58 results about "Electrocardiographic waveform" patented technology

The invention discloses an electrocardiogram waveform real-time anomaly detection and early warning evaluation method and system, and the method comprises the following steps: S1, collecting the signal data of an electrocardiogram, and carrying out the preprocessing; s2, inputting the electrocardiogram segment sequence into an improved convolutional neural network, and performing feature extraction and aggregation; s3, inputting the fusion feature sequence into a graph attention neural network, and extracting a relation between waveform local dependence and fragment state transition; s4, inputting the global feature map into an anomaly evaluation network, and outputting an anomaly judgment result and a confidence score sequence; s5, generating a risk level tag sequence in combination with the individual parameters; s6, inputting the risk level label sequence into an early warning decision network, and generating a multi-level response label and an alarm trigger signal; and S7, controlling an early warning interface to execute alarm, and synchronously writing related data. According to the invention, real-time anomaly detection and multi-stage early warning response of the electrocardiogram waveform are realized, and the timeliness and reliability of abnormal heart rhythm recognition are improved.

The invention discloses a paper electrocardiogram voltage value reconstruction method and system based on a dynamic diffusion threshold value, and belongs to the technical field of electrocardiogram analysis. Comprising the following steps: acquiring a standard paper electrocardiogram and a to-be-processed paper electrocardiogram, and extracting paper electrocardiogram parameters; based on a preset threshold value, carrying out iterative optimization to obtain an optimal threshold value so as to carry out binarization processing on the to-be-processed paper electrocardiogram to obtain a binarized paper electrocardiogram; the positioning of the electrocardiogram waveform lead position is realized; the electrocardio waveform information of the lead image area is converted into a digital signal; converting the obtained digital signal into a voltage signal; and resampling the voltage signal to obtain a digitalized reconstructed electrocardiosignal. Compared with the prior art, the method has the advantages that the image processing threshold value can be dynamically adjusted according to the local features of the paper electrocardiogram, so that the edge of the electrocardiogram waveform in the digitization process is clearer, and it is ensured that the digitization data can accurately reflect the original information of the paper electrocardiogram.

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 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.

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 present disclosure presents arrhythmia analysis systems and methods. One such method comprises processing an acquired ECG waveform signal to remove noise artifacts and form a denoised ECG waveform signal; processing the denoised ECG waveform signal to remove low quality segments and form a high quality ECG waveform signal; analyzing the high quality ECG waveform to detect a presence of a beat-independent ventricular arrhythmia; processing the denoised ECG signal to extract beat (R-peak) locations corresponding to QRS complexes from the denoised ECG signal; analyzing the denoised ECG signal to detect a presence of a beat-dependent ventricular arrhythmia based on the extracted beat (R-peak) locations; analyzing the denoised ECG signal to detect a presence of one or more supraventricular arrhythmias based on the extracted beat locations of the ECG signal; and outputting a report containing one or more arrhythmias detected by the analyzing steps. Other methods / systems are also provided.

The invention discloses an electrocardiogram waveform prediction device, a computer program product, equipment and a medium, and relates to the technical field of data processing, and the electrocardiogram waveform prediction device comprises an information collector which is used for collecting basic information, heart information, body surface electrocardiogram signals and electrolyte information of a target object; the signal processor is connected with the information collector and is used for carrying out electrocardio nonlinear fitting through the basic information, the heart information, the body surface electrocardio signals and the electrolyte information to obtain an in-vivo target electrocardiogram waveform of a target object when the PICC tip reaches a target position; and the display is connected with the information collector and the signal processor and is used for displaying the body surface electrocardiosignal and the in-vivo target electrocardiogram waveform. After the signal processor is used for carrying out electrocardio nonlinear fitting, the in-vivo target electrocardiogram waveform of the target object when the PICC tip reaches the target position can be obtained, the in-vivo target electrocardiogram waveform is made to be matched with the target object, and accurate prediction of the electrocardiogram waveform in PICC catheterization is achieved.

The present invention increases the withstand voltage between a biological information measurement electrode and a charging terminal without increasing the size of a biological information measurement device. This biological information measurement device comprises: an electrocardiographic measurement means including an electrode for measuring an electrocardiographic waveform of a person to be measured; a main body part including a bottom portion positioned on a side that comes into contact with an arm part of the person to be measured when the device is worn; a charging terminal to which power for charging is input; and an insulating member separating the charging terminal and the electrode.

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.

An electrocardiographic detection device according to the present invention includes a power supply unit that applies alternating-current power of a preset frequency to a rider that is a subject that is riding in a moving body, a pair of sensor electrodes that are provided so as to be opposite each other at two positions in the moving body that sandwich the heart of the rider and can each be electrically contacted by the rider, a detection unit that detects the voltage at each of the pair of sensor electrodes and also detects a voltage signal that represents an electrocardiographic waveform for the rider from the detected voltage, a determination unit that uses the voltage at the frequency of the alternating-current power as obtained from the voltage at each of the pair of sensor electrodes to determine whether the rider is contacting each of the pair of sensor electrodes, and an output unit that outputs the voltage signal that represents the electrocardiographic waveform for the rider when it has been determined that the rider is contacting each of the pair of sensor electrodes.

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.

Systems, methods, and devices involve receiving a package of data that includes an electrocardiogram (ECG) waveform associated with a potential cardiac event, processing the ECG waveform to extract interval data associated with the potential cardiac event, inputting the ECG waveform and the interval data into a trained machine learning model, and determining, by the trained machine learning model, that the potential cardiac event comprises a normal rhythm.

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.

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.

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.

An electrocardiographic waveform-based adaptive pulse ablatograph includes at least two electrodes configured to transmit an ablation pulse to a tissue during use; a pulse waveform generator coupled to the electrodes and configured to transmit a nanosecond pulse having a voltage of 15 kv-35 kv to the electrodes; an electrocardiographic detection device configured to collect an electrocardiographic waveform signal; and a control device in signal connection to the electrocardiographic detection device and in control connection to the pulse waveform generator. By controlling duration of pulse release and the magnitude of pulse energy of the pulse waveform generator and the electrodes in the effective refractory period, the control device makes dynamic adjustment quickly according to a real-time heartbeat of a patient, thus increasing the proportion of the pulse release duration in the effective refractory period and improving the safety.

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.

This biological information measurement device is used while worn on a human body. The biological information measurement device comprises at least a first electrode and a second electrode, and is configured to be capable of measuring an electrocardiographic waveform based on the potential difference between the first electrode and the second electrode. The biological information measurement device comprises: a body housing including a side surface formed of a conductive material and functioning as the first electrode, a bottom surface on which the second electrode is disposed and that comes into contact with the human body when the biological information measurement device is worn, and a top surface located opposite the bottom surface; an electrocardiographic signal detection circuit for detecting signals related to potentials of the first electrode and the second electrode; a first electric path that conducts the first electrode and the electrocardiographic signal detection circuit; and a second electric path on which an electrostatic discharge protection element is mounted, and that couples the first electrode and the second electrode via the electrostatic discharge protection element.

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 application discloses a kind of atrioventricular node double-path supraventricular tachycardia demonstration model of heart arrhythmia model technical field, including base, lamp ring, lamp bead, ventricular model and atrial model;The base is the base of stable support, controller and display screen are arranged on the base;Ventricular model and atrial model are fixed on the base, the ventricular model is directly below the atrial model, the electrocardiogram physiological mechanism of atrioventricular node double-path supraventricular tachycardia has been complex and abstruse content in arrhythmia teaching, it is difficult to understand.By the demonstration of the model, the abnormal electrocardio conduction path of the double-path mechanism of atrioventricular node supraventricular tachycardia can be directly displayed;And each kind of conduction mode is matched with electrocardiogram waveform by display screen display, so that students can more easily understand disease mechanism and process, promote understanding corresponding electrocardiogram, teaching is more vivid and intuitive.

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.

To make it possible to accurately determine a highly reliable part of an electrocardiographic waveform.SOLUTION: A first determination unit 34 of a steering ECU 30 performs first filter processing that applies a band-pass filter of a first frequency band to an electrocardiographic waveform, and performs a first determination that determines whether a sum of absolute values of a first waveform that has undergone the first filter processing is smaller than a threshold TH1_2. A second determination unit 36 performs second filter processing that applies a band-pass filter of a second frequency band different from the first frequency band to the electrocardiographic waveform, and performs a second determination that determines whether a sum of absolute values of a second waveform that has undergone the second filter processing is smaller than a threshold TH2_2. Then, a third determination unit 38 determines a part of the electrocardiographic waveform, for which the first determination and the second determination are affirmative, as a specific part with high reliability.SELECTED DRAWING: Figure 3

A computer-implemented method to determine peak oxygen consumption ({dot over (V)}O2 PEAK) from electrocardiogram (ECG) waveform data includes the steps of recording, by at least one first computing device, an electrocardiogram (ECG) waveform data of a subject; transmitting, by the at least one first computing device, the ECG waveform data, to at least one second computing device communicatively coupled to the at least one first computing device; determining, by the at least one second computing device, a {dot over (V)}O2 PEAK of the subject using a convolutional neural network; and transferring, by the at least one second computing device, the {dot over (V)}O2 PEAK to the first computing device associated or a device associated with the subject.

A control method for an intracardiac defibrillation catheter system is provided for performing a safer treatment by shortening the time between switching the mode to perform defibrillation and synchronization with R wave. The system includes a catheter, electrode part, power supply, input part inputting an electrocardiogram, and changeover part connected to the power supply, for switching between a first mode and second mode for electrically disconnecting and connecting the power supply and electrode part, which is connected to the power supply via the changeover part. The method includes switching the first mode to second mode with the changeover part when a cardiac potential reaches a peak of P wave and / or Q wave obtained from an electrocardiographic waveform of the electrocardiogram, and applying a voltage to the electrode part with the power supply when the cardiac potential reaches a peak of R wave obtained from the electrocardiographic waveform of the electrocardiogram.

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 present application relates to a kind of digital electrocardiogram waveform identification and time limit parameter measurement method, the present application selectively according to the signal type of the need to retain one or more of these interference signals and part electrocardio feature signal is decomposed to obtain the feature signal of the layer needed to retain, again by the selective superposition integration of each layer effective signal and feature signal, join the method for identifying J point, QRS wave, P wave, T wave, retain the effective signal data of 3 wave bands finally for doctor auxiliary diagnosis in each layer, then join positioning method is used to realize the accurate positioning of the start point and end point position of PR interval, QT interval, QRS time limit, then the corresponding effective value is determined in conjunction with the amplitude of each wave band, finally join the algorithm for the calculation of heart rate to realize the calculation of heart rate.The present application can shorten the effective time of doctor to view electrocardiogram, improve the efficiency of doctor to read electrocardiogram, reduce the misdiagnosis rate caused by long time reading.