39 results about "12 lead electrocardiogram" patented technology

The invention discloses an automatic electrocardiogram recognition system. The system comprises an electrocardiogram acquisition device, a wireless/wired network transmission module, an electrocardiogram collection and time domain feature recognizer, an electrocardiogram dominant wave interphase recognizer, an electrocardiogram QRS wave group similarity recognizer and an electrocardiogram queuing recognizer, the electrocardiogram acquisition device inputs acquired data to the electrocardiogram collection and time domain feature recognizer via the transmission module, the electrocardiogram collection and time domain feature recognizer recognizes to obtain positions of peak points of P waves, QRS waves and T waves on a 12-lead, the electrocardiogram dominant wave interphase recognizer recognizes heart rate to obtain normal and abnormal results of the heart rate, the electrocardiogram QRS wave group similarity recognizer recognizes whether an electrocardiogram probably has premature beat or not, and the electrocardiogram queuing recognizer sequences and outputs. The system performs real-time computer-aided analysis of clinically acquired 12-lead electrocardiograms to automatically recognize arrhythmia and premature beat electrocardiograms, and accordingly efficiency of electrocardiogram analysis is improved while a priority processing means is provided for emergency electrocardiograms.

A plurality of electrodes for measuring electrocardiogarphic waveforms are attached on body surface positions that constitute a subset of the standard 12-lead system. The measured electrocardiogarphic waveforms of said subset of said standard 12-lead system are used to calculate the electrocardiogarphic waveforms of remaining leads in the said standard 12-lead system. The measured and calculated electrocardiographic waveforms are synthesized to form a standard 12-lead electrocardiogram. The invention is capable of monitoring the 12-lead electrocardiogram with reduced number of electrodes, wherein a portion of waveforms are directly measured and used as primary information for diagnosing heart disease, and the other portion of waveforms are derived from the measured leads and are used as a secondary information for improving the accuracy of diagnosis. The invention is especially useful in monitoring ischemic heart disease and acute myocardial infarction in cases where mounting and maintaining ten electrodes to obtain 12-lead electrocardiogram is difficult, such as in ambulatory monitoring, long-term monitoring and home monitoring.

The invention disclosed a 12-lead electrocardiogram detector and a long-range electrocardiogram monitoring and diagnosing system. The 12-lead electrocardiogram detector comprises a lead system, wherein the lead system comprises a wearable lead body and a plurality of electrodes connected to the lead body; the electrodes comprise six fixed electrodes and four movable electrodes, the fixed electrodes are sequentially fixed on the lead body according to the anatomic position of the electrocardiogram detection, and the six fixed electrodes are arranged in the inverted Z-shaped structure. The long-range electrocardiogram monitoring and diagnosing system comprises the 12-lead electrocardiogram detector, an electrocardiogram module connected with the 12-lead electrocardiogram detector to form a whole, and a server system linked with the electrocardiogram module in a wireless manner. According to the 12-lead electrocardiogram detector and the long-range electrocardiogram monitoring and diagnosing system which are disclosed by the invention, the positioning difficulty of the electrodes of the 12-lead detection can be greatly lowered, not only is the measurement accurate, time-saving and effortless, but also the self-diagnosis or the artificial diagnosis can be performed, so that finding the changes of the illness condition of a patient in time is convenient, and corresponding measures are adopted; the electrocardiogram module can perform an early warning for the electrocardiogram allorhythmia, so that the illness risk is reduced.

The invention discloses a channel pace-making signal detection method of an electrocardiogram machine, comprising the following steps: (1) carrying out sampling on original signals and carrying out differential processing on the sampled signals; (2) setting necessary conditions C1 for judging pace-making signals on the basis of a first threshold TH and a second threshold TH_Trail, detecting differential signals y(n) and filtering pulse spikes according to the necessary conditions C1; and (3) counting the number of spikes with high slope and low slope around the filtered pulse spikes, and carrying out noise evaluation on the filtered pulse spikes on the basis of the counted number. By utilizing the channel pace-making signal detection method, the noise and correct pace-making signals can be effectively distinguished, the accuracy of magnetic resonance angiography (QRS) detection and noise level evaluation is improved, therefore, the channel pace-making signal detection method can be conveniently applied on detection processing of channel pace-making signals of the 12-lead electrocardiogram machine, thus having good improvement effect in the process of detecting and analyzing electrocardiosignals.

The invention discloses an ACS (Acute Coronary Syndrome) regional synergistic treatment network system and an assistant decision-making method thereof. The ACS regional synergistic treatment network system comprises a doctor client, an emergency center server system, a 12-lead electrocardiogram monitoring system/Bluetooth electronic oximeter and an RFID (Radio Frequency Identification Devices) medical card, wherein the 12-lead electrocardiogram monitoring system/Bluetooth electronic oximeter is used for transmitting acquired information to a medical tablet computer through Bluetooth, and transmitting the acquired information to the emergency center server system through a 3G wireless network; a medical PDA (Personal Digital Assistant) is used for reading patient information through the RFID medical card, and transmitting the patient information to the emergency center server system through the 3G wireless network; and the emergency center server system is connected with the medical client through a network. Through adoption of the ACS regional synergistic treatment network system and the assistant decision-making method thereof, the emergency condition of the illness state of a patient can be judged; a synergistic treatment assistant decision-making scheme can be provided; medical experts are assisted in early judgment of an ACS; and the medical treatment time of an ACS patient is shortened greatly.

The invention discloses an electrocardiogram multi-disease analysis method based on the deep neural network. The method comprises the following steps that 12-lead electrocardiogram data is collected;the 12-lead electrocardiogram data is cut into target electrocardiogram data with the equal length; the target electrocardiogram data is substituted into a target deep neural network model, and the probability of N tasks predicated by the target deep neural network model is output; and according to the probability of the N tasks and the probability threshold value preset corresponding to the N tasks, the prediction result for the N tasks is obtained.

The invention discloses a linear reconstruction method of standard number 12 lead electrocardiogram segments based on self-adaptive electrocardiosignal region segmentation. The method comprises the following steps of self-adaptive electrocardiosignal region segmentation, wherein standard number 12 lead electrocardiosignals are subjected to self-adaptive segmentation, and according to wave characteristics of the electrocardiosignals and different heartbeat stages, the standard number 12 lead electrocardiosignals are divided into a head and tail segment, an ST-T segment, an R-P segment and a QRSsegment; linear regression training and reconstruction, wherein a least squares criterion is used for conducting linear modeling and linear reconstruction on an existing electrocardio sample; sub region electrocardio deserialization, wherein due to the fact that signals to be reconstructed are subjected to linear reconstruction respectively after electrocardiosignal region segmentation, the reconstructed electrocardio sub region sequences need to be restored to common sequential electrocardio signals. The linear reconstruction method of the standard number 12 lead electrocardiogram segments based on self-adaptive electrocardiosignal region segmentation is fast and accurate.

The invention provides a method and a system for analyzing 18-lead dynamic electrocardiograms on the basis of Wilson lead. The method includes arranging 10 electrode slices at preset positions of the body surface of a tested person, acquiring electrocardiogram signals of the tested person by the aid of each electrode slice and processing the electrocardiogram signals to obtain corresponding electrocardiogram data; acquiring 12-lead electrocardiogram data of the tested person according to the electrocardiogram data of the tested person; computing X-axis, Y-axis and Z-axis data on the basis of Wilson lead systems according to the 12-lead electrocardiogram data of the tested person; deriving lead data for representing the left ventricle of the tested person on the basis of the Wilson lead systems and deriving lead data for representing the right ventricle of the tested person on the basis of the Wilson lead systems; generating the 18-lead electrocardiograms of the tested person. The method and the system have the advantages that 12-lead electrocardiograms can be recorded and synchronized by the aid of the improved Wilson lead systems, and the 18-lead electrocardiograms can be calculated from the 12-lead electrocardiograms.

The invention discloses a method for analyzing abnormal electrocardiogram tension for remote medical care. The method comprises the following steps of firstly, collecting a large amount of standard 12-lead electrocardiogram data in a remote method; then, converting the electrocardiogram into high-dimension tension electrocardiogram data by a short-time Fourier transform; directly using the high-dimension tension electrocardiogram data as a feature, and extracting electrocardiogram features directly being used for classification by an feature extraction and feature dimension reduction algorithm through directly using the tension data as the input. Because the method is based on a TTV (transit timing variable) transform principle, the features based on vector storage can be obtained, and then the vector features are classified by a SVM (support vector machine) classifying method. The method has the advantages that the tension electrocardiogram data are directly used as the input, the structure information of multi-lead electrocardiogram is fully utilized, the defect of non-precise data ton single analysis of the original single-lead electrocardiogram is eliminated, and the effectivity of the electrocardiogram analysis is realized.

In order to derive a standard 12-lead electrocardiogram, ones of limb leads and chest leads which constitute a lead system for the standard 12-lead electrocardiogram using 10 electrodes are selected. Electrocardiographic waveforms corresponding to the selected ones of the limb leads and the chest leads are obtained, as measured electrocardiographic waveforms, with electrodes attached on a living body. Electrocardiographic waveforms corresponding to a remaining ones of the limb leads and the chest leads are calculated, as non-measured electrocardiographic waveforms, with a prescribed transformation matrix and the measured electrocardiographic waveforms.

The invention discloses a risk stratification method for myocardial ischemia based on deterministic learning and deep learning. The method includes the steps that conventional 12-lead electrocardiogram signals are collected, based on the deterministic learning theory, neural network modeling and identification are conducted on intrinsic electrocardiodynamic characteristics of the shallow electrocardiogram signals, and the intrinsic dynamic characteristics of ECG signals are obtained; the convolutional neural network under the framework of deep learning is used for achieving the risk stratification of myocardial ischemia. The method combines the deterministic learning dynamic modeling method and the deep learning classification method for the first time, the method is applied to early riskstratification of myocardial ischemia based on the conventional 12-lead electrocardiogram signals, no additional detection equipment is needed, and the method is easy and convenient to use and easy tooperate. Through the deterministic learning method, the dynamic characteristics more sensitive to the ischemic state are extracted, the deep neural network can learn data features independently without further data characterization, and the complexity of the system is reduced.

The invention discloses an emergency cardiovascular care network system and a classification and early warning method thereof. The system comprises a doctor client, an emergency center server system and a 12 lead electrocardiogram collection module, the 12 lead electrocardiogram collection module sends collected information to a medical tablet personal computer through Bluetooth, and transmits thecollected information to the emergency center server system through a 4G wireless network, and the emergency center server system is connected with the medical client. Accordingly, electrocardiogramabnormality symptoms of patients can be classified and pre-warned according to emergencies, medical specialists are helped to judge cardiovascular diseases in the early stage, and the medical treatment time of the patients suffering from the cardiovascular diseases is greatly shortened.

The invention provides a 12-lead electrocardiogram data acquisition card which relates to a medical device. The electrocardiogram acquisition card adopts hardware description language programming, such as VHDL and so on, to realize the selection and the control of the 12-lead electrocardiogram acquisition, the A/D conversion, the control of sampling rate, the filtering process of the electrocardiogram data, the sensitivity control and the data storage and transmission by FPGA. A general control module controls lead signals output by a sensitivity control module to an A/D conversion and control module to carry out the sensitivity detection and controls the lead signals after the sensitivity is detected by a data processing module to carry out the filtering process; a lead falling-off detecting part judges whether the lead falls off or not according to lead falling-off signals; a data transmission module receives a control instruction sent by an upper computer and transmits the lead signals processed by filtering into the upper computer. The data acquisition card improves the integration degree of a circuit and reduces the use amount and the volume of a resistor largely, thereby reducing the power consumption greatly, saving the cost and improving the interference immunity.

The invention discloses a health monitoring all-in-one machine with a 12-lead electrocardiogram monitoring instrument. The health monitoring all-in-one machine comprises a first function machine, a second function machine and a third function machine, wherein the first function machine comprises a display, a blood-pressure meter, a glucometer, an oximeter, the 12-lead electrocardiogram monitoring instrument, a main controller, a card reader and a card reading panel; the second function machine comprises a weight measuring sensor and a microprocessor; the third function machine comprises a display screen and an ultrasonic wave probe; the blood-pressure meter is used for measuring the blood pressure value of a user; the glucometer is used for measuring the blood sugar value of the user; the oximeter is used for measuring the blood oxygen value of the user; the 12-lead electrocardiogram monitoring instrument measures the electrocardiogram signals of the user; the weight measuring sensor measures the body weight data of the user; the ultrasonic probe detects the body height data of the user. The blood pressure value, the blood sugar value, the blood oxygen value, the electrocardiogram condition, the body height data and the body weight data of the user can be measured; the advantages of multifunction integration, high integration degree and high automation degree can be realized; the dismountable structure is used, so that the convenient dismounting can be realized for transportation; the repair is also convenient.

The invention discloses a portable remote 12-lead electrocardiogram real-time diagnosis system comprising a data acquisition box, an integrated multi-lead electrode plate and a smartphone. The system is simple in structure, lower in price and good in portability, a patient can diagnose electrocardio movement in real time according to requirement of symptoms, and the problem that electrocardiogram in hospitals cannot capture electrocardio conditions during attacks outside the hospitals is solved; waiting is not required, the integrated multi-lead electrode plate is disposable, distribution of precordial lead electrodes on the electrode plate takes body surface markers such as nipples on two sides of human bodies, sternums and the like as reference points, operation by non-medical workers is facilitated, great convenience is brought, meanwhile, the possibility of infectious skin disease cross infection is avoided; the integrated multi-lead electrode plate is attached to the chest and cannot bring inconvenience to the life of the patient, electrocardiograms are transferred to a hospital terminal to be analyzed and diagnosed by doctors for real-time report, the electrocardio conditions can be accurately judged, the diagnosis accuracy is improved, and the using effect is good.

The invention relates to a three-dimensional color coding display method for myocardial blood volume distribution, through which the blood volume distribution information of electrocardiosignals is converted and displayed on a visual three-dimensional color model. The method is characterized in that a 12-lead electrocardiogram (ECG) of a human body is collected, and the myocardial blood volume distribution information of the ECG, i.e. ST-segment deviation, is extracted; in a cardiac electric axis system, the total electrocardial damage vector is obtained through the adverse projection of the ST-segment damage vector of each lead; a standard three-dimensional heart model is established, the central position of an area where the blood volume is scarcely distributed is the joint of the total damage vector and the surface of the heart model, the distribution range is proportional to the total damage vector, and RGB (red, green and blue) coding is carried out according to the different distances between all the positions and the center of the area where the blood volume is scarcely distributed, so as to display the myocardial blood volume distribution on the surface of the heart model.

The invention discloses an intelligent blurry electrocardiogram calculation and measurement sensor, which comprises a compact-type vital sign signal virtual instrument system sensor hung on the human body, a portable blurry electrocardiogram sensor host and a portable blurry electrocardiogram sensor host base. The intelligent blurry electrocardiogram calculation and measurement sensor provides on-line acquired reliable and high-fidelity 12 lead electrocardiogram data with amplitude shaft mark and timer shaft mark, GPS information with position vector, speed vector and time vector and active incident information with human-computer interaction vector and time vector, even function of the whole blurry electrocardiogram for electrocardiogram doctors by adopting neural fuzzy controller technology and wireless real-time communication technology.

The invention provides a 12-lead electrocardiogram data acquisition and synchronization display system. The 12-lead electrocardiogram data acquisition and synchronization display system comprises a mobile device and an electrocardiogram imaging software system installed on the mobile device, and the electrocardiogram imaging software system comprises a data reading module, a tag identification module, a thread extracting data module, a data buffer cache, an imaging system and a data storage system. The invention further discloses a method of the 12-lead electrocardiogram data acquisition and synchronization display system, a multi-thread concurrent processing module is arranged, a data acquisition thread module is used for receiving and storing data, a real-time drawing thread module readsthe data to display an electrocardiogram in real time, the data acquisition thread module and a tag protocol module are used for labeling, saving, and sending the electrocardiogram data, the electrocardiogram data are sent through the mail, and a receiver can repeatedly reappear the electrocardiogram recorded by a user.

The invention belongs to the field of medicine care, and discloses an electrocardiogram automatic recognition system. The electrocardiogram automatic recognition system is provided with a 12-lead electrocardiogram collector, a wireless/wired network transmission module, an electrocardiogram collection and time domain feature recognizer, an electrocardiogram main wave interphase analyzer, an electrocardiogram QRS wave similarity analyzer, a 12-lead electrocardiogram queuing analyzer and an output module. The collected electrocardiogram information is subjected to wired or wireless transmissionthrough the wireless/wired network transmission module; time domain feature analysis and recognition is performed through the electrocardiogram collection and time domain feature recognizer; the mainwave interphase characteristics of the electrocardiogram are analyzed through the electrocardiogram main wave interphase analyzer, and main wave interphase characteristic data is generated; the QRS wave similarity is compared and analyzed through the electrocardiogram QRS wave similarity analyzer; the queuing analysis is performed on the 12-lead electrocardiogram of a patient through the 12-lead electrocardiogram queuing analyzer; finally, the analyzed data is summarized and output through the data output module.

The present invention is different to the existing 12-leads electrocardiogram mobile information system which could only provide the inquiring service to specific smart phone operation system, and designed using the network service as the platform for data transforming and communications of the programs between the mobile-end and the server-end. The different kinds of databases (eg, SQL SERVER MYSQL) are then transformed to same kind SQLITE database according to the property of the SQLITE database supporting many kinds of operation, so as to provide services to smart phones using many different kinds of operation systems, and achieve the goal to integrate the mobile database of 12-leads electrocardiogram.

The invention relates to an electrocardiogram monitoring system which relates to the field of medical teaching. The system comprises a dummy provided with a magnetic field generating unit; a magneticfield detecting unit used for detecting magnetic induction intensity of the magnetic field generating unit; a processing module comprising a storage unit and connected with the magnetic field detection unit; and a display unit connected with the processing module and used for displaying the electrocardiogram. The invention can realize the application on the medical teaching model. An operator is allowed to connect an analog lead electrode at any position on the dummy and can be directly connected to an electrocardiogram monitor. A normal or abnormal, regular or irregular 12 lead electrocardiogram waveforms are displayed on the monitor and whether the electrode is connected to the correct position of the dummy or not is detected.