The method can improve the transmission efficiency of electrocardiogram data and ensure the integrity of the electrocardiogram data in the case that the network state is abnormal.

A measuring device for biological information, which is used by attaching it to an arm section of a human body and which is capable of measuring at least one electrocardiographic waveform, includes an electrode element including a shaft section on which screw processing is carried out and a head section, wherein the head section of the electrode element is fixed in a state in which it is in contact with an outer surface of a main body housing, the shaft section is joined with a sensor substrate in the main body housing and is electrically connected to the sensor substrate, and thus the positioning of the sensor substrate in the main body housing and the fixing and electrical connection of the electrode and the sensor substrate can be carried out together.

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.

The invention discloses a method and system for rapidly measuring electrocardiogram and pulse blood oxygen saturation, and relates to the technical field of medical detection equipment. According to the method for rapidly measuring the electrocardiogram and the pulse blood oxygen saturation degree, on the basis of a set time period, preset transmission light signal time sequence data of a first to-be-measured part and preset electrocardiosignal time sequence data between a second to-be-measured part and the first to-be-measured part are synchronously collected; performing optical filtering and amplitude adjustment processing on the transmission light signal time sequence data, and performing analysis based on a preset blood oxygen saturation analysis algorithm to obtain a pulse blood oxygen saturation value; the method comprises the following steps of: performing enhanced filtering and de-noising processing on electrocardiosignal time sequence data to generate an electrocardiogram waveform, extracting a QRS wave group from the electrocardiogram waveform, calculating a heart rate based on the QRS wave group, and displaying and outputting the heart rate. And the operation process is greatly simplified.

The invention relates to the technical field of signal processing, and discloses a high-frequency electrocardiosignal harmonic interference filtering method, device and equipment and a medium, and the method comprises the steps: obtaining object information of a target object and an initial electrocardiosignal under a target lead; determining the initial spectrum intensity of the preset frequency point; determining a target group of the target object; based on the target group reference intensity value of the target group, determining a lead reference value, corresponding to the preset frequency point, of the target object under the target lead; based on the initial spectrum intensity corresponding to the preset frequency point and the lead reference value, whether harmonic interference exists in the initial electrocardiosignal or not is judged; and the electrocardiosignals with harmonic interference are filtered out. By accurately identifying and filtering high-frequency harmonic interference, useful high-frequency details are reserved as far as possible under the condition that the harmonic interference is filtered, the authenticity and effectiveness of electrocardiogram signals are guaranteed, doctors can make more accurate diagnosis, and misjudgment of interference signals on electrocardiogram waveforms is avoided.

Physiological monitoring can be provided through a lightweight wearable monitor that includes two components, a flexible extended wear electrode patch and a reusable monitor recorder that removably snaps into a receptacle on the electrode patch. The wearable monitor sits centrally on the patient's chest along the sternum oriented top-to-bottom. The placement of the wearable monitor in a location at the sternal midline, with its unique narrow “hourglass”-like shape, significantly improves the ability of the wearable monitor to cutaneously sense cardiac electrical potential signals, particularly the P-wave and the QRS interval signals indicating ventricular activity in the ECG waveforms. In particular, the ECG electrodes on the electrode patch are tailored to be positioned axially along the midline of the sternum for capturing action potential propagation in an orientation that corresponds to the aVF lead used in a conventional 12-lead ECG that is used to sense positive or upright P-waves.

A defibrillator for customizing cardiac therapy treatment of a patient while a responder is administering cardiopulmonary resuscitation (CPR) to the patient's heart. During operation, the defibrillator monitors an electrocardiogram (ECG) waveform of the patient's heart while the responder is administering CPR to the patient's heart. When the ECG waveform monitored by the defibrillator while the responder is administering CPR to the patient's heart indicates a shockable rhythm of the patient's heart, the defibrillator derives a treatment advisory from the quality of the CPR administered to the patient's heart by the responder, the vitality of the shockable rhythm of the patient's heart, and optionally other factors.

An electrocardiographic waveform measurement device includes a plurality of electrodes configured to measure an electrocardiographic waveform of a measurement target, a vibration detection unit configured to approach a chest region of the measurement target to detect vibration based on a beat of a heart of the measurement target, and a control unit configured to execute measurement processing for the electrocardiographic waveform. The control unit further executes lead type determination processing for determining, based on a detection result from the vibration detection unit, at least whether the electrocardiographic waveform measured by the measurement processing is an electrocardiographic waveform obtained by chest lead measurement.

The utility model relates to a kind of electrocardiograph monitoring equipment, belong to electrocardiograph monitoring technical field, this electrocardiograph monitoring equipment includes: front-end signal processing circuit, for the filtered processing of input lead signal, obtain filtered lead signal;Lead signal includes 3 lead signal or 5 lead signal;Drive signal processing circuit, for selecting drive signal in filtered lead signal based on the waveform to be displayed and selecting drive lead in lead;Drive lead and drive signal are used to eliminate common-mode interference signal;Collector, for collecting lead signal after eliminating common-mode interference signal, generate electrocardiogram waveform.The utility model is built using discrete circuit to realize simultaneously supporting 5 lead and 3 lead electrocardiograph acquisition, can select different price and performance discrete component to build electrocardiograph monitoring system according to actual demand, optimize cost, while discrete circuit can be customized according to specific application requirement Design, function extension is more convenient, improve flexibility.

An electrocardiogram (ECG) measurement method with reduced power consumption for displaying a six-lead ECG waveform using a portable apparatus and a smartphone is disclosed. The apparatus includes three electrodes configured to contact both hands and a left leg of a user, two contact detectors configured to detect a contact status of the user, and a microcontroller. Upon detecting simultaneous contact on all three electrodes, the microcontroller transitions from a low-power mode to an active mode, activating two amplifiers and a constant voltage generator to acquire two ECG signals. The two ECG signals are converted into two digital lead signals and wirelessly transmitted to the smartphone. The smartphone generates four additional derived lead signals and displays a six-lead ECG waveform based on the two received signals.

The invention provides an electrocardiogram detection method and device based on a magnetoresistive sensor. The electrocardiogram detection method based on the magnetoresistive sensor comprises the following steps: arranging a magnetic marker in a pre-cardiac region body surface preset region of a detected object; a magnetoresistive sensor array is arranged at a preset distance of a precardiac region of a measured object, and magnetoresistive sensor signals including ballistocardiogram signals and noise signals are collected in real time through magnetic field coupling between the magnetoresistive sensor array and a magnetic marker; preprocessing the magnetoresistive sensor signal, and extracting a ballistocardiogram signal from the preprocessed magnetoresistive sensor signal; and inputting the ballistocardiogram signal into the reconstruction model to output an electrocardiogram waveform. By collecting ballistocardiogram signals in real time and converting the ballistocardiogram signals into electrocardiogram signals through a model algorithm, the accuracy and stability of measurement are improved, and the method is suitable for early prevention and long-term monitoring of cardiovascular diseases.

The article to this design is a biometric information measuring device that is installed in a bathtub, as shown in Reference Figure 3, which shows the state of use. When in use, the device measures the bather's biometric information, such as heart rate and electrocardiogram waveform, while immersed in hot water. This information is then transmitted to a water heater remote controller, a mobile information terminal, etc. When not in use, the device can be charged wirelessly by placing it on a charger, as shown in Reference Figures 1 and 2, which show the state of use.

The application relates to the field of medical education, and particularly discloses a waveform stereoscopic electrocardiogram teaching demonstration device and method, which comprises a data processing unit and a physical teaching aid; the data processing unit receives two-dimensional electrocardiogram waveform data and converts the two-dimensional electrocardiogram waveform data into a three-dimensional digital model through a three-dimensional modeling algorithm; the physical teaching aid is integrally formed through 3D printing based on the model, the configuration of the physical teaching aid maps the voltage amplitude to the height and maps the time axis to the length, so that the waveform becomes a three-dimensional structure which can be observed and touched; the method comprises the following steps: acquiring electrocardiogram waveform data, performing three-dimensional coordinate mapping and model generation, and finally applying the physical teaching aid to teaching demonstration after the physical teaching aid is manufactured through color 3D printing after structure optimization; the abstract electrocardiogram waveform is converted into an intuitive three-dimensional entity, the multi-sensory teaching mode combining vision and touch is used, and the intuitiveness, contrast and memory depth of electrocardiogram morphology learning are significantly improved.

To increase a withstand voltage between a biological information measuring electrode and a charging terminal without increasing a biological information measurement device in size. A biological information measurement device includes: an electrocardiogram measuring unit configured to measure an electrocardiograph waveform of a subject and including an electrode; a body portion including a bottom portion configured to face and contact an arm portion of the subject in an attachment state; a charging terminal that receives power for charging; and an insulating member configured to separate the charging terminal from the electrode.

A mode adaptive coefficient filter system for a physiological patent monitoring (“PPM”) method and apparatus provides an electrocardiogram (“ECG”) display function with an improved resolution of artifact issues when large baseline offsets occur to input signals. In one aspect of the disclosure the method and system provide an ECG monitoring and display function using the mode adaptive coefficient filter system for an active filter process provides for an improved ECG artifact resolution minimizing discontinuous wave forms when applied to an input signal that achieves improved signal quality and reduced latency in signal rendering. The method may be utilized for both infinite impulse response (“IIR”) and finite impulse response (“FIR”) systems with similar filter structures.

In some embodiments, there is provided system for processing electrocardiogram waveforms. The system may include at least one processor and at least one memory including instructions, which when executed by the at least one processor causes operations including receiving a segmented electrocardiogram waveform, wherein the segmented electrocardiogram waveform is for a heartbeat epoch; determining, for the segmented electrocardiogram waveform, initial estimates for mean, height, and standard deviation for a Gaussian curve; determining, for the initial estimates, upper bounds and lower bounds; fitting, using the initial estimates, the upper bounds, and the lower bounds, the Gaussian curve to the segmented electrocardiogram waveform; and determining, using the fitted Gaussian curve, one or more parameters and / or waveform shape parameters to enable application of a treatment. Related systems, methods, and articles of manufacture are also disclosed.

Introduced here approaches to developing, training, and implementing algorithms to cardiac dysfunction through automated analysis of physiological data. As an example, a model may be developed and then trained to quantify left and right ventricular dysfunction using electrocardiogram waveform data that is associated with a population of individuals who are diverse in terms of age, gender, ethnicity, socioeconomic status, and the like. This approach to training allows the model to predict the presence of left and right ventricular dysfunction in a diverse population. Also introduced here is a regression framework for predicting numeric values of left ventricular ejection fraction.

To provide a defibrillator capable of clearly notifying a period corresponding to an operation mode.SOLUTION: The defibrillator includes a display processing section which displays an electrocardiographic waveform of a patient on a displaying section, a setting section which can individually set a color of the electrocardiographic waveform to be displayed on the displaying section corresponding to a plurality of operation modes, and a changing section which sets a period set to a first mode included in the plurality of operation modes as a first period, sets a period set to a second mode included in the plurality of operation modes as a second period, and sets the color of the electrocardiographic waveform displayed during the first period and the color of the electrocardiographic waveform displayed during the second period to different colors.SELECTED DRAWING: Figure 3A

The invention provides a medication response electrocardiogram generation system and method based on a multi-modal condition control diffusion model, and the system comprises a data collection and preprocessing module, a feature extraction module, a multi-time-point condition control diffusion model construction module, and a model training and prediction module. Through the multi-lead electrocardiogram before and after drug combination, drug information and patient individual information, with ControlNet as a basic framework, a structure control sub-module and a multi-modal condition sub-module are introduced to construct a multi-time-point condition control diffusion model, and the multi-lead electrocardiogram after multi-time-point drug use is predicted. The device can accurately simulate and generate the electrocardiogram waveform of the patient after medication under the intervention of a specific drug, not only can reflect the subtle difference of the drug action on the cardiac electrophysiological activities of different patients, but also can provide a richer and more visual basis for evaluating the drug electrophysiological effect clinically in a full-waveform and multi-lead manner; and individualization and scientificity of drug risk prediction are improved.

The present disclosure provides a magnetoresistive sensor-based electrocardiogram detection method and device. The magnetoresistive sensor-based electrocardiogram detection method comprises: setting a magnetic marker on a predetermined region of the precordial region of the measured object; setting a magnetoresistive sensor array at a predetermined distance of the precordial region of the measured object, and collecting magnetoresistive sensor signals containing ballistocardiogram signals and noise signals in real time through the magnetic field coupling between the magnetoresistive sensor array and the magnetic marker; preprocessing the magnetoresistive sensor signals, and extracting the ballistocardiogram signals from the preprocessed magnetoresistive sensor signals; and inputting the ballistocardiogram signals into a reconstruction model to output electrocardiogram waveforms. The method of collecting ballistocardiogram signals in real time and converting the ballistocardiogram signals into electrocardiogram signals through a model algorithm improves the accuracy and stability of the measurement, and is suitable for early prevention and long-term monitoring of cardiovascular diseases.

A method of assessing a likelihood of a patient having a pulmonary embolism (PE) comprises receiving discrete patient data, including patient-related clinical and demographic data pertinent to the patient, receiving electrocardiograph (ECG) waveform data obtained from examination of the patient, processing both the received discrete patient data and received set of ECG waveform data using a supervised deep learning multimodal fusion model that has been trained using analogous input training data including both discrete patient data and ECG waveform data to obtain an optimal match to results from corresponding patient computed tomography pulmonary angiograms (CTPA), indicative of a presence or absence of a pulmonary embolism, and outputting a measure of the likelihood of the patient having a pulmonary embolism.

In a main body of an upper-arm type sphygmomanometer that measures blood pressure of a subject by using a bag-shaped arm cuff to be wound around an arm of the subject, a main body housing includes an upper surface, and a first side surface and a second side surface on left and right sides. The first side surface includes a first side surface electrode region, the second side surface includes a second side surface electrode region, the upper surface includes a first upper surface electrode region, a first electrocardiogram waveform measurement electrode is provided in the first side surface electrode region, a second electrocardiogram waveform measurement electrode is provided in the second side surface electrode region, and a first reference electrode is provided in the first upper surface electrode region.

Increasing the breakdown voltage between a biological information measuring electrode and a charging port without increasing the dimensions of a biological information measuring device. A biological information measuring device comprises: an electrocardiogram measuring unit configured to measure an electrocardiographic waveform of a subject and including an electrode; a body section including a base section configured to face and contact an arm section of the subject in a restraint state; a charging port receiving current for charging; and an insulating element configured to isolate the charging port from the electrode.

Systems, methods, apparatuses, and computer program products for reconstructing electrocardiogram (ECG) waveforms from photoplethysmogram (PPG) signals using dictionary learning and deep learning for continuous monitoring and analytics. A method may include obtaining an electrical signal of a heart. The method may also include obtaining a circulatory signal related to a pulsatile volume of blood in tissue. The method may further include preprocessing the electrical signal and the circulatory signal. In addition, the method may include learning a mapping from at least one of the preprocessed electrical signal and the preprocessed circulatory signal. Further, the method may include training a model using the mapping. The method may also include deriving cardiovascular data based on the trained model.

The invention provides a non-contact physiological signal waveform reconstruction method and system based on a millimeter wave radar. The method comprises the following steps: preprocessing an acquired original radar signal into a mixed physiological signal containing a pulse wave signal, a heart rate signal and a respiration signal; performing short-time Fourier transform on the mixed physiological information to obtain an input feature map, and extracting a high-level semantic feature map from the input feature map through an encoder; separating each independent physiological signal feature map from the high-level semantic feature map through a separator; a corresponding physiological signal waveform is reconstructed through an independent decoder corresponding to each physiological signal according to an independent physiological signal feature map and a high-level semantic feature map, a blood pressure decoder adopts a structural design symmetrical to a heart rate decoder and a respiration decoder, and the blood pressure decoder adopts a structural design symmetrical to the heart rate decoder and the respiration decoder; and the blood pressure decoder completes the reconstruction of the blood pressure waveform according to the analysis of the pulse wave signal. The continuous blood pressure waveform, the electrocardiogram waveform and the respiration waveform are jointly reconstructed through the millimeter wave radar.

The invention relates to the technical field of medical instruments, in particular to an integrated hemodialysis and electrocardiograph monitoring all-in-one machine and a using method thereof.The integrated hemodialysis and electrocardiograph monitoring all-in-one machine comprises a machine body, a display screen and a controller are embedded in the machine body, and the machine body internally comprises a monitoring cavity, a dialysis cavity and an auxiliary cavity; an electrocardiogram monitoring module is arranged in the monitoring cavity, the electrocardiogram monitoring module is electrically connected with the controller, and an electrocardiogram signal collecting unit used for collecting electrocardiogram waveform signals of a patient is arranged in the monitoring cavity; a motor and a pipeline system used for blood extracorporeal circulation are arranged in the dialysis cavity, the motor is electrically connected with the controller, a control assembly used for controlling the blood flow speed during dialysis is arranged on the motor, and a power supply module is arranged in the auxiliary cavity. The electrocardiogram monitoring module is embedded into the hemodialysis machine body, the occupied space and the manufacturing cost are reduced, meanwhile, the pressure of the blood pressure cuff is controlled through the flow change of the blood pump, and the accuracy of blood pressure measurement is improved.

The application discloses a paper electrocardiogram voltage value reconstruction method and system based on a dynamic diffusion threshold, and belongs to the technical field of electrocardioanalysis. The method comprises the following steps: obtaining a standard paper electrocardiogram and a paper electrocardiogram to be processed, and extracting paper electrocardiogram parameters; based on a preset threshold, an optimal threshold is obtained through iterative optimization to perform binary processing on the paper electrocardiogram to be processed, and a binary paper electrocardiogram is obtained; the position of an electrocardio waveform lead is located; electrocardio waveform information in a lead image area is converted into a digital signal; the obtained digital signal is converted into a voltage signal; the voltage signal is resampled, and a digital reconstructed electrocardio signal is obtained. Compared with the prior art, the method has the advantages that the threshold of image processing can be dynamically adjusted according to the local features of the paper electrocardiogram, the edges of the electrocardiogram waveform are clearer in the digitalization process, and the digitalized data can accurately reflect the original information of the paper electrocardiogram.