Vascular parameter monitoring method and vascular parameter monitoring device

Abstract

This application relates to a method and device for monitoring vascular parameters. The method includes: acquiring finger pressure information and finger arterial physiological information during a monitoring period; obtaining the actual value of the oscillation envelope using the finger arterial physiological information, and obtaining the actual value of the pulse transit time using the finger arterial physiological information; obtaining a first model; obtaining a second model; and simultaneously optimizing the objective function using the first and second models to obtain estimated values ​​of vascular parameters during the monitoring period. The objective function is generated based on a first error and a second error, where the first error is obtained from the actual value of the oscillation envelope and the estimated value of the oscillation envelope generated based on the first model, and the second error is obtained from the actual value of the pulse transit time and the estimated value of the pulse transit time generated based on the second model. This method can improve the accuracy and robustness of vascular parameter estimation.

Description

Technical Field

[0001] This application relates to the field of blood pressure monitoring technology, and in particular to a method and device for monitoring vascular parameters. Background Technology

[0002] Blood pressure is a key indicator for the clinical diagnosis and treatment of cardiovascular diseases. Hypertension significantly increases the incidence of various cardiovascular risks, including stroke, coronary artery disease, heart failure, atrial fibrillation, and peripheral vascular disease. Close monitoring of blood pressure trends can lead to a deeper understanding of the pathogenesis of cardiovascular diseases, thereby enabling more precise and effective management and control.

[0003] Mobile devices are now widely used and enable daily monitoring of human health information such as activity levels and heart rate. Blood pressure monitoring technology based on mobile devices can provide users with long-term, continuous feedback, potentially promoting early diagnosis and proactive management of cardiovascular diseases and providing strong protection for people's health.

[0004] Most current smartphone-based blood pressure monitoring research relies on built-in or external sensors in the phone to illuminate the skin and capture the reflected light to detect changes in blood volume in microvessels—a method known as photoplethysmography (PPG). PPG signals show a certain correlation with blood pressure and can be used for blood pressure estimation. However, signal acquisition and analysis are easily affected by external light, motion interference, and other factors, leading to inaccurate blood pressure estimates. Summary of the Invention

[0005] Therefore, it is necessary to provide a vascular parameter monitoring method and device that can improve the accuracy of the detected blood pressure, addressing the aforementioned technical problems.

[0006] In a first aspect, this application provides a method for monitoring vascular parameters, including:

[0007] Acquire finger pressure information and finger arterial physiological information during the monitoring period;

[0008] The actual value of the oscillation envelope is obtained using the physiological information of the finger artery, and the actual value of the pulse transmission time is obtained using the physiological information of the finger artery.

[0009] A first model is obtained, which is based on the finger pressure information and vascular parameters to obtain an oscillation envelope estimate; a second model is obtained, which is based on vascular parameters to obtain a pulse transit time estimate.

[0010] The objective function is optimized by combining the first model and the second model to obtain the estimated values ​​of vascular parameters during the monitoring period. The objective function is generated based on the first error and the second error. The first error is obtained by the actual value of the oscillation envelope and the estimated value of the oscillation envelope generated based on the first model. The second error is obtained by the actual value of the pulse transit time and the estimated value of the pulse transit time generated based on the second model.

[0011] In one embodiment, the finger artery physiological information includes photoplethysmography (PPG) signals, and the actual value of pulse transit time is obtained using the finger artery physiological information, including:

[0012] The maximum and minimum pulse transit times during the monitoring period were obtained based on the photoplethysmography signal.

[0013] The actual value of pulse transit time is obtained by using the maximum pulse transit time and the minimum pulse transit time.

[0014] In one embodiment, obtaining the actual value of the pulse transit time using the maximum pulse transit time and the minimum pulse transit time includes:

[0015] Calculate the ratio of the square of the maximum pulse transit time to the square of the minimum pulse transit time;

[0016] The logarithm of the comparison value is taken to obtain the actual value of the pulse transmission time.

[0017] In one embodiment, obtaining the actual value of the oscillation envelope using finger artery physiological information includes:

[0018] Peak points are detected line by line in the photoplethysmography signal to obtain the upper envelope;

[0019] Valley points are detected line by line in the photoplethysmography signal to obtain the lower envelope;

[0020] The actual value of the oscillation envelope is obtained using the upper and lower envelopes.

[0021] In one embodiment, the vascular parameters further include initial vascular volume parameters and arterial stiffness index parameters, and the steps to obtain the first model include:

[0022] The arterial compliance function is obtained, which characterizes the vascular volume based on the relationship between initial vascular volume parameters, arterial stiffness index parameters, and transmural pressure variables.

[0023] The first model was obtained using the arterial compliance function.

[0024] In one embodiment, the vascular parameters include target systolic blood pressure parameters and target diastolic blood pressure parameters. The transmural arterial pressure variable is related to the target systolic blood pressure parameters, target diastolic blood pressure parameters, and finger pressure information. A first model is obtained using an arterial compliance function, including:

[0025] Based on the arterial compliance function, the vascular volume function corresponding to the target systolic blood pressure parameter is obtained by using finger pressure information and target systolic blood pressure parameter; based on the arterial compliance function, the vascular volume function corresponding to the target diastolic blood pressure parameter is obtained by using finger pressure information and target diastolic blood pressure parameter.

[0026] The first model is obtained based on the vascular volume function corresponding to the target systolic blood pressure parameter and the vascular volume function corresponding to the target diastolic blood pressure parameter.

[0027] In one embodiment, the target systolic blood pressure parameter is related to a maximum systolic blood pressure parameter and a minimum systolic blood pressure parameter, wherein the maximum systolic blood pressure parameter corresponds to a minimum pulse transit time parameter, and the minimum systolic blood pressure parameter corresponds to a maximum pulse transit time parameter. The step of obtaining the second model includes:

[0028] The pulse wave propagation velocity function is obtained based on the arterial compliance function;

[0029] The pulse transmission time function is obtained by using the pulse wave transmission velocity function and the pulse transmission distance;

[0030] Based on the pulse transit time function, the maximum pulse transit time function is determined using the minimum systolic blood pressure parameter, and the minimum pulse transit time function is determined using the maximum systolic blood pressure parameter, so as to obtain the second model using the maximum transit time function and the minimum pulse transit time function.

[0031] In one embodiment, a second model is obtained using the maximum transit time function and the minimum pulse transit time function, including:

[0032] Obtain the ratio of the square of the maximum transmission time function to the square of the minimum transmission time function;

[0033] The logarithm of the comparison value is taken to obtain the second model.

[0034] In one embodiment, obtaining the actual value of pulse transit time using finger artery physiological information includes:

[0035] The phase difference of the pulse wave at different positions of the finger is obtained by using photoplethysmography signals, so as to obtain the actual value of the pulse transmission time.

[0036] In one embodiment, the finger artery physiological information also includes an electrocardiogram signal, and the step of obtaining the actual value of pulse transit time using the finger artery physiological information includes:

[0037] The first feature point of the pulse wave of the finger at a single location is obtained by using photoplethysmography signal, and the second feature point of the electrocardiogram signal is obtained.

[0038] The phase difference between the first feature point and the second feature point is obtained to obtain the actual value of the pulse transmission time.

[0039] Secondly, this application also provides a vascular parameter monitoring device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0040] Acquire finger pressure information and finger arterial physiological information during the monitoring period;

[0041] The actual value of the oscillation envelope is obtained using the physiological information of the finger artery, and the actual value of the pulse transmission time is obtained using the physiological information of the finger artery.

[0042] A first model is obtained, which is based on the finger pressure information and vascular parameters to obtain an oscillation envelope estimate; a second model is obtained, which is based on vascular parameters to obtain a pulse transit time estimate.

[0043] The objective function is optimized by combining the first model and the second model to obtain the estimated values ​​of vascular parameters during the monitoring period. The objective function is generated based on the first error and the second error. The first error is obtained by the actual value of the oscillation envelope and the estimated value of the oscillation envelope generated based on the first model. The second error is obtained by the actual value of the pulse transit time and the estimated value of the pulse transit time generated based on the second model.

[0044] The aforementioned vascular parameter monitoring method and device acquire finger pressure information and finger arterial physiological information during the monitoring period. The finger arterial physiological information is used to obtain the actual value of the oscillation envelope, and the finger arterial physiological information is used to obtain the actual value of the pulse transit time. This facilitates subsequent estimation of vascular parameters using the actual values ​​of the oscillation envelope and pulse transit time. A first model is then obtained, which estimates the oscillation envelope based on finger pressure information and vascular parameters. A second model is then obtained, which estimates the pulse transit time based on vascular parameters. This allows for constraint on the estimation of vascular parameters using two models, resulting in more accurate estimates. To obtain the estimated values ​​of vascular parameters, the first and second models can be simultaneously optimized using an objective function to obtain the estimated values ​​of vascular parameters during the monitoring period. The objective function is generated based on a first error and a second error. The first model generates the estimated value of the oscillation envelope, with the first error derived from the actual value and the estimated value of the oscillation envelope. The second model generates the estimated value of the pulse transit time, with the second error derived from the actual value and the estimated value of the pulse transit time. Compared to using a single model to estimate vascular parameters, this method obtains estimated values ​​of vascular parameters by simultaneously optimizing the objective function of two models. It also obtains blood pressure based on finger pressure information during the monitoring period. This method can adapt to the physiological conditions of more organisms and can adapt to changes in vascular state without calibration, thereby improving the accuracy and robustness of vascular parameter estimation and increasing the efficiency of vascular parameter estimation. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 This is a diagram of an application device for a vascular parameter monitoring method in one embodiment;

[0047] Figure 2 This is a diagram of an application device for a vascular parameter monitoring method in another embodiment;

[0048] Figure 3 This is a flowchart illustrating a vascular parameter monitoring method in one embodiment;

[0049] Figure 4 This is a flowchart illustrating the step of obtaining the first model in one embodiment;

[0050] Figure 5This is a flowchart illustrating the step of obtaining the first model in another embodiment;

[0051] Figure 6 This is a flowchart illustrating the step of obtaining the second model in one embodiment;

[0052] Figure 7 This is a schematic diagram of the oscillation envelope in one embodiment;

[0053] Figure 8 This is a schematic diagram of a vascular parameter monitoring device in one embodiment;

[0054] Figure 9 This is a schematic diagram of a vascular parameter monitoring device in another embodiment;

[0055] Figure 10 This is a schematic diagram of a vascular parameter monitoring device in yet another embodiment;

[0056] Figure 11 Used in one embodiment Figure 10 The diagram shown illustrates the operation of the vascular parameter monitoring device.

[0057] Figure 12 for Figure 10 A schematic diagram of the multi-mode integration module in the diagram;

[0058] Figure 13 This is a schematic diagram of the screen of a vascular parameter monitoring device in one embodiment;

[0059] Figure 14 This is an internal structural diagram of a vascular parameter monitoring device in one embodiment. Detailed Implementation

[0060] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0061] The vascular parameter monitoring method provided in this application embodiment can be applied to, for example... Figure 1The illustrated vascular parameter monitoring device includes a pressure acquisition module 102, an arterial physiological information acquisition module 104, a data processing module 106, and a vascular parameter acquisition module 108. The pressure acquisition module 102 acquires finger pressure information during the monitoring period. The arterial physiological information acquisition module 104 acquires finger arterial physiological information during the monitoring period. The data processing module 106 processes the acquired information. For example, the data processing module 106 uses the finger arterial physiological information to obtain the actual value of the oscillation envelope and the actual value of the pulse transit time. The vascular parameter acquisition module 108 obtains a first model and a second model, and obtains estimated values ​​of the oscillation envelope and pulse transit time based on the first and second models, respectively. The vascular parameter acquisition module 108 also performs objective function optimization by simultaneously using the first and second models to obtain estimated values ​​of vascular parameters during the monitoring period.

[0062] The physiological information of the finger arteries can include electrocardiogram (ECG) signals and photoplethysmography (PPG) signals. The ECG signal refers to the electrocardiogram signal. For example... Figure 2 As shown, the pressure acquisition module 202 may include a pressure sensor. The arterial physiological information acquisition module 204 may include a PPG sensor and an ECG sensor. Figure 2 In the illustrated embodiment, processing device A and processing device C can be located in the same device or in different devices. The data processing module may include processing device A from the data acquisition module and a mobile terminal module. The vascular parameter acquisition module may be... Figure 2 The system includes a vascular parameter calculation module. The data processing module within the data acquisition module processes the information collected by the sensors, such as through filtering. The data transmission module then sends the processed information to the mobile terminal module. The mobile terminal module displays the processed information from each sensor on its interface. The terminal can be, for example, a mobile computer, a mobile phone, or a wearable device. The vascular parameter calculation module can estimate vascular parameters using information sent from either the mobile terminal module or the data acquisition module. The data storage module within the vascular parameter calculation module stores the received information in a memory for later analysis of sensor data collected over a period of time. The model algorithm deployment module deploys the model and analyzes the information stored in the memory to estimate vascular parameters.

[0063] In other words, such as Figure 2As shown, the processor can also send the signals collected by the sensor to a smart terminal for processing to obtain blood pressure estimates and other vascular parameter estimates. In this case, the data acquisition module in the processor includes data processing and data transmission. It connects to the Android / iOS mobile terminal module via Bluetooth. After the mobile terminal receives the data, the processor B deployed within it includes dynamic data display, data transmission, and blood pressure estimation. Optionally, processor B can also send signals to the cloud to estimate blood pressure. For example, the cloud-based blood pressure calculation module receives data from the Android / iOS terminal via the HTTP protocol and executes the functions of processor C in the cloud, including data storage and blood pressure estimation.

[0064] In other embodiments, the arterial physiological information acquisition module may include multiple PPG sensors to acquire PPG signals from different fingers.

[0065] In one exemplary embodiment, such as Figure 3 As shown, a method for monitoring vascular parameters is provided, which can be applied to... Figure 1 The process is illustrated using the processor in the example, including steps 302 to 308.

[0066] in:

[0067] Step 302: Obtain finger pressure information and finger arterial physiological information during the monitoring period.

[0068] The monitoring period refers to the time during which the subject uses the application device to monitor their blood pressure. The subject refers to the living organism whose blood pressure is being measured, such as a human. Finger pressure information refers to the information obtained by the pressure sensor when the subject presses it. Finger pressure information, for example, refers to the force exerted on the pressure sensor when the subject presses it. Finger arterial physiological information can refer to the subject's ECG signal acquired by the ECG sensor and / or the PPG signal acquired by the PPG sensor.

[0069] During blood pressure monitoring, the processor receives signals from various sensors to obtain finger pressure and finger artery physiological information. The finger artery physiological information can be used to obtain the subject's pulse transmission information. The finger pressure information can be used to obtain oscillation envelope information.

[0070] Step 304: During finger pressing, obtain the actual value of the oscillation envelope using the physiological information of the finger artery, and obtain the actual value of the pulse transmission time using the physiological information of the finger artery.

[0071] The monitoring period is during finger pressure. The oscillation envelope refers to the envelope of the arterial blood flow oscillation signal. This envelope is formed by connecting the peak and trough values ​​of the oscillation signal, reflecting the trend of blood flow oscillation amplitude changes over time.

[0072] In blood pressure monitoring, as finger pressure changes, the blood flow in the arteries produces periodic oscillations with each heartbeat. The amplitude of these oscillations varies with finger pressure. The oscillation envelope, formed by connecting the points of maximum and minimum amplitude of these oscillations, creates a curve that illustrates how the oscillation amplitude changes with finger pressure.

[0073] The oscillation envelope is crucial in blood pressure measurement because it helps determine systolic and diastolic blood pressure. Systolic pressure typically corresponds to the point where the oscillation begins, while diastolic pressure corresponds to the point where the oscillation amplitude disappears. Therefore, in this embodiment, the oscillation envelope can be used to estimate blood pressure.

[0074] The actual value of pulse transmission time refers to a value related to the actual pulse transmission time, such as a value obtained by performing mathematical operations on the actual pulse transmission time.

[0075] In this embodiment, the physiological information of the finger artery includes the PCG signal. After the processor obtains the PPG signal, it performs peak-valley detection and curve fitting on the obtained PPG signal to obtain the upper and lower envelopes, and then obtains the oscillation envelope. Thus, the oscillation envelope value corresponding to each time point within the monitoring period can be obtained.

[0076] In this embodiment, the processor can obtain finger pressure information corresponding to each time point within the monitoring period. The processor can also analyze the obtained finger pressure information and PPG signal to obtain the relationship between the finger pressure information and the PPG signal, thereby obtaining the relationship between the finger pressure information and the oscillation envelope. Subsequently, the estimated value of the oscillation envelope and the actual value of the oscillation envelope can be mapped based on the finger pressure information in subsequent steps.

[0077] To obtain the pulse transit time (PRT) during the monitoring period, i.e., the actual value of the PRT, the processor can perform feature detection on the acquired ECG and PPG signals. In other embodiments, the processor can perform feature detection on multiple PPG signals acquired by multiple PPG sensors to obtain the PRT. These PPG signals correspond to signals from different body parts of the subject.

[0078] Step 306: Obtain the first model and then the second model.

[0079] The first model estimates the oscillation envelope based on finger pressure information and vascular parameters. The second model estimates the pulse transit time based on vascular parameters. In other words, the first model represents the relationship between finger pressure information, vascular parameters, and oscillation envelope parameters, while the second model represents the relationship between vascular parameters and pulse transit time parameters.

[0080] In this embodiment, two models are obtained and fused to estimate the subject's blood pressure, reducing the error caused by estimating blood pressure using a single model. The first model establishes the relationship between the oscillation envelope and vascular parameters, while the second model establishes the relationship between pulse transit time and vascular parameters. The oscillation envelope in the first model is also correlated with finger pressure.

[0081] The first model was used to establish the relationship between the subject's finger pressure, oscillation envelope, and vascular parameters during the monitoring period. The second model was used to establish the relationship between the subject's vascular parameters and pulse transit time during the monitoring period.

[0082] Step 308: Combine the first and second models to optimize the objective function to obtain estimated values ​​of vascular parameters during the monitoring period.

[0083] The objective function is generated based on a first error and a second error. The first error is obtained from the actual value of the oscillation envelope and the estimated value of the oscillation envelope generated based on the first model. The second error is obtained from the actual value of the pulse transit time and the estimated value of the pulse transit time generated based on the second model. In other words, the estimated value of the oscillation envelope is generated based on the first model, and the estimated value of the pulse transit time is generated based on the second model.

[0084] The objective function of the first and second models is optimized simultaneously to obtain estimated values ​​of vascular parameters during the monitoring period. This can be achieved by using nonlinear least squares to solve for the unknown parameters in the first and second models. Unknown parameters include, for example, those used to calculate systolic blood pressure, diastolic blood pressure, vascular volume, and arterial stiffness.

[0085] Optionally, during the solution process, the estimated values ​​of finger pressure information and blood pressure parameters can be substituted into the first model to obtain the oscillation envelope estimate, and the estimate can be substituted into the second model to obtain the pulse transmission estimate. The target error is obtained based on the first error between the estimated and actual oscillation envelope values, and the second error between the estimated and actual pulse transmission values. The estimated vascular parameters corresponding to the target error that meets the conditions are used as the estimated vascular parameters for the monitoring period. Vascular parameters include at least systolic and diastolic blood pressure parameters. The unknown parameters in the second model are the same as those in the first model. The unknown parameters in the first and second models are solved using the nonlinear least squares method to obtain the estimated vascular parameters.

[0086] When the target error meets the conditions, such as when the target error is the minimum error, the estimated value of the vascular parameters corresponding to the target error is used as the final estimated value of the vascular parameters during the monitoring period, such as the estimated value of systolic blood pressure and the estimated value of diastolic blood pressure.

[0087] In the aforementioned vascular parameter monitoring method, finger pressure information and finger artery physiological information are acquired during the monitoring period. The actual value of the oscillation envelope is obtained using the finger artery physiological information, and the actual value of the pulse transit time is also obtained using the finger artery physiological information. An estimated value of the oscillation envelope is obtained based on a first model and finger pressure information. The first model represents the relationship between finger pressure information, vascular parameters, and oscillation envelope parameters. The actual value of the pulse transit time is obtained based on a second model, which represents the relationship between vascular parameters and pulse transit time parameters. This allows for the acquisition of vascular parameters based on constraints from two models, resulting in more accurate vascular parameters. To obtain vascular parameters, the estimated values ​​of the vascular parameters are substituted into the first model to obtain the estimated value of the oscillation envelope, and then substituted into the second model to obtain the estimated value of the pulse transit time. A target error is obtained based on the first error between the estimated value of the oscillation envelope and the actual value of the oscillation envelope, and the second error between the estimated value of the pulse transit time and the actual value of the pulse transit time. The estimated value of the vascular parameters corresponding to the target error that meets the conditions is used as the blood pressure during the monitoring period. Compared to using the first model alone, this method adds a second model for parameter optimization, enabling the acquisition of more accurate vascular parameters. Compared to using the second model alone, this method obtains blood pressure based on finger pressure information, which can adapt to changes in vascular condition without calibration, thereby improving the accuracy and robustness of blood pressure estimation.

[0088] In some embodiments, the processor can utilize the relationship between vascular volume and the pressure difference across the arterial wall to obtain a first model, namely an oscillating envelope model. When the finger is not under pressure, the value of the oscillating envelope can be obtained based on the vascular volume corresponding to the maximum and minimum arterial pressure, i.e., the vascular volume at systolic pressure and the vascular volume at diastolic pressure. Optionally, the value of the oscillating envelope can be the difference between the vascular volume at systolic pressure and the vascular volume at diastolic pressure.

[0089] Therefore, to obtain the first model, it is necessary to first determine the relationship between transmural pressure and vascular volume. For example... Figure 4 As shown, the steps to obtain the first model include steps 402 to 404. Wherein:

[0090] Step 402: Obtain the arterial compliance function.

[0091] Among them, the arterial compliance function characterizes the vascular volume based on the relationship between the initial vascular volume parameters, the arterial stiffness index parameters, and the transmural pressure variable of the arterial vessel.

[0092] Step 404: Obtain the first model using the arterial compliance function.

[0093] In this embodiment, the arterial compliance function is obtained by multiplying the initial vascular volume parameter and the exponent of the arterial stiffness index parameter and the arterial transmural pressure variable. In practical applications, the arterial transmural pressure variable can be obtained by processing the acquired signal. There are at least two arterial stiffness index parameters. When there are two arterial stiffness index parameters, one of them can be used to represent the vascular volume when the arterial transmural pressure is less than zero; when the arterial transmural pressure is greater than zero, two arterial stiffness index parameters are needed to represent the vascular volume.

[0094] In one embodiment, the arterial compliance function is represented in exponential form based on the relationship between transmural pressure and arterial volume (same as vessel volume). Optionally, the formula for the arterial compliance function is as follows:

[0095]

[0096] Among them, P t V represents the transmural pressure of the artery, i.e., the pressure difference across the arterial wall; a and b are arterial stiffness parameters; ao This represents the initial vascular volume.

[0097] Arterial transmural pressure can be greater than zero or less than zero, depending on the characteristics of the artery itself and the pressure it experiences. For example, when the pressure on an artery is too high, the transmural pressure may be less than zero. Obtain vascular volume. When the pressure on the artery is not high, the transmural pressure of the artery is still greater than zero. At this point, based on... Obtain vascular volume.

[0098] Since the oscillation envelope is related to changes in blood vessel volume, the first model can be obtained using the arterial compliance function.

[0099] In this embodiment, the relationship between arterial stiffness, transmural pressure, and vascular volume is characterized by an arterial compliance function. Since transmural pressure is correlated with systolic and diastolic blood pressure, and vascular volume is correlated with the oscillatory envelope, the relationship between the oscillatory envelope and systolic and diastolic blood pressure (i.e., the first model) can be obtained based on the arterial compliance function. Furthermore, the estimated values ​​of systolic and diastolic blood pressure can be obtained using this first model. Moreover, because the arterial compliance function also includes arterial stiffness and vascular volume, this embodiment can also be used to estimate arterial stiffness and vascular volume.

[0100] As mentioned earlier, the transmural pressure in the arterial compliance function is related to systolic blood pressure, diastolic blood pressure, and finger pressure. Therefore, estimates of the subject's systolic and diastolic blood pressure can be obtained based on the arterial compliance function. In establishing the first model, the target systolic blood pressure parameter is used to characterize the estimated systolic blood pressure of the subject, and the target diastolic blood pressure parameter is used to characterize the estimated diastolic blood pressure of the subject. For example... Figure 5 As shown, obtaining the first model using the arterial compliance function includes steps 502 to 504. Wherein:

[0101] Step 502: Based on the arterial compliance function, obtain the vascular volume function corresponding to the target systolic blood pressure parameter using finger pressure information and target systolic blood pressure parameter; based on the arterial compliance function, obtain the vascular volume function corresponding to the target diastolic blood pressure parameter using finger pressure information and target diastolic blood pressure parameter.

[0102] Step 504: Obtain the first model based on the vascular volume function corresponding to the target systolic blood pressure parameter and the vascular volume function corresponding to the target diastolic blood pressure parameter.

[0103] In this embodiment, finger pressure is obtained based on finger pressure information. Since finger pressure may be greater than systolic blood pressure, may fall between systolic and diastolic blood pressure, or may be less than diastolic blood pressure, the transmural pressure of the artery may be greater than or less than zero. Furthermore, the method of calculating vascular volume is related to whether the transmural pressure of the artery is greater than zero. That is, when the transmural pressure of the artery is less than zero, it is based on... Obtain vascular volume. Based on the transmural pressure of the arterial vessel being greater than zero. Obtain vascular volume.

[0104] Therefore, the formula for the first model can vary depending on whether the transmural pressure of the artery is greater than zero.

[0105] Specifically, when the finger pressure is greater than the systolic blood pressure, the corresponding transmural pressure of the artery is less than zero. Therefore, the vascular volume function corresponding to the target systolic blood pressure parameter is obtained based on the arterial compliance function corresponding to a transmural pressure of less than zero. That is... Since diastolic blood pressure is less than systolic blood pressure, the transmural arterial pressure in the vascular volume function corresponding to diastolic blood pressure is also less than zero. Therefore, the vascular volume function corresponding to the target diastolic blood pressure parameter is obtained based on the arterial compliance function corresponding to a transmural arterial pressure of less than zero.

[0106] When the finger pressure is less than the systolic blood pressure but greater than the diastolic blood pressure, the corresponding transmural pressure of the artery is greater than zero. Therefore, the vascular volume function corresponding to the target systolic blood pressure parameter is obtained based on the arterial compliance function corresponding to a transmural pressure greater than zero. At this point, the transmural pressure of the artery in the vascular volume function corresponding to the diastolic pressure is less than zero. Therefore, the vascular volume function corresponding to the target diastolic pressure parameter is obtained based on the arterial compliance function corresponding to a transmural pressure of less than zero.

[0107] When finger pressure is less than diastolic blood pressure, the transmural arterial pressure in the vascular volume function corresponding to diastolic blood pressure is greater than zero. Therefore, the vascular volume function corresponding to the target diastolic blood pressure parameter is obtained based on the arterial compliance function corresponding to a transmural arterial pressure greater than zero. Since diastolic blood pressure is less than systolic blood pressure, the transmural pressure of the artery corresponding to systolic blood pressure is also greater than zero. Therefore, the vascular volume function corresponding to the target systolic blood pressure parameter is obtained based on the arterial compliance function corresponding to the transmural pressure of the artery being greater than zero.

[0108] Right now

[0109] The formula for the first model can be as follows:

[0110]

[0111] Among them, P f Finger pressure; a and b are arterial stiffness parameters; SBP is systolic blood pressure; DBP is diastolic blood pressure; k is the proportionality coefficient between waveform oscillation amplitude and arterial volume oscillation amplitude; V ao This represents the initial vascular volume.

[0112] In this embodiment, a first model is constructed based on the arterial compliance function to obtain the relationship between the oscillation envelope and systolic and diastolic blood pressure. Thus, after obtaining the actual value of the oscillation envelope of the subject during the monitoring period, the estimated values ​​of systolic and diastolic blood pressure can be obtained based on the actual value of the oscillation envelope and the first model. This embodiment uses oscillometric methods to estimate vascular parameters, which is feasible and accurate.

[0113] In addition to obtaining the relationship between systolic blood pressure, diastolic blood pressure, and oscillatory envelope based on the first model, the relationship between vascular parameters and pulse transit time is also obtained based on the second model. This allows for the fusion of the first and second models to estimate the subject's vascular parameters. Using two relationships to constrain the estimation of vascular parameters improves the robustness of the estimated parameters and reduces the influence of a single model on the estimation. In some embodiments, pulse transit time needs to be represented using pulse transit distance, but the first model does not contain parameters related to pulse transit distance. Therefore, when building the second model, parameters not present in the first model need to be eliminated to better fuse the two models, reduce unnecessary parameter interference with vascular parameter estimation, and thus lower the difficulty of vascular parameter estimation. Figure 6 As shown, the specific steps for establishing the second model are as follows:

[0114] Step 602: Obtain the pulse wave transmission velocity function based on the arterial compliance function.

[0115] Step 604: Obtain the pulse transmission time function using the pulse wave transmission velocity function and the pulse transmission distance.

[0116] Step 606: Based on the pulse transit time function, determine the maximum pulse transit time function using the minimum systolic blood pressure parameter, and determine the minimum pulse transit time function using the maximum systolic blood pressure parameter, so as to obtain the second model using the maximum transit time function and the minimum pulse transit time function.

[0117] Optionally, pulse transmission time can be obtained from pulse transmission distance and pulse transmission velocity. Pulse transmission velocity can be obtained from blood density, vascular volume, and transmural pressure of the artery. Optionally, pulse transmission velocity can be expressed by the following formula:

[0118]

[0119] Where V represents blood vessel volume, P represents arterial transmural pressure, and ρ represents blood density.

[0120] Substituting the arterial compliance function into the above equation, and combining this with the fact that pulse transit time can be obtained from pulse transit distance and pulse transit velocity, we can obtain the following formula for pulse transit time:

[0121]

[0122] Where L is the transmission distance from the heart to the finger, ρ is the blood density, a and b are arterial stiffness parameters, and b a (t) represents the transmural pressure of the artery.

[0123] Since the application device in this embodiment makes it difficult to observe pulse transmission distance and blood density, in order to eliminate pulse transmission distance and blood density in the second model, the obtained oscillation envelope information, pulse transmission information, and finger pressure information can be used to estimate vascular parameters. The actual pulse information can be obtained based on two pulse transmission times. For example, it can be the maximum pulse transmission time and the minimum pulse transmission time. In this way, pulse transmission distance and blood density can be eliminated based on two pulse transmission times. In this embodiment, the two pulse transmission times can be squared and then divided. For details on how to obtain the second model, please refer to the following steps:

[0124] Step 610: Obtain the ratio of the square of the maximum transmission time function to the square of the minimum transmission time function.

[0125] Step 612: Take the logarithm of the comparison values ​​to obtain the second model. The unknown parameters in the second model are the same as the unknown parameters in the first model.

[0126] Among them, the unknown parameters refer to the target systolic blood pressure parameter, the target diastolic blood pressure parameter, the arterial stiffness parameter, and the vascular volume parameter.

[0127] In this embodiment, the maximum transit time function and the minimum transit time function are selected to construct the second model, where the maximum transit time corresponds to the minimum systolic blood pressure, and the minimum transit time corresponds to the maximum systolic blood pressure. This second model can thus characterize the relationship between pulse transmission information and vascular parameters, and can be combined with the first model to obtain estimated values ​​of vascular parameters.

[0128] Specifically, the maximum and minimum transmission time functions can be obtained based on the formula for pulse transmission time. Then, the ratio of the squares of the maximum and minimum transmission time functions can be obtained, thus yielding a second model that eliminates pulse transmission distance and blood density. To simplify the model calculation, the logarithm of the squared ratio can be taken. Since transmural arterial pressure is related to systolic blood pressure, the formula for the second model can be as follows:

[0129]

[0130] Where a and b are arterial stiffness parameters. Since SBP and PTT are inversely proportional, SBP... max Corresponding PTT min SBP min Corresponding PTT max .

[0131] Optionally, since transmural arterial pressure is related not only to systolic blood pressure but also to diastolic blood pressure, a second model can be obtained using diastolic blood pressure-related parameters.

[0132] Since the second model requires the use of the maximum and minimum systolic blood pressure parameters, the target systolic blood pressure parameter in the first model can be obtained based on the average of the maximum and minimum systolic blood pressure parameters.

[0133] In this embodiment, by processing the maximum and minimum transit time functions, parameters not present in the first model are eliminated from the second model. This ensures that the second model has no redundant unknown parameters compared to the parameters in the first model, thereby facilitating the subsequent estimation of vascular parameters (e.g., blood pressure, vascular volume, arterial stiffness) and reducing the impact of redundant parameters on blood pressure estimation. Furthermore, combining the first and second models to estimate vascular parameters improves the accuracy and robustness of vascular parameter estimation.

[0134] After establishing the first and second models, the objective function can be optimized using the nonlinear least squares method to estimate the arterial stiffness parameters, systolic blood pressure, and diastolic blood pressure. The specific model function can be:

[0135]

[0136] in, This represents the error between the physical model and the actual measured value of the oscillation envelope. OMWE(t) represents the error between the physical model of the pulse transmission method and the actual measured value, and OMWE(t) represents the oscillation envelope obtained from the actual measurement (the actual value of the oscillation envelope). is the estimated value of the first model; a and b are arterial stiffness parameters. The pulse transmission estimate for the second model. The actual value of pulse transit time, SBP is systolic blood pressure, DBP is diastolic blood pressure, k is the proportionality coefficient between waveform oscillation amplitude and arterial volume oscillation amplitude, and V ao The initial blood vessel volume is denoted by λ. λ is the weight ratio of the loss functions fitted by the OMWE function and the pulse transit time function. The weighting factor can be set to 1.

[0137] The above describes the process of establishing the first and second models. After establishing the first and second models, the following content explains how to estimate the corresponding values ​​of vascular parameters based on the first and second models during the monitoring period.

[0138] As mentioned above, parameter estimation requires obtaining the actual values ​​of the oscillation envelope and pulse transit time. In an exemplary embodiment, the actual pulse transit time can be obtained using both ECG and PPG signals, or multiple PPG signals. Since the pulse transit estimate in the second model requires two pulse transit times, the processor needs to obtain at least two actual pulse transit times using the PPG sensor. Based on the correspondence between maximum systolic blood pressure and minimum actual pulse transit time, and vice versa, the processor can obtain the maximum and minimum actual pulse transit times of the subject during the monitoring period to obtain two actual pulse transit times. The processor can then use these two actual pulse transit times to obtain the actual pulse transit time value. The actual pulse transit time value is a value related to pulse transit time. For example, it can be the ratio of the maximum to the minimum actual pulse transit time. In this embodiment, the actual pulse transit time value is used in conjunction with the pulse transit estimate from the second model to estimate blood pressure. Obtaining the actual value of pulse transit time using finger artery physiological information includes steps 620 to 622. Wherein:

[0139] Step 620: Obtain the maximum and minimum pulse transit times within the monitoring period based on the photoplethysmography signal.

[0140] Step 622: Obtain the actual value of pulse transit time using the maximum pulse transit time and the minimum pulse transit time.

[0141] As mentioned above, the pulse transit time estimate in the second model can be obtained based on the maximum and minimum transit time functions. To enable the estimation of blood pressure (e.g., systolic and diastolic pressure) using a second error between the estimated and actual pulse transit times, the actual pulse transit time should correspond to the estimated pulse transit time. Therefore, the processor can acquire the maximum and minimum transit times within the monitoring period based on the photoplethysmography signal and use these times to obtain the actual pulse transit time. In some embodiments, the actual pulse transit time can be obtained by taking the ratio of the squares of the maximum and minimum pulse transit times. In other embodiments, the actual pulse transit time can be obtained by taking the logarithm of the comparison values. This reduces the complexity of the second model.

[0142] In some embodiments, the application device does not include an ECG sensor but includes two or more PPG sensors. In this case, the processor can obtain the maximum or minimum pulse transit time by using the phase difference of the pulse wave at different locations of the finger obtained from the photoplethysmography signal.

[0143] In other embodiments, the application device includes an ECG sensor and a PPG sensor. In this case, the processor can obtain the maximum or minimum pulse transit time using a first feature point of the obtained ECG signal and a second feature point of the finger PPG signal obtained at a single location; the phase difference between the first and second feature points is obtained to obtain the first or second pulse transit time, and thus the actual value of the pulse transit time.

[0144] In this embodiment, to make the estimated blood pressure value more accurate, in addition to obtaining the actual value of pulse transit time, it is also necessary to obtain the actual value of oscillation envelope using finger artery physiological information. Finger artery physiological information can refer to the PPG signal. Obtaining the actual value of oscillation envelope using finger artery physiological information includes steps 710 to 714. Wherein:

[0145] Step 710: Detect the peak points of each photoplethysmography signal to obtain the upper envelope.

[0146] Step 712: Detect the valley points of the photoplethysmography signal line by line to obtain the lower envelope.

[0147] Step 714: Obtain the actual value of the oscillation envelope using the upper and lower envelopes.

[0148] Among them, such as Figure 7 As shown, the oscillation envelope 701 represents the actual value of the oscillation envelope, the finger pressure curve 702 represents the finger pressure, and the oscillation waveform 703 represents the PPG signal. The processor can detect the peak points (maximum points) of each PPG signal to obtain the upper envelope. It can also detect the valley points (minimum points) of each PPG signal to obtain the lower envelope. The actual value of the oscillation envelope is then obtained using the upper and lower envelopes. The value of the oscillation envelope can, for example, be the difference between the corresponding upper and lower envelope values.

[0149] In this embodiment, by performing feature point detection on the PPG signal, the upper and lower envelopes are obtained, and then the oscillation envelope is obtained, so that the PPG sensor can be used to achieve cuffless blood pressure estimation without reducing the accuracy of blood pressure estimation.

[0150] In one embodiment, the subject presses their finger on the pressure sensor of the application device and touches the ECG and PPG sensors of the application device with other fingers. The processor then receives the pressure, ECG, and PPG signals collected by each sensor. The processor then processes these signals. The pressure and PPG signals are processed to obtain the actual oscillation envelope. The PPG and ECG signals are processed to obtain the maximum and minimum pulse transit times. The maximum and minimum pulse transit times are divided and their logarithms are taken to obtain the actual pulse transit time. The finger pressure corresponding to the pressure signal is substituted into the oscillation envelope model to obtain the first model. A second model is obtained based on the maximum and minimum pulse transit time parameters. The objective function is optimized using a nonlinear least squares method to obtain estimates of systolic blood pressure, diastolic blood pressure, arterial stiffness, and vascular volume. The objective function is a joint function of the oscillation envelope estimation error and the pulse transit estimation error. The oscillation envelope estimation error is the deviation between the actual oscillation envelope value and the estimated oscillation envelope value obtained based on the first model. The pulse transmission estimation error is the deviation between the actual pulse transmission time and the pulse transmission estimate obtained based on the second model.

[0151] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0152] Based on the same inventive concept, this application also provides a vascular parameter monitoring device for implementing the vascular parameter monitoring method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations of the one or more vascular parameter monitoring device embodiments provided below can be found in the limitations of the vascular parameter monitoring method described above, and will not be repeated here.

[0153] In one exemplary embodiment, a vascular parameter monitoring device is provided, comprising: a pressure acquisition module, an arterial physiological information acquisition module, a data processing module, and a blood pressure acquisition module, wherein:

[0154] The pressure acquisition module is used to acquire finger pressure information during the monitoring period;

[0155] The arterial physiological information acquisition module is used to acquire finger arterial physiological information during the monitoring period;

[0156] The data processing module is used to obtain a first model based on a first model and finger pressure information, and to obtain a second model based on a second model. The first model represents the relationship between finger pressure information, vascular parameters and oscillation envelope, and the second model represents the relationship between vascular parameters and pulse transmission time.

[0157] The blood pressure acquisition module is used to substitute the estimated values ​​of vascular parameters into the first model to obtain the oscillation envelope estimate, and substitute the estimate into the second model to obtain the pulse transmission estimate. Based on the first error between the oscillation envelope estimate and the actual value of the oscillation envelope, and the second error between the pulse transmission estimate and the actual value of the pulse transmission time, the target error is obtained. The estimated values ​​of vascular parameters corresponding to the target error that meet the conditions are used as the blood pressure during the monitoring period. The blood pressure includes at least systolic blood pressure and diastolic blood pressure.

[0158] In one embodiment, the arterial physiological information acquisition module is used to acquire the maximum pulse transit time and minimum pulse transit time within the monitoring period based on the photoplethysmography signal; and to acquire the actual value of the pulse transit time using the maximum pulse transit time and the minimum pulse transit time.

[0159] In one embodiment, the arterial physiological information acquisition module is used to calculate the ratio of the square of the maximum pulse transit time to the square of the minimum pulse transit time; and take the logarithm of the ratio to obtain the actual value of the pulse transit time.

[0160] In one embodiment, the arterial physiological information acquisition module is used to detect peak points of the photoplethysmography signal line by line to obtain the upper envelope; to detect valley points of the photoplethysmography signal line by line to obtain the lower envelope; and to obtain the actual value of the oscillation envelope using the upper envelope and the lower envelope.

[0161] In one embodiment, the data processing module is used to obtain an arterial compliance function, which characterizes the vascular volume based on the relationship between the initial vascular volume parameter, the arterial stiffness index parameter, and the arterial transmural pressure variable; and the first model is obtained using the arterial compliance function.

[0162] In one embodiment, the data processing module is used to obtain a vascular volume function corresponding to the target systolic blood pressure parameter based on the arterial compliance function, using the finger pressure information and the target systolic blood pressure parameter; to obtain a vascular volume function corresponding to the target diastolic blood pressure parameter based on the arterial compliance function, using the finger pressure information and the target diastolic blood pressure parameter; and to obtain the first model based on the vascular volume function corresponding to the target systolic blood pressure parameter and the vascular volume function corresponding to the target diastolic blood pressure parameter.

[0163] In one embodiment, the data processing module is used to obtain a pulse wave velocity function based on the arterial compliance function; obtain a pulse wave transmission time function using the pulse wave velocity function and the pulse transmission distance; determine a maximum pulse wave transmission time function using the minimum systolic blood pressure parameter based on the pulse wave transmission time function; determine a minimum pulse wave transmission time function using the maximum systolic blood pressure parameter; and obtain the second model using the maximum transmission time function and the minimum pulse wave transmission time function.

[0164] In one embodiment, the data processing module is further configured to obtain the ratio of the square of the maximum transmission time function to the square of the minimum transmission time function; take the logarithm of the ratio to obtain a second model, wherein the unknown parameters in the second model are the unknown parameters in the first model.

[0165] In one embodiment, the arterial physiological information acquisition module is used to obtain the phase difference of the pulse wave of the finger at different positions using the photoplethysmography signal to obtain the actual value of the pulse transit time; or to obtain a second feature point of the pulse wave of the finger at a single position using the photoplethysmography signal to obtain a first feature point of the electrocardiogram signal; and to obtain the phase difference between the first feature point and the second feature point to obtain the actual value of the pulse transit time.

[0166] In an exemplary embodiment, a vascular parameter monitoring device is provided, comprising a force sensor and a PPG sensor. The force sensor and PPG sensor are integrated. The force sensor is used to acquire the finger pressure of a subject. The subject presses the force sensor, enabling the processor to obtain the subject's finger pressure. An arterial physiological sensor is used to acquire the subject's electrocardiogram (ECG) signal and photoplethysmography (PPG) signal. Finger pressure and PPG signal can be used to obtain oscillation envelope information, and PPG signal and ECG signal can be used to obtain pulse transmission information. A data acquisition module acquires signals from each sensor and sends them to the processor. The processor receives the signals sent by the data acquisition module and processes them, for example, processing each signal to obtain oscillation envelope information and pulse transmission information. Furthermore, the application device also includes a screen. The screen is configured as a visual indicator to guide the subject to press their finger evenly on the screen to change the external pressure of the artery, thereby obtaining changes in the subject's physiological signals (e.g., PPG signals), which are then used to estimate the subject's blood pressure. The finger can be evenly pressed at any position on the screen to obtain physiological information. Alternatively, indicator information, such as numbers, can be displayed in a fixed area of ​​the screen, allowing the subject to aim at the numbers and press the screen. Physiological information can include oscillation envelope information, pulse transmission information, or blood pressure information. Blood pressure information can include systolic blood pressure, diastolic blood pressure, arterial stiffness indices, etc. Oscillation envelope information can be an oscillometric waveform, which can be a function of arterial volume oscillation relative to the transmural pressure of the finger artery. Pulse transmission information can be a function of pulse transmission time relative to the transmural pressure of the finger artery.

[0167] like Figure 8 As shown, the vascular parameter monitoring device can be a smartphone. The left thumb contacts the PPG-integrated acquisition contact, while the left index finger, right index finger, and right thumb contact the ECG signal acquisition electrodes for simultaneous acquisition of pressure, PPG, and ECG signals. Simultaneously, following the finger pressure guidance interface on the phone screen, the left thumb slowly increases the applied pressure. The locally acquired data is stored in the local memory. The vascular parameter acquisition module executes the vascular parameter monitoring method and displays the results on the phone screen. The results can be systolic and diastolic blood pressure. A graph showing changes in finger pressure can be displayed on the phone screen to guide the subject in slowly applying pressure. The phone screen can also display a pulse map and an ECG.

[0168] In some embodiments, the arterial physiological information acquisition module can be used to acquire electrocardiogram (ECG) signals and PPG signals to obtain pulse transit time information. In other embodiments, the arterial physiological information acquisition module is used to acquire PPG signals corresponding to different fingers to obtain pulse transit time information.

[0169] In other embodiments, the vascular parameter monitoring device can be a smartwatch. It can also be a device that collects electrocardiogram (ECG) signals from the wrist. Figure 9 As shown, screen 901 displays a real-time finger pressure acquisition guidance interface, as well as a dynamic display interface for PPG and ECG signals (shown as ECG signals in the figure). ECG signal acquisition electrode 902 is used to acquire ECG signals. A pressure-PPG multi-mode sensor module is deployed in the same location, allowing for PPG and pressure signal acquisition by pressing with the finger of the non-wearing hand. Another ECG electrode 903 on the back of the watch is used to contact the wrist of the wearing hand for ECG signal acquisition.

[0170] When the arterial physiological information acquisition module is used to acquire electrocardiogram (ECG) signals and PPG signals, the vascular parameter monitoring device includes an ECG sensor and a PPG sensor.

[0171] Alternatively, the blood pressure monitoring device can also be a phone case. The various sensors and processor are integrated into the phone case. The processor can directly process the signals collected by the sensors to obtain an estimated blood pressure value. For example... Figure 10 As shown, Figure 10 The device on display is an integrated unit in the form of a phone case. The multi-mode integrated module 1001 integrates a force sensor and a PPG sensor. The ECG sensor is located on the outside of the phone case at the finger contact point and acquires data via a metal dry electrode. Simultaneously with the acquisition of the PPG signal, pressure is transmitted to the force sensor through a pressure transmission component, achieving synchronous and high-quality acquisition of pressure, PPG, and ECG signals. The processor 1002 processes the acquired ECG, PPG, and pressure signals.

[0172] like Figure 11 As shown, Figure 11 What is being shown is Figure 10 The diagram shows the operation of the device. During the data acquisition process, the user needs to position the device and the operating arm at chest height, place the right thumb flat on the upper end of the acquisition device 1101, apply pressure steadily according to the visual indicators on the screen, and simultaneously place the left thumb and right index finger on the ECG signal acquisition electrode 1102 to achieve synchronous acquisition of pressure signal, PPG signal and ECG signal.

[0173] like Figure 12 As shown, Figure 12 for Figure 10An exploded view of the multimode integrated module. The multimode integrated module includes a force sensor 1201 and a physiological signal front-end processing chip 1204. The force sensor 1201 is a thin-film piezoresistive pressure sensor with a range of 0-4.4N, a contact area of ​​12mm in diameter, a pressure range of 0-292mmHg, and a sensor length of 25.4mm. The force sensor 1201 is located at the bottom of the multimode integrated module. The multimode integrated module also includes acrylic material 1202 for support, specifically a cube with dimensions of 8×8×3mm and a cylinder with a diameter of 16mm and a height of 3mm. The cylinder is fixed and filled using hot melt adhesive 1205. Above the support material is the physiological signal front-end processing chip 1204, and on the chip is a spacer 1203, which has a hollow center to accommodate the chip size, and its overall size is a circle with a diameter of 12mm. This allows for the acquisition of pressure and arterial physiological signals using a single multi-mode integrated module, reducing the space occupied by the signal acquisition module in the overall device, and enabling high-quality synchronous acquisition of pressure and PPG signals.

[0174] In some embodiments, Figure 10 The integrated device shown can be connected to a screen to display the collected information. This screen can also be configured with a "Start" button to begin collecting physiological information and a "Stop" button to stop collecting physiological information, thereby using the collected physiological information to estimate vascular parameters. Figure 10 The integrated device shown can be used to estimate vascular parameters, or it can be connected to other terminals to estimate vascular parameters. For example... Figure 13 As shown, during the acquisition process, the dynamic guidance of pressure signal acquisition, ECG signal waveform, and PPG signal waveform can be seen on the screen. Figure 13 The first table image in the dataset is used to represent finger pressure information during the acquisition process. Figure 13 The second table image in the table is used to represent the ECG signals acquired during the acquisition process. Figure 13 The third table image in the middle is used to represent the PPG signals acquired during the acquisition process. Figure 13 The "Start" button is clicked to begin collecting physiological information. Figure 13 The “DISCONNECT” button is clicked to end the monitoring of physiological information.

[0175] When the arterial physiological information acquisition module is used to acquire PPG signals corresponding to different sites, the vascular parameter monitoring device includes at least two PPG sensors. A force sensor is used to measure the pressure of finger pressure; two or more PPG sensors are used to measure PPG waveforms at multiple locations, one of which measures the waveform at the finger position; a screen is configured to display visual indicators to guide the subject to place their fingertip vertically on the camera and screen to aim at a number, and to display finger pressure in real time to guide the subject to press their finger evenly on the camera and screen to change the external pressure on the artery; a processor is used to process the pulse pressure signal, acquire the pulse transmission time through the time delay between multi-channel PPGs, and finally estimate blood pressure based on a model algorithm.

[0176] Each module in the aforementioned vascular parameter monitoring device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0177] In one exemplary embodiment, a vascular parameter monitoring device is provided. This device can be a terminal, and its internal structure diagram can be as follows: Figure 14 As shown, the vascular parameter monitoring device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computational and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a vascular parameter monitoring method. The display unit of the blood pressure monitoring device forms a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen, and the input device for the vascular parameter monitoring device can be an external sensor.

[0178] Those skilled in the art will understand that Figure 14The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0179] In one embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0180] In one embodiment, a computer program product is provided, the computer program product including a computer program that can be executed by a processor to implement the steps in the above method embodiments.

[0181] In one embodiment, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and executes the computer instructions, causing the computer device to perform the steps in the above method embodiments.

[0182] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0183] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0184] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for monitoring vascular parameters, characterized in that, The method includes: Acquire finger pressure information and finger arterial physiological information during the monitoring period; The actual value of the oscillation envelope is obtained using the physiological information of the finger artery, and the actual value of the pulse transmission time is obtained using the physiological information of the finger artery. A first model is obtained, which is based on the finger pressure information and vascular parameters to obtain an oscillation envelope estimate; a second model is obtained, which is based on vascular parameters to obtain a pulse transit time estimate. The objective function is optimized by combining the first model and the second model to obtain the estimated values ​​of vascular parameters during the monitoring period. The objective function is generated based on the first error and the second error. The first error is obtained by the actual value of the oscillation envelope and the estimated value of the oscillation envelope generated based on the first model. The second error is obtained by the actual value of the pulse transit time and the estimated value of the pulse transit time generated based on the second model.

2. The method according to claim 1, characterized in that, The finger artery physiological information includes photoplethysmography (PPG) signals, and the step of using the finger artery physiological information to obtain the actual value of pulse transit time includes: The maximum pulse transit time and minimum pulse transit time within the monitoring period are obtained based on the photoplethysmography signal. The actual value of pulse transit time is obtained using the maximum pulse transit time and the minimum pulse transit time.

3. The method according to claim 2, characterized in that, The step of obtaining the actual value of pulse transit time using the maximum pulse transit time and the minimum pulse transit time includes: Calculate the ratio of the square of the maximum pulse transit time to the square of the minimum pulse transit time; The logarithm of the ratio is taken to obtain the actual value of the pulse transmission time.

4. The method according to claim 2, characterized in that, The method of obtaining the actual value of the oscillation envelope using the physiological information of the finger artery includes: The peak points of each photoplethysmogram signal are detected to obtain the upper envelope; The valley points of the photoplethysmography signal are detected one by one to obtain the lower envelope; The actual value of the oscillation envelope is obtained using the upper envelope and the lower envelope.

5. The method according to claim 2, characterized in that, The vascular parameters include blood pressure parameters, initial vascular volume parameters, and arterial stiffness index parameters. Obtaining the first model includes: Obtain the arterial compliance function, which characterizes the vascular volume based on the relationship between the initial vascular volume parameter, the arterial stiffness index parameter, and the arterial transmural pressure variable; The first model is obtained using the arterial compliance function.

6. The method according to claim 5, characterized in that, The blood pressure parameters include target systolic blood pressure parameters and target diastolic blood pressure parameters. The transmural arterial pressure variable is related to the target systolic blood pressure parameter, the target diastolic blood pressure parameter, and the finger pressure information. Obtaining the first model using the arterial compliance function includes: Based on the arterial compliance function, the vascular volume function corresponding to the target systolic blood pressure parameter is obtained using the finger pressure information and the target systolic blood pressure parameter; based on the arterial compliance function, the vascular volume function corresponding to the target diastolic blood pressure parameter is obtained using the finger pressure information and the target diastolic blood pressure parameter. The first model is obtained based on the vascular volume function corresponding to the target systolic blood pressure parameter and the vascular volume function corresponding to the target diastolic blood pressure parameter.

7. The method according to claim 6, characterized in that, The target systolic blood pressure parameter is related to the maximum systolic blood pressure parameter and the minimum systolic blood pressure parameter, wherein the maximum systolic blood pressure parameter corresponds to the minimum pulse transit time parameter, and the minimum systolic blood pressure parameter corresponds to the maximum pulse transit time parameter. Obtaining the second model includes: The pulse wave propagation velocity function is obtained based on the arterial compliance function; The pulse wave propagation velocity function and the pulse propagation distance are used to obtain the pulse propagation time function; Based on the pulse transit time function, the maximum pulse transit time function is determined using the minimum systolic blood pressure parameter, and the minimum pulse transit time function is determined using the maximum systolic blood pressure parameter, so as to obtain the second model using the maximum pulse transit time function and the minimum pulse transit time function.

8. The method according to claim 7, characterized in that, The process of obtaining the second model using the maximum pulse transit time function and the minimum pulse transit time function includes: Obtain the ratio of the square of the maximum pulse transit time function to the square of the minimum pulse transit time function; Take the logarithm of the ratio to obtain a second model, where the unknown parameters in the second model are the same as the unknown parameters in the first model.

9. The method according to claim 2, characterized in that, The finger artery physiological information also includes electrocardiogram signals, and the step of obtaining the actual value of pulse transit time using the finger artery physiological information includes: The phase difference of the pulse wave at different positions of the finger is obtained using the photoplethysmography signal to obtain the actual value of the pulse transmission time; or The second feature point of the pulse wave of the finger at a single location is obtained using the photoplethysmography signal, and the first feature point of the electrocardiogram signal is obtained. The phase difference between the first feature point and the second feature point is obtained to obtain the actual value of the pulse transmission time.

10. A vascular parameter monitoring device, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 9.

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