31 results about "Arterial pressure waveform" patented technology

Cardiac stroke volume (SV) of a subject is estimated as a function of a value derived from a measured arterial pressure waveform. The value may be the standard deviation, or a function of the difference between maximum and minimum pressure values, or a function of either the maximum value of the first time derivative or the absolute value of the minimum of the first time derivative of the pressure waveform, or both, or a function of the magnitude of one or more spectral components of the pressure waveform at a frequency corresponding to the heart rate. Cardiac output is then estimated as the product of the subject's heart rate and SV, scaled by a calibration constant. Arterial pressure may be measured invasively or non-invasively.

One or more cardiovascular parameters is estimated as a function of the arterial pressure waveform, in particular, using at least one statistical moment of pressure waveform having an order greater than one. Arterial compliance, the exponential pressure decay constant, vascular resistance, cardiac output, and stroke volume are examples of cardiovascular parameters that can be estimated using various aspects of the invention. In one embodiment of the invention, not only are the first four moments (mean, standard deviation, skewness, and kurtosis) of the pressure waveform used to estimate the cardiovascular parameter(s) of interest, but also heart rate, statistical moments of a set of pressure-weighted time values, and certain anthropometric patient measurements such as age, sex, body surface area, etc.

Cardiac stroke volume (SV) of a subject is estimated as a function of a value derived from a measured arterial pressure waveform. The value may be the standard deviation, or a function of the difference between maximum and minimum pressure values, or a function of either the maximum value of the first time derivative or the absolute value of the minimum of the first time derivative of the pressure waveform, or both, or a function of the magnitude of one or more spectral components of the pressure waveform at a frequency corresponding to the heart rate. Cardiac output is then estimated as the product of the subject's heart rate and SV, scaled by a calibration constant. Arterial pressure may be measured invasively or non-invasively.

One or more cardiovascular parameters is estimated as a function of the arterial pressure waveform, in particular, using at least one statistical moment of pressure waveform having an order greater than one. Arterial compliance, the exponential pressure decay constant, vascular resistance, cardiac output, and stroke volume are examples of cardiovascular parameters that can be estimated using various aspects of the invention. In one embodiment of the invention, not only are the first four moments (mean, standard deviation, skewness, and kurtosis) of the pressure waveform used to estimate the cardiovascular parameter(s) of interest, but also heart rate, statistical moments of a set of pressure-weighted time values, and certain anthropometric patient measurements such as age, sex, body surface area, etc.

The invention discloses a non-invasive central aortic blood pressure measuring method and device. The non-invasive central aortic blood pressure measuring method includes, according to a human artery network model based on viscous fluid mechanics, a method of calculating artery network model personalized parameters of a measured person through measured radial artery and brachial artery pulse wave signals and arm blood pressure values, a method of calculating an ascending aorta-radial artery transfer function and a method of calculating central arterial pressure waveforms through measured central arterial pressures. The non-invasive central aortic blood pressure continuous measuring device comprises a pulse wave signal processing and analysis unit and a radial artery and brachial artery pulse wave signal acquisition unit worn on a wrist. The method is different from an existing general transfer function method, the artery network model parameters of each person to be measured are measured and calculated and the artery network model parameters are numerical characteristics of the cardiovascular system states of the person to be measured with the calculated central arterial pressure waveforms, and the method and device has important meanings in prevention, curing and control of cardiovascular diseases, especially high-risk diseases, such as hypertensions and coronary heart diseases.

System and method of monitoring a patient including acquiring a respiration waveform and an arterial pressure waveform and determining a window on the respiration waveform that represents end expiration and approximates an apnea condition. The method can include calculating a systolic pressure variation value, a delta up value, and a delta down value based on a portion of the arterial pressure waveform corresponding to the window on the respiration waveform. In some embodiments, the respiration waveform can be acquired without manual interruption of mechanical ventilation and the values can be calculated substantially continuously.

An exercise therapy device 1 includes a pulse wave sensors 16 for detecting a pulse wave of a lower limb of a patient when being fixed to the patient, a walking sensor 15 for detecting a walking distance that the patient has walked, and a target walking distance setting section 30. The target walking distance setting section 30 is configured to set a target walking distance for exercise therapy, when the pulse wave detected by the pulse wave sensors 16 has a waveform having a predetermined shape which is flatter than an arterial pressure waveform, based on the walking distance of the patient by the time when the pulse wave has the waveform having the predetermined shape.

System and method of monitoring a patient including acquiring a respiration waveform and an arterial pressure waveform and determining a window on the respiration waveform that represents end expiration and approximates an apnea condition. The method can include calculating a systolic pressure variation value, a delta up value, and a delta down value based on a portion of the arterial pressure waveform corresponding to the window on the respiration waveform. In some embodiments, the respiration waveform can be acquired without manual interruption of mechanical ventilation and the values can be calculated substantially continuously.

The invention discloses a central arterial blood pressure measuring device. The central arterial blood pressure measuring device comprises a brachial arterial blood pressure measurement module, an electrocardiogram measurement module, a radial arterial blood pressure measurement module, a data processing module, a pulse wave conduction time evaluation module, a pulse wave reflection coefficient evaluation module, a central arterial pressure calculation module, a data display module and the like; the pulse wave conduction time evaluation module is used for solving pulse wave conduction time; the pulse wave reflection coefficient evaluation module divides pulse waves into incident waves and reflected waves, and calculates the ratio of the amplitude of the incident waves to the sum of the amplitudes of the incident waves and the reflected waves to obtain a pulse wave reflection coefficient; the central arterial pressure calculation module calibrates a brachial arterial blood pressure waveform; meanwhile, the pulse wave conduction time and the pulse wave reflection coefficient are input into a mathematical model to calculate a transfer function, and then the transfer function and the calibrated brachial arterial blood pressure waveform are utilized for calculating a central arterial pressure waveform. By means of the device, the measurement accuracy of the central arterial pressurecan be significantly improved, and the measurement error is reduced.

Multivariate statistical models for the detection of vascular conditions, methods for creating such multivariate statistical models, and methods for the detection of vascular condition in a subject using the multivariate statistical models are described. The models are created based on arterial pressure waveform data from a first group of subjects that were experiencing a particular vascular condition and a second group of subjects that were not experiencing the same vascular condition. The multivariate statistical models are set up to provide different output values for each set of input data. Thus, when data from a subject under observation is input into the model, the relationship of the model output value to the established output values for the two groups upon which the model was established will indicate whether the subject is experiencing the vascular condition.

Methods for the detection of vascular conditions such as vasodilation in a subject are described. The methods involve receiving a signal corresponding to an arterial blood pressure and calculating one or more cardiovascular parameters from the arterial blood pressure. The cardiovascular parameters are calculated using factors impacted by vascular conditions such as vasodilation. Factors impacted by these vascular conditions include the area under the systolic portion of the arterial blood pressure signal, the duration of systole, and the ratio of the duration of the systole to the duration of the diastole. By monitoring cardiovascular parameters that are calculated using factors impacted by vascular conditions such as vasodilation for changes indicating the vascular conditions, such vascular conditions can be detected.

The invention discloses a cardiac output detector wireless transmission device which is mainly applied to detecting transient temperature of human arterial blood. According to the technical scheme that a physical layer and a data link layer of a CAN (controller area network) protocol are integrated in a CAN bus communication interface, the cardiac output detector wireless transmission device is a main unit capable of receiving and controlling wireless transmission of multiple auxiliary units. The cardiac output detector wireless transmission device is structurally characterized by being composed of an infusion connector, a button cell, a wireless communication module, a wireless communication module shell, a temperature sensor, a PICCO (pulse induced contour crdic output) double-cavity tube, a catheter fixator, and a wireless receiving module and a software program of a cardiac output detector; the cardiac output detector also named as a PICCO catheter before innovation is a measuring instrument used at the front end of the cardiac output monitor; the measuring principle of the cardiac output monitor is that single cardiac output (CO) is measured by adopting a hot dilution method, and continuous cardiac output (ICCO) is acquired by analyzing area under arterial pressure-waveform curves; meanwhile, intrathoracic blood volume (ITBV) and extravascular lung water (EVLW) can be calculated.

The present invention belongs to the field of medical technology, and discloses a system and a method for interaction in cardiovascular medicine department recovery based on the Internet of things. Acentral control module substitutes obtained parameters into a phase noise power law model to obtain a phase noise measurement result of detected signals and perform dispatching of a parameter calculation module; and the parameter calculation module analyzes arterial pressure waveform data to determine whether a user is in an abnormal state or not right now and determine accurate parameters of theuser's angiocarpy. The system and the method for interaction in cardiovascular medicine department recovery employ a recovery planning prompting module to compare a recovery plan established by medical workers with stored recovery plans, and store the recovery plans and set preset prompting time in a condition without conflicts occurred to facilitates ensuring of the accuracy of the established recovery plan, and improve the execution efficiency and the accuracy of the recovery plan compared to the artificial notice and prompting in the prior art so as to improve the user recovery effect.

The invention provides a central arterial blood pressure measurement method based on a human artery 3D blood vessel network model. A plurality of steps in the simulation process are programmed into parameterized instructions through the ANSYS secondary development language APDL. Outlet parameters of the corresponding blood vessel network model are given for measured different radial artery pressure waveform signals of the left and right hands, and the corresponding personalized simulation is calculated to obtain the central arterial pressure waveform. The plurality of steps include defining aUPF module, setting regional boundary conditions, setting a solver to perform calculation, performing blood vessel and blood grid division, loading a load, visually solving central arterial blood pressure waveform and blood vessel deformation parameters and the like, and analyzing results. According to the method, non-invasive operation is performed, and the data display is intuitive and accurate;and at the same time, the simulation change conditions of blood in blood vessels can be observed in real time, which provides a certain basis for the clinical diagnosis, treatment and scientific research of cardiovascular diseases.

The invention discloses a central arterial pressure waveform reconstruction system and method, a peripheral artery pulse wave measurement module of the reconstruction system sends measured peripheral artery pulse waves to a pulse wave correction module for correction, and outputs corrected pulse wave data to a central arterial pressure reconstruction calculation module; and the central arterial pressure reconstruction calculation module is composed of an input layer, a calculation layer and an output layer. The input layer receives the corrected peripheral artery pulse waves and inputs the corrected peripheral artery pulse waves to the calculation layer, the calculation layer is composed of a plurality of long-short-term memory units, and each long-short-term memory unit receives signals of the input layer at the current moment and output of the long-short-term memory unit at the previous moment; each long-short-term memory unit outputs to the output layer and simultaneously serves as the input of the long-short-term memory unit at the next moment; and the output layer outputs the finally reconstructed central arterial pressure pulse wave to a data display module. According to the method, end-to-end central arterial pressure waveform reconstruction can be automatically realized, and the reconstruction accuracy is obviously superior to that of a traditional method.

The application provides a method and device for adjusting blood flow rate under the largest congestion state based on a microcirculation drag index. The method for adjusting the blood flow rate underthe largest congestion state based on the microcirculation drag index comprises the following steps of according to the blood flow rate v, an aortic pressure wave form and physiological parameters, obtaining a microcirculation drag index iFMR in a diastolic phase; if the microcirculation drag index iFMR in the diastolic phase is less than K, then enabling an adjusting parameter r to be 1; and ifthe microcirculation drag index iFMR in the diastolic phase is larger than or equal to K, enabling an adjusting parameter r to be shown as the description, wherein K is a positive number less than 100. For the method disclosed by the invention, according to the physiological parameters, the microcirculation drag index iFMR in the diastolic phase is obtained, then iFMR is compared with K to obtainthe adjusting parameter, and then through the product of the adjusting parameter and the blood flow rate under the largest congestion state, the amended blood flow rate under the largest congestion state is obtained, so that the measuring result is more pointed, the individualization difference is obvious, and the method is more accurate.

The invention belongs to the technical field of medical treatment, and discloses a cardiovascular disease risk control method based on big data. A cardiovascular disease risk control method system based on the big data comprises a heart rate detecting module, a blood pressure detection module, a blood flow velocity detecting module, a single chip microcomputer control module, a cloud service module, a parameter calculation module, an early warning module, a data storage module, a displaying module, a real-time analyzing module, a predicating model module, a data managing module and an analysisresult reporting module. The analyzing and calculation speed of cardiovascular disease risk data can be greatly improved through the cloud service module, and the detecting efficiency is improved; arterial pressure waveform data of a subject is provided and analyzed by the parameter calculation module, and therefore it is determined whether or not the subject experiences an abnormal state. A multivariate statistic model is applied to the arterial pressure waveform data, and therefore cardiovascular parameters of the subject are determined.

The invention provides a method and a device for a blood vessel assessment parameter on the basis of a physiological parameter, and a storage medium. The method for the blood vessel assessment parameter on the basis of the physiological parameter comprises the following steps of: obtaining the physiological parameter; obtaining a blood flow speed v; obtaining an aortic pressure waveform which changes along with time in real time; and according to the blood flow speed v, the aortic pressure waveform and the physiological parameter, obtaining a coronary artery blood vessel assessment parameter.By use of the method, according to the blood flow speed v, the aortic pressure waveform and the physiological parameter, the coronary artery blood vessel assessment parameter is obtained, the personalized measurement of the coronary artery blood vessel assessment parameter is carried out by aiming at patients of different genders and differentiated diseases histories, the method exhibits better pertinence, and the accuracy of the measurement of the coronary artery blood vessel assessment parameter is improved.

A method for determination of cardiac output from a recording of an arterial pressure waveform (10). The method comprises the steps of measuring the patient's peripheral arterial pressure relative to time in order to estimate a central pressure waveform (CPW) and calculating the patient's cardiac output from the CPW using the Water Hammer formula (as defined herein).

The invention discloses a system and method for central arterial pressure waveform reconstruction based on CNN-BiLSTM, and relates to the technical field of artificial intelligence and medical device research and development. The invention includes a data acquisition control module, a radial artery pressure measurement module, a fingertip arterial pressure measurement module, a data processing module, a central arterial pressure calculation module and a data display module. The invention does not need to manually extract features, and does not need to establish an intermediate simulation model and its parameter estimation, and automatically establishes an end-to-end reconstruction model of peripheral blood pressure and central arterial pressure, which effectively improves the reconstruction accuracy of the central arterial pressure waveform. The improvement of the neural network structure improves the model's ability to learn waveform features. Compared with other artificial neural networks, this network has a stronger learning ability for blood pressure waveforms and better reconstruction of central arterial pressure.

The invention discloses an algorithm for predicting abnormal blood pressure causing cerebral apoplexy based on big data and artificial intelligence, and relates to the technical field of blood pressure prediction. The method comprises the following steps: (1) preparing an available clinical database containing arterial pressure waveforms, and training; (2) marking periods of hypotension and non-hypotension in the database to serve as a training data set; (3) processing the arterial pressure waveforms to extract waveform features; and (4) mapping the waveform features to predict the hypotensionevent by using the training data. According to the invention, based on the high-fidelity arterial pressure waveforms, the blood pressure is predicted through the machine learning algorithm, the machine learning is applied to the arterial pressure waveform, the algorithm for predicting the blood pressure is created, the blood pressure change is accurately predicted, and the early warning functionis provided under the condition that the blood pressure is abnormal, so that cerebral apoplexy is effectively prevented.

The invention belongs to the technical field of a medical special bed, and discloses an intelligent special bed for the cardiology department, a control system and a control method. The control systemfor the intelligent special bed for the cardiology department comprises an image acquisition module, a blood pressure detection module, a heart rate detection module, a body temperature detection module, a main control module, an image processing module, a parameter calculation module, a lifting module, an illumination module, a data storage module and a display module. According to the invention, image information loss caused by reduction of a resolution of an output image is made up, a tissue structure reduction degree is high and an image display effect is better; meanwhile, by the parameter calculation module, arterial pressure waveform data of a subject is provided and analyzed so as to determine whether the subject is in an abnormal state. If the subject is determined to be in the abnormal state, a multivariate statistical model is applied to the arterial pressure waveform data so as to determine cardiovascular parameters of the subject.

The present invention relates to multivariate statistical models for detecting vascular states, methods for creating these multivariate statistical models, and methods for using the multivariate statistical models to detect vascular states in a subject. This model is created based on arterial pressure waveform data from a first group of subjects experiencing a particular vascular state and a second group of subjects not experiencing the same vascular state. Multivariate statistical models are built to provide different output values ​​for each set of input data. Thus, when data from a subject under observation is input into the model, the relationship between the model output and the established output for which the model is based will indicate whether the subject experienced the vascular state established by these two groups of subjects.

The invention discloses a cardiac output detector wireless transmission device which is mainly applied to detecting transient temperature of human arterial blood. According to the technical scheme that a physical layer and a data link layer of a CAN (controller area network) protocol are integrated in a CAN bus communication interface, the cardiac output detector wireless transmission device is a main unit capable of receiving and controlling wireless transmission of multiple auxiliary units. The cardiac output detector wireless transmission device is structurally characterized by being composed of an infusion connector, a button cell, a wireless communication module, a wireless communication module shell, a temperature sensor, a PICCO (pulse induced contour crdic output) double-cavity tube, a catheter fixator, and a wireless receiving module and a software program of a cardiac output detector; the cardiac output detector also named as a PICCO catheter before innovation is a measuring instrument used at the front end of the cardiac output monitor; the measuring principle of the cardiac output monitor is that single cardiac output (CO) is measured by adopting a hot dilution method, and continuous cardiac output (ICCO) is acquired by analyzing area under arterial pressure-waveform curves; meanwhile, intrathoracic blood volume (ITBV) and extravascular lung water (EVLW) can be calculated.

The invention provides a method and device for acquiring central arterial pressure and a computer readable storage medium. The method comprises the following steps of: constructing a calculation model by adopting an artificial intelligence algorithm; obtaining the peripheral arterial pressure waveform of a to-be-tested person by adopting a non-invasive measurement method; and inputting the peripheral arterial pressure waveform of the to-be-tested person into the calculation model for calculation, and outputting the central arterial pressure waveform of the to-be-tested person. Compared with a general transfer function method, the scheme considers the difference between individuals. Non-invasive measurement of the central arterial pressure waveform is realized by the scheme. In addition, compared with a scheme for calculating the central arterial pressure through a one-dimensional arterial model, the scheme does not need to solve the one-dimensional model for many times to adjust sensitive parameters, and a large amount of time is saved.

The present application provides a method, device and storage medium for acquiring blood vessel evaluation parameters based on physiological parameters. The method for acquiring coronary artery evaluation parameters based on physiological parameters includes: acquiring physiological parameters; acquiring blood flow velocity v; acquiring a real-time aortic pressure waveform changing with time; The above physiological parameters were used to obtain the evaluation parameters of coronary arteries. According to blood flow velocity v, aortic pressure waveform, and physiological parameters, the application obtains coronary artery assessment parameters, and performs personalized measurement of coronary artery assessment parameters for patients with different genders and differentiated disease histories. It improves the accuracy of the measurement of coronary artery vascular assessment parameters.

The present application provides a method and device for adjusting the blood flow velocity and flow velocity in the state of maximum congestion based on the microcirculation resistance index. The method for adjusting the blood flow velocity in the state of maximum congestion based on the microcirculation resistance index includes: obtaining the diastolic microcirculation resistance index iFMR according to the blood flow velocity v, the aortic pressure waveform, and the influencing parameters; if the diastolic microcirculation resistance If the index iFMR<K, then the adjustment parameter r=1; if the diastolic microcirculation resistance index iFMR≥K, then the adjustment parameter wherein, K is a positive number less than 100. This application obtains the diastolic microcirculation resistance index iFMR according to the influencing parameters; then compares iFMR with K to obtain the adjustment parameters, and then obtains the corrected maximum hyperemia state through the product of the adjustment parameters and the blood flow velocity in the maximum hyperemia state Blood flow velocity, the measurement results are more targeted, individual differences are obvious, and more accurate.

The invention discloses a central arterial blood pressure measurement device, including brachial arterial blood pressure measurement, electrocardiogram measurement, radial artery blood pressure measurement, data processing, pulse wave transit time evaluation, pulse wave reflection coefficient evaluation, central arterial pressure calculation and data display, etc. module; the pulse wave transit time evaluation module is used to obtain the pulse wave transit time; the pulse wave reflection coefficient evaluation module divides the pulse wave into incident waves and reflected waves, and calculates the sum of the reflected wave amplitude and the sum of the incident wave and reflected wave amplitudes. The ratio of pulse wave reflection coefficient is obtained; the central arterial pressure calculation module calibrates the radial artery blood pressure waveform; at the same time, the pulse wave transit time and pulse wave reflection coefficient are input into the mathematical model to calculate the transfer function, and then use the transfer function and the calibrated The radial artery blood pressure waveform was calculated to calculate the central arterial pressure waveform. The invention can significantly improve the measurement accuracy of the central arterial pressure and reduce the measurement error.

In some examples, determining of a heart failure status of a patient using a medical device comprising a plurality of electrodes includes determining an estimated arterial pressure waveform of the patient based on an arterial impedance signal received from at least two of the plurality of electrodes. The estimated arterial pressure waveform may comprise a plurality of arterial pressure cycles. Each of the plurality of arterial pressure cycles may correspond to a different cardiac cycle of a plurality of cardiac cycles of the patient. At least one value of an intrinsic frequency of the corresponding arterial pressure cycle may be determined for at least some of the plurality of cardiac cycles and the heart failure status of the patient may be determined based on the at least one value of the intrinsic frequency.

The invention discloses a non-invasive central aortic blood pressure measuring method and device. The non-invasive central aortic blood pressure measuring method includes, according to a human artery network model based on viscous fluid mechanics, a method of calculating artery network model personalized parameters of a measured person through measured radial artery and brachial artery pulse wave signals and arm blood pressure values, a method of calculating an ascending aorta-radial artery transfer function and a method of calculating central arterial pressure waveforms through measured central arterial pressures. The non-invasive central aortic blood pressure continuous measuring device comprises a pulse wave signal processing and analysis unit and a radial artery and brachial artery pulse wave signal acquisition unit worn on a wrist. The method is different from an existing general transfer function method, the artery network model parameters of each person to be measured are measured and calculated and the artery network model parameters are numerical characteristics of the cardiovascular system states of the person to be measured with the calculated central arterial pressure waveforms, and the method and device has important meanings in prevention, curing and control of cardiovascular diseases, especially high-risk diseases, such as hypertensions and coronary heart diseases.