26 results about "QT interval" patented technology

Embodiments of the present disclosure provide a mobile electrocardiogram (ECG) sensor comprising an electrode assembly comprising electrodes, wherein the electrode assembly senses heart-related signals when in contact with a body of a user, and produces electrical signals representing the sensed heart-related signals. The ECG sensor further comprises a processing device, operatively coupled to the electrode assembly, the processing device to provide the sensed heart-related signals to a machine learning module trained to predict a twelve-lead QT interval (QTc) value from the mobile ECG sensor comprising less than twelve leads. The ECG sensor also comprises a housing containing the electrode assembly and the processing device.

The invention relates to the technical field of image enhancement, in particular to an angiocardiography high-precision angiography enhancement method and system. The method comprises the steps that an ECG curve of electrocardiosignals before and after contrast agent injection of a patient and a blood vessel image are obtained; determining the compressible degree of each wave band according to the change of different wave bands and the change of the heart rate in the QT interval before and after the contrast agent is injected; determining the increment duration of each wave band in combination with the standard duration, the actual duration and the compressible degree; performing standardized adjustment on the ECG time phase of each frame of blood vessel image in combination with the increment time length and the actual time length of each wave band to obtain a standard time phase; determining a mask matched with each negative film according to the standard time phases of the negative films and the masks; and carrying out image subtraction on each negative film and the matched mask, and carrying out angiography enhancement processing. The blood vessel imaging precision after digital subtraction can be improved, the blood vessel artifact phenomenon is reduced, and the blood vessel imaging precision and reliability are enhanced.

The invention provides an electrocardio physiological signal feature extraction method for heart conduction block classification, and belongs to the technical field of electrocardio physiological signals. 12-lead electrocardiosignals and auxiliary signals of a patient are collected, a wave equation is established through a water-wave-imitating interference multi-signal fusion algorithm, and a multi-lead signal interference mode is simulated; the method comprises the following steps: extracting time domain characteristic parameters including a PR interval, a QRS wave width, a QT interval and the like from a fusion signal, and calculating frequency domain characteristic parameters including power density distribution and a heart rate variability index; nonlinear dynamic characteristic parameters including a sample entropy value, a fractal dimension and the like are extracted, the conduction block type is judged according to the PR interval length and a QRS wave falling mode, and the technical problem that a weak heart conduction block characteristic signal cannot be accurately recognized through single-lead electrocardio analysis is solved.

A cardiopulmonary management system includes a multi-sensor device and a controller. The multi-sensor device includes an elongated body having a first end and a second end, a first electrode disposed at the first end of the body, a second electrode disposed at the second end of the body, an electrical circuitry disposed near a middle of the body, and a sound sensor. The multi-sensor device is configured to be disposed on a skin of a subject and to measure cardiopulmonary parameters from the subject. The controller is configured to derive a score of sound change, heart rate change, thoracic impedance change, respiratory rate change, QRS wavelength change, QT interval change, electromechanical activation time change, and left ventricular systolic time change based on the measured cardiopulmonary parameters. The controller is further configured to control an operation of the system when the derived score is greater than a threshold.

The application discloses a blood pressure monitoring device based on multi-source physiological parameter adaptive control, comprising a blood pressure measurement module, an electrocardiogram measurement module and a processing module. The blood pressure measurement module comprises a microcontroller unit and an air pump and a deflation valve controlled thereby. The processing module acquires multi-source physiological parameters and controls the air path accordingly: when the skin conductance response is high, the deflation time is shortened to reduce the stress stimulus of the patient; when the pulse pressure difference of the initial measurement is large, the deflation frequency is increased to adapt to the rapid change of blood pressure and avoid false hypotension; when the electrocardiogram QT interval is long, the inflation time is prolonged to ensure measurement accuracy. The application dynamically adjusts the inflation and deflation physical process through multi-source physiological feedback, significantly improving the measurement accuracy and adaptability of the device under complex physiological conditions.

Embodiments of the present disclosure provide a mobile electrocardiogram (ECG) sensor comprising an electrode assembly comprising electrodes, wherein the electrode assembly senses heart-related signals when in contact with a body of a user, and produces electrical signals representing the sensed heart-related signals. The ECG sensor further comprises a processing device, operatively coupled to the electrode assembly, the processing device to provide the sensed heart-related signals to a machine learning module trained to predict a twelve-lead QT interval (QTc) value from the mobile ECG sensor comprising less than twelve leads. The ECG sensor also comprises a housing containing the electrode assembly and the processing device.

Applicants disclose methods, uses, and compositions for treating patients suffering from Cushing Syndrome or Cushing Disease (collectively referred to as' CS ') without causing a significant QT interval extension (e.g., the difference of the QT interval after administration from the baseline QT interval by no more than about 10 milliseconds). The therapeutic amount of the heteroaryl ketone fused aza-naphthane compound may be from about 50 mg / day (mg / day) to up to about 500 mg / day, in embodiments, up to about 800 mg / day. The methods, uses, and compositions can shorten QT intervals, and can be used to treat QT prolongation in patients, including CS patients. The treatment may be a treatment administered orally to a fasting patient or an eating patient. The heteroaryl ketone fused aza-naphthane compounds can be administered with meals. The heteroaryl ketone fused aza-naphthane compound may be reracolan, which is (R)-(1-(4-fluorophenyl)-6-((1-methyl-1H-pyrazol-4-yl) sulfonyl)-4, 4a, 5, 6, 7, 8-hexahydro-1H-pyrazolo [3, 4-g] isoquinolin-4a-yl) (4-(trifluoromethyl) pyridin-2-yl) methanone having the following structure (I) # imgabs 0 #

This application relates to the field of human bioelectrical signal measurement, specifically to a method, system, and apparatus for determining the voltage value of an electrocardiogram (ECG) signal at a predetermined future time. The method involves acquiring an ECG signal over a predetermined time period and processing it in segments to enable data extraction; determining the QT interval trend slope, the proportion of low-frequency energy in the ST segment, and the standard deviation of the RR interval sequence of heart rate variability in the processed ECG signal, and assigning weighting coefficients; determining the average voltage value at each moment within the predetermined time period based on the processed ECG signal; and finally determining the voltage value of the ECG signal at the predetermined future time based on the determined trend slope, low-frequency energy proportion, sequence standard deviation, weighting coefficients, and average value. The method provided by this application allows for accurate determination of the voltage value of a user's ECG signal at a predetermined future time.

Various embodiments presented herein describe a system, and related method and computer-readable storage media storing instructions, including one or more of the following: memory configured to store a plurality of QT interval values; and processing circuitry configured to: continuously determine, based on an ECG of a patient sensed by an implantable medical device, the plurality of QT interval values; determine at least one of whether a first QT interval value of the plurality of QT interval values meets a first threshold or whether a change in magnitude of a difference between two QT interval values of the plurality of QT interval values meets a second threshold; and based on at least one of a determination that the first QT interval value meets the first threshold or the change in magnitude of the difference between the two QT interval values meets the second threshold, generate a first indication for output.

Disclosed herein are example devices for detecting one or more parameters of a cardiac signal. The devices include one or more electrodes and sensing circuitry configured to sense a cardiac signal via the one or more electrodes. The devices further include processing circuitry configured to determine an R-wave of the cardiac signal and determine a previous RR interval of the cardiac signal and a current RR interval of the cardiac signal based on the determined R-wave. The processing circuitry is further configured to determine a search window based on one or more of the current RR interval or the previous RR interval, determine a T-wave of the cardiac signal in the search window, and determine a QT interval based on the determined T-wave and the determined R-wave.

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.

Methods and systems for monitoring blood glucose levels of a subject are described, the method comprising the steps of: continuously acquiring electrocardiogram parameters of the subject, the electrocardiogram parameters comprising heart rate, heart rate variability, QT interval, and Tp / Rp ratio; inputting the acquired electrocardiogram parameters into a learning algorithm for processing the parameters; and outputting a continuously updated output value representative of the blood glucose level of the subject.

Embodiments of the present application disclose a decision rule determination method and device, equipment and a storage medium, the method comprising: obtaining sample data comprising a sub-feature combination label of a plurality of sample electrocardio signals, the sub-feature combination label comprising at least a sub-feature threshold of each sub-feature of a confirmed QT interval in the sample electrocardio signals; performing evolution processing on the sub-feature threshold by using the sample data and a preset evolution algorithm, determining a target sub-feature threshold of each sub-feature of an optimal sub-feature combination label; and performing rule construction processing according to the target sub-feature threshold, and determining a target decision rule for feature recognition of a QT interval in a to-be-recognized electrocardio signal. In the foregoing manner, the evolution algorithm can be used to perform evolution iteration on the sub-feature threshold in the sample data, to obtain a target sub-feature threshold with the highest recognition accuracy, so as to formulate and use the target decision rule to recognize the QT interval, thereby facilitating improvement of the accuracy of recognizing the QT interval.

The invention relates to the technical field of biological medicines, in particular to application of an hERG potassium channel inhibitor in preparation of a medicine for prolonging a heart QT interval. The compound 1, 3-(4-chlorphenyl)-N-{3-[(1-1-phenyl-1H-tetrazole-5-yl) thio]-propyl}-2-propenyl-1-amine or the pharmaceutically acceptable salt of the compound 1, 3-(4-chlorphenyl)-N-{3-[(1-1-phenyl-1H-tetrazole-5-yl) thio]-propyl}-2-propenyl-1-amine can target an hERG potassium ion channel; in a rabbit heart rate monitoring experiment, compared with a solvent control, the intraperitoneal injection of 10 mg / kg of 1, 3-(4-chlorphenyl)-N-{3-[(1-1-phenyl-1H-tetrazole-5-yl) thio]-propyl}-2-allyl-1-amine can obviously prolong the QT interval and reduce the heart rate, and has the application potential of regulating the heart function.

An example device for detecting one or more parameters of a cardiac signal is disclosed herein. The device includes one or more electrodes and sensing circuitry configured to sense a cardiac signal via the one or more electrodes. The device further includes processing circuitry configured to determine an R-wave of the cardiac signal and determine whether the R-wave is noisy. Based on the R-wave being noisy, the processing circuitry is configured to determine whether the cardiac signal around a determined T-wave is noisy. Based on the cardiac signal around the determined T-wave not being noisy, the processing circuitry is configured to determine a QT interval or a corrected QT interval based on the determined T-wave and the determined R-wave.

This invention discloses a multi-parameter fusion method and system for real-time risk assessment of cardiac rehabilitation exercise, relating to the field of medical and health information technology. The method includes: collecting electrocardiogram signals, heart rate, and acceleration data; extracting ST segment offset, QT interval, and heart rate variability features; calculating heart rate reserve percentage and metabolic equivalent; inputting the multi-dimensional features into a bidirectional LSTM network to output risk probabilities; determining the risk level based on the comprehensive risk index and generating exercise intensity recommendations. This invention achieves prospective risk prediction and adaptive intensity regulation, improving the safety of cardiac rehabilitation training.

A method for anesthetizing and / or sedating a subject with shorter QT interval or reduced risk of TdP or lower risk of cardiac arrhythmias, said method comprising administering an effective dose of cipepofol to the subject.

This invention discloses an auxiliary nursing system for cardiology patients, belonging to the field of auxiliary nursing technology. This system integrates data from multiple devices and removes interference signals through a multi-source data acquisition module. A time-series alignment processor achieves precise time-dimensional fusion, breaking down data silos and improving data accuracy and consistency. A dynamic risk assessment engine, through real-time monitoring of multiple units, can promptly detect risks such as QT interval abnormalities and fluid imbalances, and issue graded warnings to avoid delayed risk assessment. A nursing instruction generator generates instructions based on warnings and calls clinical guidelines, covering medication, equipment control, etc., providing digital support for nursing decisions. A clinical feedback interface combined with a model optimizer optimizes the system based on medical and nursing correction records, achieving dynamic adaptation. Furthermore, the system expands its functionality by connecting to hospital information systems and adding visualization displays, further improving the nursing process.

An example device for detecting one or more parameters of a cardiac signal is disclosed herein. The device includes one or more electrodes and a sensing circuit configured to sense a cardiac signal via the one or more electrodes. The apparatus further includes processing circuitry configured to determine an R-wave of the cardiac signal and determine whether the R-wave is noisy. Based on the R-wave being noisy, the processing circuitry is configured to determine whether the cardiac signal around a determined T-wave is noisy. Based on the cardiac signal around the determined T-wave not being noisy, the processing circuitry is configured to determine a QT interval or a corrected QT interval based on the determined T-wave and the determined R-wave.

The invention relates to the technical field of medical monitoring, and particularly discloses a thyroid cancer postoperative hypocalcemia early warning method based on wearable equipment, and the method carries out the seven steps of monitoring through the wearable equipment: firstly, building a personalized physiological reference model which comprises an initial nerve excitation threshold value and a normal QT interval fluctuation range; continuously collecting electrocardiosignals to identify the heart repolarization abnormal trend, and dynamically adjusting the monitoring intensity; a nerve excitation threshold change is tracked through encrypted nerve detection, and a collaborative deterioration index is generated; after heart and nerve indexes are subjected to cross validation, calculating a quantitative composite early warning risk score; and finally, an early warning instruction is transmitted according to the grading threshold. Non-clinical symptom period early warning is achieved, the accuracy is improved through double evidence chains, efficient and low-consumption monitoring is achieved in combination with personalized benchmark and self-adaptive monitoring, visual risk scoring and action guidance are provided for users, and the safety and life quality of postoperative patients are effectively improved.

To provide a biological information processor, a biological information processing method, and a program that enable highly accurately evaluating the degree of pain of a patient.SOLUTION: A biological information measurement device 100 for evaluating the degree of pain of a patient, comprises: a measurement part that measures biological information of the patient; a storage part that stores biological information for reference; a comparison part that compares the biological information with the biological information for reference; and a calculation part that calculates a pain score of the patient on the basis of a comparison result by the comparison part. The comparison part calculates at least one common biological parameter among a heart rate, a QT time, a pulse wave propagation time, a perfusion index, and an RR interval for each of the biological information and the biological information for reference, and compares the biological parameter of the biological information with the biological parameter of the biological information for reference.SELECTED DRAWING: Figure 1

The application relates to the technical field of image enhancement, in particular to a high-precision blood vessel imaging enhancement method and system for cardiovascular imaging. The method comprises the following steps: acquiring an ECG curve of an electrocardiosignal before and after injection of a contrast medium of a patient, and acquiring a blood vessel image; determining the compressibility of each wave band according to the changes of the QT interval of each wave band and the heart rate before and after injection of the contrast medium; determining the incremental time length of each wave band by combining a standard time length, an actual time length and the compressibility; standardizing and adjusting the ECG phase of each frame of the blood vessel image according to the incremental time length and the actual time length of each wave band to obtain a standard phase; determining the matched mask of each negative film according to the standard phase of the negative film and the mask; and performing image subtraction on each negative film and the matched mask and performing blood vessel imaging enhancement processing. The application can improve the imaging precision of the blood vessels after digital subtraction, reduce the blood vessel artifact phenomenon, and enhance the imaging precision and reliability of the blood vessels.

The invention provides a wireless electrocardiogram monitoring equipment wireless wire harness integrator, system and method. The integrator comprises a plurality of modules: an electrocardiogram signal acquisition module monitors signals in real time; the data preprocessing module filters and amplifies the signal; the QT interval calculation module analyzes a QT interval; the heart rate variability calculation module extracts an HRV index; the electrocardiogram analysis model analyzes the electrocardiogram; the early warning module gives an alarm based on the analysis result; the wireless communication module transmits a result to a monitoring center, and all the modules are integrated; during use, the integrator firstly collects electrocardiosignals and then preprocesses the electrocardiosignals to ensure signal quality. The QT interval and heart rate variability module analyzes the processed signals and extracts key parameters. The electrocardio analysis model deeply analyzes electrocardio signals through the parameters, and the early warning module determines whether to give an alarm or not according to the analysis result. If the electrocardiogram is abnormal, the early warning module triggers an alarm and sends the alarm to a monitoring center through wireless communication, so that medical staff can respond in time, and the diagnosis efficiency is improved.

The invention discloses an auxiliary nursing system for a patient in the department of cardiology, and relates to the technical field of auxiliary nursing, the auxiliary nursing system for the patient in the department of cardiology integrates multi-device data and cleans interference signals through a multi-source data acquisition module, realizes precise time dimension fusion through a time sequence alignment processor, breaks data islands, and improves the accuracy of nursing. The data accuracy and continuity are improved; the dynamic risk assessment engine can timely find out risks such as QT interval abnormity and liquid unbalance through multi-unit real-time monitoring and perform graded early warning, and risk assessment lag is avoided; the nursing instruction generator calls clinical guidelines to generate instructions according to early warning, medicine, equipment regulation and control and the like are covered, and digital support is provided for nursing decision making; a clinical feedback interface is combined with a model optimizer, and dynamic self-adaption is realized based on a medical care correction record optimization system; in addition, the system further expands and is in butt joint with a hospital information system, functions of visual display and the like are added, and the nursing process is further improved.

A system comprises a cloud computing system, a computing device, and a sensor device. The sensor device is configured to sense an electrocardiogram of the patient, detect a ventricular tachyarrhythmia based on sensed electrocardiogram, and wirelessly communicate with the computing device in response to the detection of the ventricular tachyarrhythmia. Based on the wireless communication from the sensor device, the computing device is configured to at least one of output a local alarm or transmit an alert to an emergency medical service via the cloud computing system. Processing circuitry of at least one of the sensor device, the computing device, or the cloud computing system is configured to determine QT intervals based on the electrocardiogram, and transmit a message indicating QT prolongation of the patient to a clinician based on a determination that the QT intervals satisfy one or more QT prolongation criteria.

A myocardial ischemia detection device and a myocardial ischemia detection method, wherein the myocardial ischemia detection device includes a measuring unit and a processing unit. The myocardial ischemia detection method includes a measuring step, a feature extraction step, and a first analysis step. The measuring step obtains multiple electrocardiogram (ECG) signals of a human body by means of the measuring unit. The measurement positions of at least part of the ECG signals correspond to the left chest of the human body. The feature extraction step extracts the QT interval of each ECG signal by means of the processing unit, and calculates multiple feature values corresponding to multiple points of the human body. The first analysis step is to compare the point positions corresponding to at least one of the lowest feature values to detect the location of myocardial ischemia. Compared with the existing analysis method based on the waveform changes of the ST segment, the QT interval is less affected by noise and baseline offset, and can avoid evaluation errors.