12 results about "QT interval" patented technology

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.

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.

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.

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.

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.

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.

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.