Doppler-based PWV calculation method, device, storage medium and electronic device

Abstract

The present invention relates to a Doppler-based PWV calculation method, device, storage medium and electronic device; wherein the method includes the following steps: synchronously acquiring two physiological signals on the same side and in different parts, wherein at least one physiological signal is a Doppler blood flow signal and at most one physiological signal is a pulse signal; if the physiological signal is a pulse signal, a corresponding pulse fluctuation curve is generated; if the physiological signal is a Doppler blood flow signal, spectrum envelope processing is performed on the Doppler blood flow signal to generate a corresponding spectrum envelope curve; the cardiac cycle on the two generated curves is identified, and the measurement time difference between the two physiological signals is determined based on the cardiac cycle to determine the PWV. The present invention has lower requirements for the user to be measured, smaller acquisition errors, and can accurately calculate the PWV in the subsequent period; and, ultrasonic Doppler technology can also be combined with conventional pulse waveform measurement to avoid the limitations of data acquisition.

Description

Technical Field

[0001] The present application relates to the technical field of signal monitoring, and in particular to a Doppler-based PWV calculation method, device, storage medium and electronic device. Background Art

[0002] With the progress of society and the rapid development of economy, people's lifestyle and eating habits have changed greatly. The incidence of cardiovascular and cerebrovascular diseases has continued to increase, making it one of the major diseases threatening human health. Among them, atherosclerosis, as the most important type of arteriosclerotic vascular lesions, is the main cause of various cardiovascular and cerebrovascular diseases. Early detection of atherosclerosis is one of the important measures to control cardiovascular diseases.

[0003] Nowadays, pulse wave velocity (PWV) is gradually attracting people's attention as an indicator for non-invasive assessment of arteriosclerosis. We know that pulse wave velocity refers to the speed of pressure wave transmission along the wall of the aorta generated by each beat of the heart. It is the speed at which the pulse generated by the expansion and contraction of the arterial wall is transmitted from the proximal end to the distal end, that is, the conduction speed of the pulse wave in the artery. It shows a good correlation with arteriosclerosis. Traditional PWV calculation is mainly through measuring the propagation time of the pulse wave between two pressure receptors and estimating the distance between the two. However, it is difficult to operate for obese patients or patients who cannot cooperate with the body position, and it is difficult to be clinically recognized. Summary of the invention

[0004] In view of this, embodiments of the present application provide a Doppler-based PWV calculation method, device, storage medium, and electronic device to solve at least one problem in the background technology.

[0005] In a first aspect, an embodiment of the present application provides a Doppler-based PWV calculation method, comprising the following steps:

[0006] Synchronously acquiring two physiological signals from the same side and different parts, wherein at least one physiological signal is a Doppler blood flow signal and at most one physiological signal is a pulse signal;

[0007] If the physiological signal is a pulse signal, generating a corresponding pulse fluctuation curve;

[0008] If the physiological signal is a Doppler blood flow signal, performing spectrum envelope processing on the Doppler blood flow signal to generate a corresponding spectrum envelope curve;

[0009] The cardiac cycles on the two generated curves are identified, and the measured time difference between the two physiological signals is determined based on the cardiac cycles to determine the PWV.

[0010] In combination with the first aspect of the present application, in an optional implementation, if the physiological signal is a Doppler blood flow signal, the Doppler blood flow signal is acquired by collecting an ultrasonic Doppler probe; or,

[0011] If the physiological signal is a pulse signal, the pulse signal is collected by a blood oxygen pulse sensor, a blood pressure airbag pulse sensor or a pressure pulse sensor.

[0012] In combination with the first aspect of the present application, in an optional implementation, the Doppler blood flow signal includes a Doppler blood flow signal of a carotid artery.

[0013] In conjunction with the first aspect of the present application, in an optional implementation manner, the specific steps of identifying the cardiac cycles on the two generated curves and determining the measurement time difference of the two physiological signals based on the cardiac cycles include:

[0014] According to the cardiac cycle of the curve, the curve is divided into a plurality of cardiac cycle curves;

[0015] Overlapping and fitting the first cardiac cycle curve after segmentation of the same curve with at least one remaining cardiac cycle curve to generate a new curve; wherein the first cardiac cycle curve is adjusted with the original coordinates as the starting point;

[0016] The measurement time difference of the two physiological signals is determined according to the two new curves generated by fitting.

[0017] In conjunction with the first aspect of the present application, in an optional implementation manner, the specific step of determining the measurement time difference of the two physiological signals according to the two new curves generated by fitting includes:

[0018] Calculate the time difference between the highest peaks of the two new curves.

[0019] In conjunction with the first aspect of the present application, in an optional implementation manner, the specific steps of performing spectrum envelope processing on the Doppler blood flow signal to generate a corresponding spectrum envelope curve include:

[0020] Continuously acquiring multiple columns of power spectrum density S(n) of Doppler blood flow signals, and obtaining an integral curve P(n) corresponding to each column of the power spectrum density S(n);

[0021] The maximum flow velocity point is determined on the integral curve P(n), and the maximum flow velocity points determined in each column are connected to obtain the corresponding spectrum envelope curve.

[0022] In a second aspect, an embodiment of the present application provides a Doppler-based PWV calculation device, comprising:

[0023] A signal acquisition module, which is configured to synchronously acquire two physiological signals from the same side and different parts, wherein at least one physiological signal is a Doppler blood flow signal and at most one physiological signal is a pulse signal;

[0024] The curve generation module includes a first submodule and a second submodule, wherein the first submodule is configured to obtain a corresponding pulse fluctuation curve if the physiological signal is a pulse signal; and the second submodule is configured to perform spectrum envelope processing on the Doppler blood flow signal to obtain a corresponding spectrum envelope curve if the physiological signal is a Doppler blood flow signal.

[0025] The time difference determination module is configured to identify the cardiac cycles on the two obtained curves, and determine the measured time difference between the two physiological signals based on the cardiac cycles to determine the PWV.

[0026] In conjunction with the second aspect of the present application, in an optional implementation manner, the method further includes:

[0027] Two probes, the probes are connected to the signal acquisition module;

[0028] Wherein, both probes are ultrasonic Doppler probes; or,

[0029] One probe is an ultrasonic Doppler probe, and the other probe is a blood oxygen pulse sensor, a blood pressure balloon pulse sensor, or a pressure pulse sensor.

[0030] In a third aspect, an embodiment of the present application provides a computer-readable storage medium, which stores instructions. When the instructions are executed by a processor of an electronic device, the electronic device can execute the Doppler-based PWV calculation method described in any one of the above-mentioned first aspects.

[0031] In a fourth aspect, an embodiment of the present application provides an electronic device, the electronic device comprising:

[0032] processor;

[0033] memory for storing computer executable instructions;

[0034] The processor is used to execute the computer executable instructions to implement the Doppler-based PWV calculation method described in any one of the first aspects above.

[0035] The beneficial effects brought by the technical solution provided in the embodiments of the present application include:

[0036] On the one hand, with the help of ultrasonic Doppler technology, the acquisition end is attached to the part to be tested when acquiring physiological signals, which has lower requirements on the user to be tested and is suitable for patients with obesity or body position that cannot cooperate. It provides a better experience and does not compress the blood vessels under the skin, so that the acquired physiological signals have smaller errors. It can also provide a data basis for the subsequent accurate calculation of PWV to more accurately evaluate the condition of arteriosclerosis. On the other hand, ultrasonic Doppler technology can be combined with conventional pulse waveform measurement to overcome the problem of incomparability of different data, obtain more diverse and rich preliminary data, and avoid the limitations of data acquisition.

[0037] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0039] Figure 1 A schematic diagram of an application scenario of a Doppler-based PWV calculation device provided in one embodiment of the present application;

[0040] Figure 2 A flowchart of a Doppler-based PWV calculation method provided in one embodiment of the present application;

[0041] Figure 3 A schematic diagram of determining the measurement time difference of two physiological signals by two spectrum envelopes according to an embodiment of the present application;

[0042] Figure 4 A specific flow chart of generating a spectrum envelope curve in an embodiment of the present application;

[0043] Figure 5 A schematic diagram of the structure of a Doppler-based PWV calculation device provided in one embodiment of the present application;

[0044] Figure 6 A schematic diagram of the structure of an electronic device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0045] In order to make the technical solutions and beneficial effects of the present invention more clearly understandable, the following is a detailed description by listing specific embodiments. The drawings are not necessarily drawn to scale, and local features may be enlarged or reduced to more clearly show the details of the local features; unless otherwise defined, the technical and scientific terms used herein have the same meanings as those in the technical field to which this application belongs.

[0046] A Doppler-based PWV calculation method provided in an embodiment of the present application can be specifically applied in an electronic device, which can be a terminal, a server or other device.

[0047] like Figure 2 As shown, the embodiment of the present application provides a Doppler-based PWV calculation method, comprising the following steps:

[0048] S001: synchronously acquiring two physiological signals at the same side and different parts, wherein at least one physiological signal is a Doppler blood flow signal and at most one physiological signal is a pulse signal;

[0049] S002: If the physiological signal is a pulse signal, generating a corresponding pulse fluctuation curve;

[0050] S003: If the physiological signal is a Doppler blood flow signal, perform spectrum envelope processing on the Doppler blood flow signal to generate a corresponding spectrum envelope curve;

[0051] S004: Identify the cardiac cycles on the two generated curves, and determine the measurement time difference between the two physiological signals based on the cardiac cycles to determine the PWV.

[0052] In the embodiment of the present application, one of the two physiological signals is a Doppler blood flow signal and the other is a pulse signal. Figure 1 As shown, physiological signals are collected at two different parts of each part to be measured on the same side of the human body, such as the arm, thigh, carotid artery, etc. For example, the physiological signals of the arm and thigh are obtained synchronously. After the physiological signals are obtained, a corresponding fluctuation curve is generated. If the physiological signal is a pulse signal, a pulse fluctuation curve is directly generated; if the physiological signal is a Doppler blood flow signal, the Doppler blood flow signal needs to be processed by spectrum envelope; after the Doppler blood flow signal generates the corresponding spectrum envelope curve, two different curves are identified. Among them, one is the pulse fluctuation curve, and the other is the spectrum envelope curve. The two curves have multiple cardiac cycles according to their respective periodic fluctuation characteristics. Then, the time delay of the physiological signals collected at the arm and thigh is determined by their respective cardiac cycle characteristics, that is, the measurement time difference. After obtaining a relatively accurate measurement time difference Δt, the value of PWV is estimated according to the mathematical formula PWV=Δd / Δt, where Δd is the distance between the two measurement parts, which is a known value.

[0053] If the two sampled parts are on opposite sides, the final measurement time difference is not relative and cannot be estimated according to the mathematical formula PWV=Δd / Δt.

[0054] Further, if the physiological signal is a Doppler blood flow signal, the Doppler blood flow signal is acquired by an ultrasonic Doppler probe; or,

[0055] If the physiological signal is a pulse signal, the pulse signal is collected by a blood oxygen pulse sensor, a blood pressure airbag pulse sensor or a pressure pulse sensor.

[0056] In this embodiment, there are many ways to obtain pulse signals, such as blood oxygen pulse sensors, blood pressure bag pulse sensors or pressure pulse sensors and other sensors. The embodiment of this application only enumerates several commonly used sensors, and it can also be other special sensors that can collect pulse signals.

[0057] When it is necessary to collect Doppler blood flow signals, an ultrasonic Doppler probe needs to be attached to the surface of the skin for collection, so as to avoid errors in the pulse waveform caused by compression of the artery. For example, the pressure sensor needs to have corresponding pressure on the artery during measurement in order to sense and measure the pulse. Due to the local pressure compression on the artery, the blood flow at the compression point will change, and the obtained pulse wave will also be deformed, which may cause errors.

[0058] Optionally, the Doppler blood flow signal includes a Doppler blood flow signal of the carotid artery. The pulse of the carotid artery has a high frequency when calculating PWV, and it is difficult to fix the pulse signal acquisition using conventional sensors. The ultrasonic Doppler probe is attached to the carotid artery to collect the Doppler blood flow signal, which is easy to operate and easy to obtain data.

[0059] like Figure 3 As shown, as an optional embodiment of the embodiment of the present application, the specific steps of identifying the cardiac cycles on the two generated curves and determining the measurement time difference of the two physiological signals based on the cardiac cycles include:

[0060] According to the cardiac cycle of the curve, the curve is divided into a plurality of cardiac cycle curves;

[0061] Overlapping and fitting the first cardiac cycle curve after segmentation of the same curve with at least one remaining cardiac cycle curve to generate a new curve; wherein the first cardiac cycle curve is adjusted with the original coordinates as the starting point;

[0062] The measurement time difference of the two physiological signals is determined according to the two new curves generated by fitting.

[0063] Furthermore, the specific step of determining the measurement time difference of the two physiological signals according to the two new curves generated by fitting includes:

[0064] Calculate the time difference between the highest peaks of the two new curves.

[0065] In the embodiment of the present application, whether it is the spectrum envelope curve or the pulse fluctuation curve, continuous periodic changes will occur, and then each curve is divided and saved as multiple groups of data according to the cardiac cycle, wherein the number of cardiac cycles is generally selected to be 4 to 24, and in the present embodiment, the number of cardiac cycles is five; the data of the spectrum envelope curve or the pulse fluctuation curve corresponding to the five cardiac cycles are overlapped, wherein the first cardiac cycle curve is adjusted with the original coordinate as the starting point, and then a graph with five vertical coordinates corresponding to the horizontal coordinate is obtained, and the scattered points on the graph are fitted to obtain a new curve, and the difference between the highest peak values ​​of the two new curves on the time axis is calculated, such as Figure 3 Δt in this embodiment selects data of multiple cardiac cycles for overlapping and superposition, and fits each scattered point after overlapping and then uses it in subsequent calculations, which can reduce random errors and improve the reliability of PWV results.

[0066] Among them, the highest peak value in the cardiac cycle is easy to determine and is related to all overlapping cardiac cycles, while the starting point of the cardiac cycle is difficult to determine, which is not conducive to quickly determining the point that can be used for PWV calculation and measurement of time difference.

[0067] Optionally, the specific steps of performing spectrum envelope processing on the Doppler blood flow signal to generate a corresponding spectrum envelope curve include:

[0068] Continuously acquiring multiple columns of power spectrum density S(n) of Doppler blood flow signals, and obtaining an integral curve P(n) corresponding to each column of the power spectrum density S(n);

[0069] The maximum flow velocity point is determined on the integral curve P(n), and the maximum flow velocity points determined in each column are connected to obtain the corresponding spectrum envelope curve.

[0070] like Figure 4As shown, specifically, first, the power spectrum density S(n) of a column is integrated with the increase of frequency (corresponding to the accumulation of grayscale from low frequency to high frequency in each column of the spectrogram), forming the integral curve P(n) of the power spectrum density integration of this column, that is, the discrete data point curve. Secondly, the origin is connected to the last point of the power spectrum density integration to form a straight line. The intersection point (Vcross, P(Vcross)) of this straight line and the integral curve P(n) is also the maximum energy point of the signal. Thirdly, the horizontal ordinate Slowest of the minimum point searched from S(1) to S(Vcross) is calculated, and the new integral curve P(m) from S(Slowest) to S(2·Vcross-Slowest) is calculated. The starting point of P(m) and the end point of P(m) are connected to obtain a new reference straight line. The frequency point corresponding to the maximum positive distance from the reference straight line is the maximum flow velocity point of the signal. Finally, the maximum flow velocity points of each column are connected to obtain the envelope of the spectrum data, that is, the spectrum envelope curve.

[0071] In this embodiment, the frequency characteristics of the power spectral density integral curve of the ultrasonic Doppler blood flow signal are used to estimate the maximum flow velocity, wherein the flow velocity and frequency are corresponding, and the flow velocity is obtained by converting the frequency. The conversion is known to those skilled in the art, has a small amount of calculation, and has high calculation efficiency, which meets the clinical requirements for real-time and rapid performance of the system.

[0072] The Doppler-based PWV calculation method provided in the present application is further explained below with reference to a specific example.

[0073] In this embodiment, ultrasonic Doppler data of the carotid artery and arm on the same side of the human body are collected synchronously. Envelope processing is performed on the two ultrasonic Doppler data, such as Figure 4 As shown, first, the power spectrum density S(n) of a column is integrated with the increase of frequency (corresponding to the accumulation of grayscale from low frequency to high frequency in each column of the spectrogram) to form the integral curve P(n) of the power spectrum density of this column, that is, the discrete data point curve; secondly, the origin is connected with the last point of the power spectrum density integration to form a straight line. The intersection point (Vcross, P(Vcross)) of this straight line and the integral curve P(n) is also the maximum energy point of the signal; thirdly, the horizontal vertical coordinate Slowest of the minimum point searched from S(1) to S(Vcross) is calculated, and the new integral curve P(m) from S(Slowest) to S(2·Vcross-Slowest) is calculated. The starting point of P(m) and the end point of P(m) are connected to obtain a new reference straight line. The frequency point corresponding to the maximum positive distance from the reference straight line is the maximum flow velocity point of the signal; finally, the maximum flow velocity points of each column are connected to obtain the envelope of the spectrum data. As shown Figure 3As shown, each cardiac cycle of the two envelopes is identified, and the data of each cardiac cycle is saved separately according to the identified cardiac cycle, that is, saved as five arrays (the first data is adjusted with the original coordinates as the starting point); the data of the corresponding carotid artery ultrasound envelope and arm ultrasound envelope of the five cardiac cycles are overlapped (the first data is adjusted with the original coordinates as the starting point) to obtain a graph with five ordinate points corresponding to the horizontal coordinate point; then a curve is fitted according to the scattered points of the graph overlapped in the previous step, and the difference between the highest peak time axis of the two fitted curves is calculated as Δt in the figure. Finally, PWV is calculated, wherein, according to the difference Δt calculated in the previous step, and the distance Δd between the carotid artery and the arm to be measured is estimated, then PWV can be calculated according to the solution formula of PWV=Δd / Δt.

[0074] In the embodiment of the present application, two physiological signals are obtained, one is the measured carotid ultrasound, and the other can be measured at other locations, and different sensors or ultrasonic Doppler probes can be used to measure, and the data types are diverse and rich. Selecting data of multiple cardiac cycles for overlapping and superposition, and fitting each scattered point after overlapping and then using it in subsequent calculations can reduce random errors and improve the reliability of PWV results. It must be ensured that at least one technology using ultrasonic Doppler blood flow measurement is used, rather than pulse wave waveform. Ultrasonic Doppler directly measures blood flow, and the envelope spectrum waveform has no other sensors that may cause pulse waveform changes after compressing the artery. For example, both air pressure and pressure sensors need to have corresponding pressure on the artery to sense and measure the pulse during measurement. Due to the local pressure compression of the artery, the blood flow at the compression point will change, and the obtained pulse wave will also be deformed, so the blood flow waveform collected by ultrasound will be more real and accurate than the pulse wave waveform.

[0075] like Figure 5 As shown, an embodiment of the present application provides a Doppler-based PWV calculation device, comprising:

[0076] A signal acquisition module, which is configured to synchronously acquire two physiological signals from the same side and different parts, wherein at least one physiological signal is a Doppler blood flow signal and at most one physiological signal is a pulse signal;

[0077] The curve generation module includes a first submodule and a second submodule, wherein the first submodule is configured to obtain a corresponding pulse fluctuation curve if the physiological signal is a pulse signal; and the second submodule is configured to perform spectrum envelope processing on the Doppler blood flow signal to obtain a corresponding spectrum envelope curve if the physiological signal is a Doppler blood flow signal.

[0078] The time difference determination module is configured to identify the cardiac cycles on the two obtained curves, and determine the measured time difference between the two physiological signals based on the cardiac cycles to determine the PWV.

[0079] Optionally, it also includes:

[0080] Two probes, the probes are connected to the signal acquisition module;

[0081] Wherein, both probes are ultrasonic Doppler probes; or,

[0082] One probe is an ultrasonic Doppler probe, and the other probe is a blood oxygen pulse sensor, a blood pressure balloon pulse sensor, or a pressure pulse sensor.

[0083] In the embodiment of the present application, the Doppler blood flow signal is collected by an ultrasonic Doppler probe; or, the pulse signal is collected by a blood oxygen pulse sensor, a blood pressure balloon pulse sensor or a pressure pulse sensor.

[0084] Furthermore, the Doppler blood flow signal includes a Doppler blood flow signal of a carotid artery. An ultrasonic Doppler probe is attached to the carotid artery to collect carotid artery ultrasonic Doppler data.

[0085] Optionally, the time difference determination module is specifically configured to:

[0086] a segmentation unit configured to segment the curve into a plurality of cardiac cycle curves according to the cardiac cycle of the curve;

[0087] An overlapping fitting unit, which is configured to overlap and fit the first cardiac cycle curve after segmentation of the same curve with at least one remaining cardiac cycle curve to generate a new curve; wherein the first cardiac cycle curve is adjusted with the original coordinates as the starting point;

[0088] The time difference determination unit is configured to determine the measurement time difference of the two physiological signals according to the two new curves generated by fitting.

[0089] Optionally, the time difference determination unit is configured to calculate the difference between the highest peak values ​​on the time axis of the two new curves.

[0090] Optionally, the second submodule is configured as:

[0091] Continuously acquiring multiple columns of power spectrum density S(n) of Doppler blood flow signals, and obtaining an integral curve P(n) corresponding to each column of the power spectrum density S(n);

[0092] The maximum flow velocity point is determined on the integral curve P(n), and the maximum flow velocity points determined in each column are connected to obtain the corresponding spectrum envelope curve.

[0093] It is worth noting that the device embodiments provided in the present application have been described in detail in the above method embodiments and will not be repeated here.

[0094] The embodiment of the present application further provides a computer-readable storage medium. The computer-readable storage medium stores instructions, and when the instructions are executed by a processor of an electronic device, the electronic device is enabled to execute the Doppler-based PWV calculation method described in any of the above embodiments.

[0095] The present application embodiment can be a system, method and / or computer program product. The computer program product may include a computer-readable storage medium, which is loaded with a computer-readable program instruction for making a processor realize various aspects of the present application. The computer program product can be written in any combination of one or more programming languages ​​to perform the program code for performing the operation of the present application embodiment, and the programming language includes an object-oriented programming language, such as Java, C++, etc., and also includes a conventional procedural programming language, such as "C" language or similar programming language. The program code can be executed completely on the user computing device, partially on the user device, as an independent software package, partially on the user computing device, partially on the remote computing device, or completely on the remote computing device or server. In the case of a remote computer, the remote computer can be connected to the user computer through any type of network-including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to connect through the Internet). In some embodiments, by utilizing the state information of computer-readable program instructions to personalize an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), the electronic circuit can execute the computer-readable program instructions to implement various aspects of the present application.

[0096] Computer readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. Computer readable storage medium is a tangible device that can keep and store instructions used by an instruction execution device. The readable storage medium can include, for example, but is not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of readable storage medium include: portable computer disk, hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disk read-only memory (CD-ROM), digital versatile disk (DVD), memory stick, floppy disk, mechanical encoding device, such as a punch card or a convex structure in a groove on which instructions are stored, and any suitable combination of the above. The computer readable storage medium used here is not interpreted as a transient signal itself, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagated by a waveguide or other transmission medium (for example, a light pulse by an optical fiber cable), or an electrical signal transmitted by a wire.

[0097] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0098] Various aspects of the present application are described herein with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer-readable program instructions.

[0099] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processor of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0100] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0101] An embodiment of the present application also provides an electronic device. Figure 6 FIG. 1 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present application. Figure 6 As shown, the electronic device includes: one or more processors and a memory; the memory stores computer executable instructions; and the processor is used to execute the computer executable instructions to implement the steps in the Doppler-based PWV calculation method as described in any of the above embodiments.

[0102] The processor may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0103] The memory may include one or more computer program products, and the computer program product may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 1501 may execute the program instructions to implement the steps in the Doppler-based PWV calculation method of each embodiment of the present application described above and / or other desired functions.

[0104] It should be noted that the Doppler-based PWV calculation method embodiment, Doppler-based PWV calculation device embodiment, computer-readable storage medium embodiment and electronic device embodiment provided in the embodiments of the present application belong to the same concept; the technical features in the technical solutions recorded in each embodiment can be arbitrarily combined without conflict.

[0105] It should be understood that the above embodiments are exemplary and are not intended to include all possible implementations included in the claims. Various modifications and changes may be made on the basis of the above embodiments without departing from the scope of the present disclosure. Similarly, the various technical features of the above embodiments may be arbitrarily combined to form other embodiments of the present invention that may not be explicitly described. Therefore, the above embodiments only express several implementations of the present invention and do not limit the scope of protection of the patent of the present invention.

Claims

1. A Doppler-based PWV calculation method, characterized in that: The following steps are involved: Synchronously acquiring two physiological signals at the same side and different parts, wherein both physiological signals are Doppler blood flow signals; Performing spectrum envelope processing on the Doppler blood flow signal to generate a corresponding spectrum envelope curve; Identify the cardiac cycles on the two generated curves, and determine the measurement time difference of the two physiological signals based on the cardiac cycles to determine the PWV; wherein, The performing spectrum envelope processing on the Doppler blood flow signal to generate a corresponding spectrum envelope curve comprises: Continuously acquiring multiple columns of power spectrum density S(n) of the Doppler blood flow signal to obtain an integral curve P(n) corresponding to each column of the power spectrum density S(n); For each column of the power spectrum density S(n), the origin is connected to the end point of the integral curve P(n) to form a straight line, and the intersection point (Vcross, P(Vcross)) of the straight line and the integral curve P(n) is obtained, and the intersection point is the maximum energy point of the Doppler blood flow signal; Get the horizontal ordinate Slowest of the minimum energy point searched from S(1) to S(Vcross), and calculate the new integral curve P(m) from S(Slowest) to S(2·Vcross-Slowest); Connect the starting point and the end point of the integral curve P(m) to obtain a new reference straight line; Determine the frequency point corresponding to the maximum positive distance of the integral curve P(m) from the reference straight line as the maximum flow velocity point of the power spectrum density S(n) of the column; The maximum flow velocity points of each column of the power spectrum density S(n) are connected to obtain the corresponding spectrum envelope curve.

2. The Doppler-based PWV calculation method according to claim 1, characterized in that: The Doppler blood flow signal is acquired by collecting an ultrasonic Doppler probe.

3. The Doppler-based PWV calculation method according to claim 1 or 2, characterized in that: The Doppler blood flow signal includes a Doppler blood flow signal of a carotid artery.

4. The Doppler-based PWV calculation method according to claim 1, wherein: The specific steps of identifying the cardiac cycles on the two generated curves and determining the measurement time difference of the two physiological signals based on the cardiac cycles include: According to the cardiac cycle of the curve, the curve is divided into a plurality of cardiac cycle curves; Overlapping and fitting the first cardiac cycle curve after segmentation of the same curve with at least one remaining cardiac cycle curve to generate a new curve; wherein the first cardiac cycle curve is adjusted with the original coordinates as the starting point; The measurement time difference of the two physiological signals is determined according to the two new curves generated by fitting.

5. The Doppler-based PWV calculation method according to claim 4, characterized in that: The specific steps of determining the measurement time difference of the two physiological signals according to the two new curves generated by fitting include: Calculate the time difference between the highest peaks of the two new curves.

6. A Doppler-based PWV calculation device, characterized in that: include: A signal acquisition module, which is configured to synchronously acquire two physiological signals at the same side and different parts, wherein both physiological signals are Doppler blood flow signals; A curve generating module, which is configured to perform spectrum envelope processing on the Doppler blood flow signal to obtain a corresponding spectrum envelope curve; A time difference determination module is configured to identify the cardiac cycles on the two obtained curves, and determine the measurement time difference of the two physiological signals based on the cardiac cycles to determine the PWV; wherein, The curve generation module is specifically used for: Continuously acquiring multiple columns of power spectrum density S(n) of the Doppler blood flow signal to obtain an integral curve P(n) corresponding to each column of the power spectrum density S(n); For each column of the power spectrum density S(n), the origin is connected to the end point of the integral curve P(n) to form a straight line, and the intersection point (Vcross, P(Vcross)) of the straight line and the integral curve P(n) is obtained, and the intersection point is the maximum energy point of the Doppler blood flow signal; Get the horizontal ordinate Slowest of the minimum energy point searched from S(1) to S(Vcross), and calculate the new integral curve P(m) from S(Slowest) to S(2·Vcross-Slowest); Connect the starting point and the end point of the integral curve P(m) to obtain a new reference straight line; Determine the frequency point corresponding to the maximum positive distance of the integral curve P(m) from the reference straight line as the maximum flow velocity point of the power spectrum density S(n) of the column; The maximum flow velocity points of each column of the power spectrum density S(n) are connected to obtain the corresponding spectrum envelope curve.

7. The Doppler-based PWV calculation device according to claim 6, characterized in that: Also includes: Two probes, the probes are connected to the signal acquisition module; Among them, both probes are ultrasonic Doppler probes.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed by a processor of an electronic device, the electronic device is enabled to execute the Doppler-based PWV calculation method according to any one of claims 1 to 5.

9. An electronic device, characterized in that: The electronic device comprises: processor; memory for storing computer executable instructions; The processor is used to execute the computer executable instructions to implement the Doppler-based PWV calculation method according to any one of claims 1 to 5.

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