Pulse wave transit time measurement system and method

Abstract

The application relates to a pulse wave transmission velocity measurement system and method, wherein the pulse wave transmission velocity measurement system comprises a chest signal acquisition device, a wrist signal acquisition device, a finger signal acquisition device and a data processing device; the chest signal acquisition device is used for acquiring a first signal, the first signal at least comprising an electrocardiosignal, and sending the first signal to the data processing device; the wrist signal acquisition device is used for acquiring a second signal, the second signal at least comprising a wrist pulse wave signal, and sending the second signal to the data processing device; the finger signal acquisition device is used for acquiring a third signal, the third signal at least comprising a finger pulse wave signal, and sending the third signal to the data processing device; and the data processing device is used for determining a pulse wave transmission velocity according to the first signal, the second signal and the third signal. The application solves the problem of low measurement accuracy of the pulse wave transmission velocity, and realizes the technical effect of accurately measuring the pulse wave transmission velocity.

Description

Technical Field

[0001] This application relates to the field of medical devices, and in particular to a pulse wave velocity measurement system and method. Background Technology

[0002] There are various non-invasive methods for assessing arterial dysfunction. In addition to intuitive imaging techniques such as CT and MRI, pulse wave velocity (PWV) can be used to assess the elasticity of large arteries. Among these, pulse wave transit time (PTT) is the key to PWV measurement.

[0003] Aortic pulse wave velocity (AOPWV) is the most commonly used non-invasive detection method in clinical practice by recording arterial pulse waves. This method can be divided into single-point and two-point methods depending on the number of arterial locations required for measurement.

[0004] The single-point method includes waveform analysis and waveform decomposition. The key to waveform decomposition is using aortic blood flow waveforms and impedance analysis to decompose the aortic pressure waveform into forward and reflected waves, and then using cross-correlation techniques to calculate the pulse wave transit time (PTT). However, this method requires aortic blood flow waves for decomposition, and the measurement of aortic blood flow waves is difficult, resulting in low accuracy in pulse wave velocity measurement. The two-point method estimates pulse wave transit time by measuring arterial waveforms at two different locations and calculating the time difference between the two waveforms. However, because this method commonly uses the carotid and femoral arteries, which include muscular arteries, the accuracy of the measurement results is not high.

[0005] There is currently no effective solution to the problem of low accuracy in measuring pulse wave transmission velocity in related technologies. Summary of the Invention

[0006] This embodiment provides a pulse wave velocity measurement system and method to solve the problem of low measurement accuracy of pulse wave velocity in related technologies.

[0007] Firstly, this embodiment provides a pulse wave velocity measurement system, including: a chest signal acquisition device, a wrist signal acquisition device, a finger signal acquisition device, and a data processing device. The data processing device is connected to the chest signal acquisition device, the wrist signal acquisition device, and the finger signal acquisition device, respectively.

[0008] The chest signal acquisition device is used to acquire a first signal, the first signal including at least an electrocardiogram signal, and to send the first signal to the data processing device;

[0009] The wrist signal acquisition device is used to acquire a second signal, the second signal including at least a wrist pulse wave signal, and to send the second signal to the data processing device;

[0010] The finger signal acquisition device is used to acquire a third signal, which includes at least a finger pulse wave signal, and to send the third signal to the data processing device.

[0011] The data processing device is used to determine the pulse wave transmission speed based on the first signal, the second signal, and the third signal.

[0012] In one embodiment, the chest signal acquisition device further includes a chest pulse wave sensor connected to the data processing device; the chest pulse wave sensor is used to acquire the user's aortic pulse wave signal and send the aortic pulse wave signal to the data processing device, so that the data processing device can obtain the user's blood pressure signal based on the aortic pulse wave signal.

[0013] In one embodiment, the pulse wave velocity measurement system further includes a blood pressure signal acquisition device connected to the data processing device; the blood pressure signal acquisition device is used to acquire blood pressure signals and send the blood pressure signals to the data processing device, so that the data processing device determines the pulse wave velocity based on the first signal, the second signal, the third signal, and the blood pressure signal.

[0014] In one embodiment, the blood pressure signal acquisition device is an arm-type blood pressure acquisition device.

[0015] In one embodiment, the wrist signal acquisition device includes a photoplethysmography (PPG) sensor connected to the data processing device; the PPG sensor is used to acquire the second signal and send the second signal to the data processing device.

[0016] In one embodiment, the finger signal acquisition device is a finger clip / finger sleeve type acquisition device.

[0017] In one embodiment, the finger clip / finger sleeve type acquisition device adjusts the length of the finger clip / finger sleeve through stepless adjustment, and records and stores the length of the finger clip / finger sleeve through an electrical signal to the data processing device.

[0018] Secondly, this embodiment provides a method for measuring pulse wave propagation velocity, including:

[0019] Acquire the user's target detection signal, which includes at least an electrocardiogram signal, a wrist pulse wave signal, a finger pulse wave signal, and a blood pressure signal;

[0020] The first pulse wave transmission time is determined based on the electrocardiogram signal, the wrist pulse wave signal, and the finger pulse wave signal.

[0021] The second pulse wave transmission time is determined based on the electrocardiogram signal, the wrist pulse wave signal, the finger pulse wave signal, and the blood pressure signal.

[0022] The pulse wave transmission distance between the user's wrist and fingers is obtained, and the pulse wave transmission speed is determined based on the first pulse wave transmission time, the second pulse wave transmission time, and the pulse wave transmission distance.

[0023] In one embodiment, determining the first pulse wave transmission time based on the electrocardiogram (ECG) signal, the wrist pulse wave signal, and the finger pulse wave signal includes: determining a first transmission time based on the time interval between corresponding peaks of the ECG signal and the wrist pulse wave signal; determining a second transmission time based on the time interval between corresponding peaks of the ECG signal and the finger pulse wave signal; and determining the first pulse wave transmission time based on the first transmission time and the second transmission time.

[0024] In one embodiment, determining the pulse wave transmission speed based on the first pulse wave transmission time, the second pulse wave transmission time, and the pulse wave transmission distance includes: acquiring multiple first pulse wave transmission times within a preset period to establish a first pulse wave transmission time set; acquiring multiple second pulse wave transmission times within a preset period to establish a second pulse wave transmission time set; determining a correlation coefficient between the first pulse wave transmission time set and the second pulse wave transmission time set; if the correlation coefficient is less than or equal to a preset threshold, then re-acquiring the first and second pulse wave transmission times; if the correlation coefficient is greater than the preset threshold, then determining a first average pulse wave transmission time based on the first pulse wave transmission time set; determining a second average pulse wave transmission time based on the second pulse wave transmission time set; determining a target transmission time based on the first average pulse wave transmission time and the second average pulse wave transmission time; and determining the pulse wave transmission speed based on the target transmission time and the pulse wave transmission distance.

[0025] Compared with related technologies, the pulse wave velocity measurement system provided in this embodiment, by setting up a chest signal acquisition device, a wrist signal acquisition device, a finger signal acquisition device, and a data processing device, wherein the data processing device is connected to the chest signal acquisition device, the wrist signal acquisition device, and the finger signal acquisition device respectively, wherein the chest signal acquisition device is used to acquire a first signal, the first signal including at least an electrocardiogram signal, and send the first signal to the data processing device; the wrist signal acquisition device is used to acquire a second signal, the second signal including at least a wrist pulse wave signal, and send the second signal to the data processing device; the finger signal acquisition device is used to acquire a third signal, the third signal including at least a finger pulse wave signal, and send the third signal to the data processing device; the data processing device is used to determine the pulse wave velocity based on the first signal, the second signal, and the third signal, thereby solving the problem of low measurement accuracy of pulse wave velocity and achieving the technical effect of accurate measurement of pulse wave velocity.

[0026] Details of one or more embodiments of this application are set forth in the following drawings and description to make other features, objects and advantages of this application more readily apparent. Attached Figure Description

[0027] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0028] Figure 1 This is a schematic diagram of the pulse wave transmission velocity measurement system according to this application;

[0029] Figure 2 This is a schematic diagram of the chest acquisition device of the pulse wave transmission velocity measurement system according to an embodiment of this application;

[0030] Figure 3 This is a schematic diagram of the structure of a pulse wave transmission velocity measurement system according to another embodiment of this application;

[0031] Figure 4 This is a flowchart of the pulse wave transmission velocity measurement method in this embodiment;

[0032] Figure 5 This is a schematic diagram of the first pulse wave transmission time extraction in the pulse wave transmission velocity measurement method according to an embodiment of this application;

[0033] Figure 6 This is a schematic diagram of the pulse wave beat according to the pulse wave transmission velocity measurement method according to an embodiment of this application;

[0034] Figure 7 This is a flowchart of the self-learning PPG template generation process of the pulse wave transmission velocity measurement method according to an embodiment of this application;

[0035] Figure 8 This is a schematic flowchart of a pulse wave transmission velocity measurement method according to another embodiment of this application. Detailed Implementation

[0036] There are various non-invasive methods for assessing arterial dysfunction. Besides intuitive imaging techniques such as CT and MRI, pulse wave velocity (PWV) can be used to assess large artery elasticity. Among these, pulse wave transit time (PTT) is crucial for PWV measurement. Initially, invasive catheter-based AOPWV measurements were used clinically, but this method is invasive and causes harm to the patient. Obtaining AOPWV by recording arterial pulse waves is the most commonly used non-invasive method in clinical practice. Depending on the number of arterial locations required for measurement, it can be divided into single-point and two-point methods. The single-point method estimates PTT using arterial pressure waveforms measured at a single arterial location. The single-point method includes waveform analysis and waveform decomposition. The key to waveform analysis is identifying the first and second systolic peaks of the pressure waveform and calculating their time difference as the PTT. However, because the second systolic peak is not obvious or absent in the elderly, it is difficult to accurately estimate PTT. The key to waveform decomposition lies in using aortic blood flow waveforms and impedance analysis techniques to decompose aortic pressure waveforms into forward and reflected waves, and then using cross-correlation techniques to calculate the PTT. However, this method requires aortic blood flow waves for pressure waveform decomposition. Although the generalized transfer function (GTF) can be used to obtain PTT from the easily measurable radial artery location, its construction and verification are quite difficult. The two-point method estimates PTT by measuring arterial waveforms at two different locations, commonly the carotid and femoral arteries, and calculating their time difference. While this method can also be used at other locations, the accuracy of the results is controversial due to the inclusion of muscular arteries.

[0037] To better understand the purpose, technical solution, and advantages of this application, the application is described and illustrated below in conjunction with the accompanying drawings and embodiments.

[0038] Unless otherwise defined, the technical or scientific terms used in this application shall have the general meaning as understood by one of ordinary skill in the art to which this application pertains. Words such as “a,” “an,” “an,” “the,” “the,” and “these,” used in this application, do not indicate quantitative limitation and may be singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that comprises a series of steps or modules (units) is not limited to the listed steps or modules (units) but may include steps or modules (units) not listed, or may include other steps or modules (units) inherent to such processes, methods, products, or devices. The terms “connected,” “linked,” and “coupled,” used in this application, are not limited to physical or mechanical connections but may include electrical connections, whether direct or indirect. The term “multiple” used in this application refers to two or more. The "and / or" operator describes the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: A alone, A and B simultaneously, and B alone. Typically, the character " / " indicates that the objects before and after it are in an "or" relationship. The terms "first," "second," and "third," etc., used in this application are merely for distinguishing similar objects and do not represent a specific ordering of the objects.

[0039] This embodiment provides a pulse wave velocity measurement system. Figure 1 This is a schematic diagram of the pulse wave transmission velocity measurement system according to this application, as shown below. Figure 1 As shown, the pulse wave velocity measurement system includes: a chest signal acquisition device, a wrist signal acquisition device, a finger signal acquisition device, and a data processing device. The data processing device is connected to the chest signal acquisition device, the wrist signal acquisition device, and the finger signal acquisition device, respectively. The chest signal acquisition device acquires a first signal, which includes at least an electrocardiogram (ECG) signal, and sends the first signal to the data processing device. The wrist signal acquisition device acquires a second signal, which includes at least a wrist pulse wave signal, and sends the second signal to the data processing device. The finger signal acquisition device acquires a third signal, which includes at least a finger pulse wave signal, and sends the third signal to the data processing device. The data processing device determines the pulse wave velocity based on the first signal, the second signal, and the third signal.

[0040] Specifically, the pulse wave velocity measurement system of this embodiment mainly consists of four parts: a chest signal acquisition device, a wrist signal acquisition device, a finger signal acquisition device, and a data processing device. The chest signal acquisition device is used to acquire signals from the user's chest position, i.e., the first signal; more specifically, it is mainly used to acquire signals from the user's left chest position. The first signal includes at least an electrocardiogram (ECG) signal. Understandably, the first signal can also include other signals that can be acquired based on the user's chest position, such as the user's aortic pulse wave signal and blood pressure signal. In one specific embodiment, the chest signal acquisition device can be an ECG recorder, etc. The wrist signal acquisition device is disposed on the user's wrist and is mainly used to acquire signals from the user's wrist position, i.e., the second signal. More specifically, the second signal includes at least a wrist pulse wave signal, i.e., a radial artery pulse wave signal at the wrist. Understandably, the wrist signal acquisition device can also acquire other signals at the user's wrist position, such as heart rate signals and blood pressure signals. In one embodiment, the wrist signal acquisition device can be a smart wearable device, such as a smart bracelet or smartwatch. The finger signal acquisition device is positioned at the user's fingertip and is primarily used to acquire signals from the user's fingertip location, i.e., the third signal. The third signal includes at least the user's fingertip artery pulse wave signal. Understandably, the finger signal acquisition device can also acquire other signals at the user's fingertip location. In one specific embodiment, the finger signal acquisition device can be a clip-on signal acquisition device, a finger sleeve signal acquisition device, or other implementations such as acquisition electrodes. The data processing device is connected to the chest signal acquisition device, wrist signal acquisition device, and finger signal acquisition device via wired and / or wireless connections, respectively, to receive the first, second, and third signals. It processes and calculates based on the first, second, and third signals to determine the user's pulse wave transmission speed. In one embodiment, the data processing device can be implemented using a computer device with a pre-set processing algorithm, or it can be implemented as a dedicated pulse wave signal processing device. Furthermore, the data processing device can also be integrated with interactive devices such as a display screen, projector, keyboard, mouse, touchscreen, and control panel to facilitate viewing and processing by medical personnel.

[0041] The pulse wave velocity measurement system of this application can effectively collect signal characteristics from multiple parts of the user's body. It combines the user's electrocardiogram (ECG) signal, radial artery pulse wave signal from the wrist, and digital artery pulse wave signal from the fingertips to calculate the pulse wave transmission time. By considering the distance between the collected points on the user's body, the pulse wave transmission velocity is determined. Compared to existing single-point measurement methods, this improves the accuracy of pulse wave transmission time measurement.

[0042] In one embodiment, the chest signal acquisition device further includes a chest pulse wave sensor connected to the data processing device; the chest pulse wave sensor is used to acquire the user's aortic pulse wave signal and send the aortic pulse wave signal to the data processing device, so that the data processing device can obtain the user's blood pressure signal based on the aortic pulse wave signal.

[0043] Specifically, Figure 2 This is a schematic diagram of the chest acquisition device of the pulse wave velocity measurement system according to an embodiment of this application, as shown below. Figure 2 As shown, the chest signal acquisition device includes an electrocardiogram (ECG) signal acquisition unit for acquiring the user's ECG signal. In addition, the device integrates a chest pulse wave sensor, i.e., a PPG sensor. This sensor can acquire the user's aortic pulse wave signal. The chest pulse wave sensor is connected to a data processing device via wired and / or wireless connection. The data processing device can analyze the aortic pulse wave signal acquired by the chest pulse wave sensor based on optical principles to determine the user's blood pressure signal. By combining the user's blood pressure signal, ECG signal, and aortic pulse wave signal to calculate the pulse wave velocity, the accuracy of the pulse wave velocity can be improved. Furthermore, acquiring the user's aortic pulse wave signal through the chest pulse wave sensor can improve the acquisition efficiency of the aortic pulse wave signal and shorten the measurement time of the pulse wave velocity.

[0044] In one embodiment, the pulse wave velocity measurement system further includes a blood pressure signal acquisition device connected to the data processing device; the blood pressure signal acquisition device is used to acquire blood pressure signals and send the blood pressure signals to the data processing device, so that the data processing device determines the pulse wave velocity based on the first signal, the second signal, the third signal, and the blood pressure signal.

[0045] Specifically, the user's blood pressure signal is also collected through a separately configured blood pressure signal acquisition device. Figure 3 This is a schematic diagram of a pulse wave velocity measurement system according to another embodiment of this application, as shown below. Figure 3 As shown, the blood pressure signal acquisition device is directly connected to the data processing device, transmitting the blood pressure signal to the data processing device via wired and / or wireless transmission. By setting up an independent blood pressure signal acquisition device, the scalability and adaptability of the pulse wave velocity measurement system can be greatly improved. More accurate user blood pressure signals can be obtained by upgrading the blood pressure signal acquisition device.

[0046] In one embodiment, the blood pressure signal acquisition device is an arm-type blood pressure acquisition device. Specifically, this embodiment provides a specific implementation of a blood pressure signal acquisition device. Existing blood pressure measurement devices include two types: arm-type and wrist-type. Preferably, the blood pressure acquisition device uses an arm-type blood pressure acquisition device with higher measurement accuracy, such as a blood pressure monitor. The working principle of a blood pressure monitor is mainly that the wrist cuff is inflated to compress the measurement site, blocking blood flow, and then the blood flows again by releasing the gas from the wrist cuff. Blood pressure measurement is based on the changes in the sound and vibration of the blood flow when the blood flows again.

[0047] In one embodiment, the wrist signal acquisition device includes a photoplethysmography (PPG) sensor connected to the data processing device. The PPG sensor is used to acquire the second signal and transmit it to the data processing device. Specifically, the wrist signal acquisition device is equipped with a PPG sensor. PPG is short for photoplethysmography, also known as photoplethysmography. The PPG sensor is a technique for measuring pulse waves based on optical principles. Through the PPG sensor, the radial artery pulse wave signal of the user's wrist can be acquired.

[0048] In one embodiment, the finger signal acquisition device is a finger clip / finger sleeve type acquisition device. Specifically, the finger clip / finger sleeve structure is a type of medical device implementation. Through this structure, the finger signal acquisition device can be securely and reliably placed on the user's fingertip, allowing for real-time and stable acquisition of the user's fingertip artery pulse wave signal.

[0049] In one embodiment, the finger clip / finger sleeve type acquisition device adjusts the length of the finger clip / finger sleeve via a stepless adjustment method, and records and stores the length of the finger clip / finger sleeve via an electrical signal to the data processing device. Specifically, the stepless adjustment method helps to adapt to different users' finger lengths and diameters, improving user comfort, and making the contact between the finger signal acquisition device and the user's finger more stable and reliable, thus improving the signal quality of the acquired third signal. Furthermore, by recording the adjusted finger clip / finger sleeve length via an electrical signal, the transmission distance of the pulse wave from the wrist to the fingertip can be accurately recorded, improving the accuracy of the final obtained pulse wave transmission speed.

[0050] It should be noted that the above modules can be functional modules or program modules, and can be implemented through software or hardware. For modules implemented through hardware, the above modules can reside in the same processor; or the above modules can be located in different processors in any combination.

[0051] This embodiment provides a method for measuring pulse wave velocity, which is adapted to the pulse wave velocity measurement system of this application embodiment. Figure 4 This is a flowchart of the pulse wave propagation velocity measurement method in this embodiment, as follows: Figure 4 As shown, the process includes the following steps:

[0052] Step S401: Obtain the user's target detection signal, which includes at least an electrocardiogram signal, a wrist pulse wave signal, a finger pulse wave signal, and a blood pressure signal.

[0053] Step S402: Determine the first pulse wave transmission time based on the electrocardiogram signal, the wrist pulse wave signal, and the finger pulse wave signal.

[0054] Step S403: Determine the second pulse wave transmission time based on the electrocardiogram signal, the wrist pulse wave signal, the finger pulse wave signal, and the blood pressure signal.

[0055] Step S404: Obtain the pulse wave transmission distance between the user's wrist and fingers, and determine the pulse wave transmission speed based on the first pulse wave transmission time, the second pulse wave transmission time, and the pulse wave transmission distance.

[0056] Through the above steps, the pulse wave transmission velocity measurement method of this application calculates two pulse wave transmission times based on multiple different signals, and determines the pulse wave transmission velocity based on these two pulse wave transmission times and the pulse wave transmission distance. Compared with the prior art, which uses a single method to obtain a pulse wave transmission time to calculate the pulse wave transmission velocity, this application comprehensively considers the two obtained pulse wave transmission times, thereby improving the accuracy of pulse wave transmission velocity calculation.

[0057] In one embodiment, determining the first pulse wave transmission time based on the electrocardiogram (ECG) signal, the wrist pulse wave signal, and the finger pulse wave signal includes: determining a first transmission time based on the time interval between corresponding peaks of the ECG signal and the wrist pulse wave signal; determining a second transmission time based on the time interval between corresponding peaks of the ECG signal and the finger pulse wave signal; and determining the first pulse wave transmission time based on the first transmission time and the second transmission time.

[0058] Specifically, the pulse wave velocity measurement method in this embodiment is adapted to the aforementioned pulse wave velocity measurement system. Based on the pulse wave velocity measurement system, the ECG signal, aortic pulse wave signal, and arterial blood pressure value at the user's left chest are measured using a chest signal acquisition device; the radial artery pulse wave at the wrist is acquired using a wrist signal acquisition device; and the digital artery pulse wave at the fingertip is acquired using a finger signal acquisition device in the form of an external finger clip. Based on the ECG signal acquired by the chest signal acquisition device, the radial artery pulse wave signal PPG_W acquired by the wrist signal acquisition device, and the digital artery pulse wave signal PPG_F acquired by the external finger clip fingertip ... Figure 5 This is a schematic diagram of the first pulse wave transmission time extraction according to the pulse wave transmission velocity measurement method of this application, as shown in the figure. Figure 5 As shown, the horizontal axis of the curve represents time in seconds, and the vertical axis represents amplitude in volts. The three curves, from top to bottom, represent the electrocardiogram (ECG), the radial artery pulse wave signal (ElbowPPG), and the fingertip pulse wave signal (FingerPPG). The first transmission time is determined based on the peak position of the ECG signal and the corresponding peak position of the radial artery pulse wave. The second transmission time is determined based on the waveform position of the fingertip pulse wave corresponding to the same peak position of the ECG signal. The first pulse wave transmission time PTT1 is obtained based on the difference between the first and second transmission times. This embodiment of the application uses the peak position of the ECG signal as a reference. Compared to directly calculating the first pulse wave transmission time based on the peak positions of the radial artery pulse wave and the fingertip pulse wave, this application effectively avoids calculation errors caused by peak correspondence errors. Furthermore, using the ECG peak position as a reference effectively improves the calculation accuracy of the first pulse wave transmission time.

[0059] In one embodiment, the second pulse wave transit time (PTT2) is obtained based on a method of establishing a generalized transfer function model and a blood flow transfer function model. Traditional generalized transfer function models are generated offline in a single instance. However, due to variations in factors such as blood vessel wall and peripheral resistance, the amplitude and morphology of the pulse wave continuously change. This embodiment proposes a method for dynamically constructing the generalized transfer function model to avoid this variation error.

[0060] First, this application proposes a self-learning photoplethysmography (PPG) beat evaluation method. It utilizes template generation to dynamically generate average pulse wave templates for the left thoracic aorta, radial artery at the wrist, and digital artery at the fingertips. During the pulse wave measurement phase, before an average template is generated, a target region with a certain time window is set. When the number of pulse wave beats within the window exceeds N, continuous comparative analysis is performed. Figure 6 This is a schematic diagram of the pulse wave beat according to the pulse wave transmission velocity measurement method according to an embodiment of this application, such as... Figure 6 As shown, a beat is defined as a waveform between two adjacent troughs. Figure 7 This is a flowchart illustrating the self-learning PPG template generation process of the pulse wave velocity measurement method according to an embodiment of this application, such as... Figure 7 As shown, the analysis process includes: when the number of pulse wave beats within the window is greater than N, calculating the correlation coefficient of adjacent beats within the window, resulting in a sequence of N-1 correlation coefficients [coeff(1), ..., coeff(N-1)]. The calculation method for the correlation coefficient includes, but is not limited to, the Pearson correlation coefficient calculation method. Then, each correlation coefficient is compared sequentially with a first set threshold. If the current correlation coefficient is greater than the first set threshold, the count M is incremented by 1 to count the number of correlation coefficients in the sequence that are greater than the first set threshold. If this number is greater than the first quantity threshold (e.g., the first quantity threshold can be set to 3*(N-1) / 4), then all pulse wave beats within the window, i.e., the target area, that are greater than the first set threshold, are taken as candidate beats for the template to be formed. All templates to be formed are normalized and then weighted to obtain the average template. Furthermore, if the number of correlation coefficients in the sequence greater than the first set threshold is less than or equal to the first threshold, and the beat correlation coefficient in the target region is greater than the second threshold 2*(N-1) / 4, then all pulse wave beats in the target region greater than the first set threshold are taken as candidate beats to be formed as templates, and the feature value of each candidate beat to be formed as template is calculated. The feature value includes, but is not limited to, the perfusion index P. SQI Pulse wave deviation S SQI Pulse wave kurtosis K SQI Average power E SQI Then, the coefficient of variation sequence of each dimension is calculated. If all values ​​are less than the second set threshold, the average template is obtained by normalizing and weighting the candidate beats to be formed; otherwise, template acquisition fails, and the process waits for the next target region to be formed. The calculation methods for feature values ​​and coefficient of variation sequence are as follows:

[0061]

[0062]

[0063]

[0064]

[0065] CV=|x i -x m | / x m

[0066] Where x in the above formula max This represents the maximum amplitude of each initial pulse wave beat corresponding to each correlation coefficient exceeding the first threshold, x. min This represents the minimum amplitude of each initial pulse wave beat corresponding to each correlation coefficient exceeding the first threshold, x. i This indicates the amplitude of each initial pulse wave beat corresponding to each correlation coefficient exceeding the first threshold. σ represents the mean amplitude of each initial pulse wave beat corresponding to each correlation coefficient greater than the first threshold, σ represents the variance of each initial pulse wave beat amplitude corresponding to each correlation coefficient greater than the first threshold, and N represents the number of initial pulse wave beats corresponding to each correlation coefficient greater than the first threshold. This represents the norm of the mean amplitude of each initial pulse wave beat corresponding to each correlation coefficient greater than the first threshold. Optionally, the computer device can obtain the coefficient of variation of each feature value according to the following formula: CV = |x i -x m | / x m In the formula, CV represents the coefficient of variation of each eigenvalue, x i This represents the skewness of each initial pulse wave beat corresponding to each correlation coefficient exceeding the first threshold, x. m This represents the mean of the skewness of each initial pulse wave beat corresponding to each correlation coefficient being greater than the first threshold.

[0067] In one embodiment, after the average template is generated, each pulse wave beat is compared with the average template in terms of similarity (correlation coefficient), and the average template is updated according to certain rules. In one embodiment, the average template update rules are as follows:

[0068] Template obj =0.9×Template obj +0.1×PPG seg

[0069] Among them, PPG seg Indicates the target pulse wave beat, Template obj This indicates the updated target pulse wave beat.

[0070] Secondly, based on the self-learning photoplethysmography pulse wave beat evaluation method of the above embodiments, the calculation method for the second pulse wave transmission time includes: constructing a generalized transfer function model between the radial artery pulse wave and the aortic pulse wave, and a blood flow transfer function model between the digital artery pulse wave and the aortic pulse wave, based on dynamically generated pulse wave templates. Wherein, the generalized transfer function model GTF(S) = Laplace transform of the average template waveform of the left thoracic aorta C(S) / Laplace transform of the average template waveform of the radial artery at the wrist W(S); the blood flow transfer function model BTF(S) = Laplace transform of the average template blood flow waveform of the left thoracic aorta BC(S) / Laplace transform of the average template blood flow waveform of the digital artery at the fingertips BF(S).

[0071] After generating the generalized transfer function model and the blood flow transfer function model, the radial artery pulse wave signal at the wrist is calibrated in conjunction with the blood pressure value measured by the left chest dynamic electrocardiogram recorder to obtain the aortic pressure waveform p(t) with blood pressure characteristics; independent component analysis is performed on the fingertip digital artery pulse wave to obtain the digital artery blood flow waveform, and combined with the blood flow transfer function model, the aortic blood flow waveform q(t) is obtained; Fourier analysis is used to calculate the characteristic impedance of the aortic pressure waveform p(t) and the aortic blood flow waveform q(t), and the aortic pressure waveform is decomposed into forward wave and reflected wave using the impedance formula. The normalized cross-correlation coefficient of the two is calculated to obtain the pulse wave transmission time PTT2.

[0072] In one embodiment, determining the pulse wave transmission speed based on the first pulse wave transmission time, the second pulse wave transmission time, and the pulse wave transmission distance includes: acquiring multiple first pulse wave transmission times within a preset period to establish a first pulse wave transmission time set; acquiring multiple second pulse wave transmission times within a preset period to establish a second pulse wave transmission time set; determining a correlation coefficient between the first pulse wave transmission time set and the second pulse wave transmission time set; if the correlation coefficient is less than or equal to a preset threshold, then re-acquiring the first and second pulse wave transmission times; if the correlation coefficient is greater than the preset threshold, then determining a first average pulse wave transmission time based on the first pulse wave transmission time set; determining a second average pulse wave transmission time based on the second pulse wave transmission time set; determining a target transmission time based on the first average pulse wave transmission time and the second average pulse wave transmission time; and determining the pulse wave transmission speed based on the target transmission time and the pulse wave transmission distance.

[0073] Specifically, after determining the first pulse wave transmission time PTT1 and the second pulse wave transmission time PTT2 according to the method of the above embodiment, a fixed time period T is used. mEstablish a time series correlation coefficient set using PTT1 and PTT2 [PTT1] T1 PTT1 T2 PTT1 Tm ] and [PTT2 T1 PTT2 T2 PTT2 Tm The two sequences are denoted as PTT1_LIST and PTT2_LIST, respectively. Calculate the correlation coefficient X between the two sequences. corr If X corr If the target pulse wave transmission time is greater than a preset threshold THR, the calculated result is output; if it is less than the preset threshold, there is no output for the current time period. In one embodiment, the target pulse wave transmission time is calculated as follows:

[0074] PTT=α×mean(PTT1_LIST)+β×mean(PTT2_LIST)

[0075] Here, α and β are user-preset calculation parameters, used to represent the calculation weights of the average value of the first pulse wave transmission time series and the average value of the second pulse wave transmission time series, respectively. In one embodiment, the sum of α and β is 1.

[0076] After obtaining the target pulse wave transit time (PTT), the recording length L of the finger clip / finger sleeve is obtained, and the pulse wave transmission velocity is calculated using the formula... The pulse wave velocity (PWV) can then be obtained. To ensure the accuracy of the pulse wave velocity, the pulse module of the finger clip / sleeve must be adjusted to the appropriate transmission line length when worn, which should be adapted to the distance from the user's wrist to the fingertip.

[0077] Based on the above embodiments, this application proposes a pulse wave velocity measurement system and method. The system includes a chest signal acquisition device, a wrist signal acquisition device, and a finger signal acquisition device, all simultaneously capable of PPG, ECG, and blood pressure monitoring. The wrist signal acquisition device is a PPG sensor. The finger signal acquisition device is a finger clip / finger sleeve type pulse monitoring module, and the length of the finger clip / finger sleeve is flexibly and infinitely adjustable, allowing for length adjustment according to the actual wearing distance. The length information is recorded as an electrical signal in a data processing device or the data storage unit of the wrist signal acquisition device via analog-to-digital conversion. The chest signal acquisition device acquires ECG signals, aortic pulse wave signals, and arterial blood pressure values ​​at the left chest. The wrist signal acquisition device acquires radial artery pulse waves at the wrist. The external finger clip / finger sleeve type finger signal acquisition device acquires digital artery pulse waves at the fingertips. Adapted to this pulse wave velocity measurement system, the present application also provides a pulse wave velocity measurement method. Figure 8 This is a schematic flowchart of a pulse wave velocity measurement method according to another embodiment of this application, as shown below. Figure 8 As shown, the transmission time (PTT1) of the wrist-to-finger pulse wave signal is obtained using the acquired radial artery pulse wave at the wrist and the digital artery pulse wave at the fingertips, based on the ECG signal from the left chest. Simultaneously, using the acquired aortic pulse wave from the left chest, radial artery pulse wave from the wrist, and digital artery pulse wave from the fingertips, a self-learning photoplethysmography pulse wave beat evaluation method is employed. Template generation is used to construct real-time robust generalized transfer function models between the radial and aortic pulse waves, and blood flow transfer function models between the digital and aortic pulse waves. The generalized transfer function models and arterial blood pressure values ​​are used to convert the radial artery pulse wave at the wrist into an aortic pressure waveform, and the blood flow transfer function models are used to convert the digital artery blood flow wave into an aortic blood flow wave. The generated aortic blood flow wave and aortic pressure waveform are decomposed into forward and backward waves using impedance formulas, and the transmission time (PTT2) is obtained using normalized cross-correlation coefficients. By establishing a time series correlation coefficient set using PTT1 and PTT2 and outputting the final pulse wave transit time (PTT), and supplementing this with the length recorded by a finger clip / finger sleeve, the pulse wave propagation velocity (PWV) can be obtained. The pulse wave propagation velocity measurement system and method of this application can stably and accurately obtain pulse wave propagation velocity using the user's upper limb pulse wave, electrocardiogram, and blood pressure information. The process is simple, feature-rich, and highly scalable.

[0078] It should be noted that the steps shown in the above process or in the flowchart of the accompanying figures can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0079] It should be understood that the specific embodiments described herein are merely illustrative of the application and not intended to limit it. All other embodiments derived by those skilled in the art based on the embodiments provided in this application without inventive effort are within the scope of protection of this application.

[0080] Obviously, the accompanying drawings are merely some examples or embodiments of this application. Those skilled in the art can apply this application to other similar situations based on these drawings without any creative effort. Furthermore, it is understood that although the work done in this development process may be complex and lengthy, for those skilled in the art, certain design, manufacturing, or production modifications made based on the technical content disclosed in this application are merely conventional technical means and should not be considered as insufficient disclosure of this application.

[0081] The term "embodiment" in this application refers to a specific feature, structure, or characteristic described in connection with an embodiment that may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily imply the same embodiment, nor does it imply that it is mutually exclusive with or independent of other embodiments. It will be clearly or implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0082] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of patent protection. 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 scope of protection of this application. Therefore, the scope of protection of this application should be determined by the appended claims.

Claims

1. A pulse wave transmission velocity measurement system, characterized in that, include: The system includes a chest signal acquisition device, a wrist signal acquisition device, a finger signal acquisition device, and a data processing device. The data processing device is connected to the chest signal acquisition device, the wrist signal acquisition device, and the finger signal acquisition device, respectively. The chest signal acquisition device is used to acquire a first signal, which includes at least an electrocardiogram signal and an aortic pulse wave signal, and to send the first signal to the data processing device. The wrist signal acquisition device is used to acquire a second signal, the second signal including at least a wrist pulse wave signal, and to send the second signal to the data processing device; the wrist pulse wave signal is a radial artery pulse wave signal at the wrist. The finger signal acquisition device is used to acquire a third signal, which includes at least a finger pulse wave signal, and to send the third signal to the data processing device. The data processing device is used to determine the pulse wave transmission speed based on the first signal, the second signal, and the third signal; The data processing device is further configured to: determine a first pulse wave transmission time based on the electrocardiogram signal, the wrist pulse wave signal, and the finger pulse wave signal; determine a second pulse wave transmission time based on the electrocardiogram signal, the wrist pulse wave signal, the finger pulse wave signal, and the blood pressure signal; determine a target transmission time by analyzing the correlation coefficients between multiple first pulse wave transmission times and multiple second pulse wave transmission times within a preset period; and determine the pulse wave transmission speed based on the pulse wave transmission distance and the target transmission time. The data processing device is further configured to, during the pulse wave measurement phase, when the number of pulse wave beats within a preset time window is greater than N, calculate the correlation coefficients of adjacent beats within the time window and compare each correlation coefficient with a first preset threshold to obtain the number of correlation coefficients greater than the first preset threshold; if the number of correlation coefficients greater than the first preset threshold is greater than a first quantity threshold, then determine all pulse wave beats corresponding to correlation coefficients greater than the first preset threshold as candidate beats to be formed as templates, and obtain a pulse wave template after normalization and weighted processing of all the templates to be formed; based on the dynamically generated pulse wave template, construct a generalized transfer function model between the radial artery pulse wave signal at the wrist and the aortic pulse wave signal, and a blood flow transfer function model between the finger pulse wave signal and the aortic pulse wave signal; and determine the second pulse wave transmission time based on the generalized transfer function model and the blood flow transfer function model.

2. The pulse wave transmission velocity measurement system according to claim 1, characterized in that, The data processing device is further configured to determine all pulse wave beats corresponding to correlation coefficients greater than the first set threshold as candidate beats to be formed template if the number of correlation coefficients greater than the first set threshold is less than or equal to the first set threshold and greater than the second set threshold. Calculate the feature value of each candidate beat to be formed as well as the coefficient of variation of each feature value; if each coefficient of variation is less than a second set threshold, then the candidate beat to be formed is processed by normalized weighted average to obtain the pulse wave template.

3. The pulse wave transmission velocity measurement system according to claim 1, characterized in that, The chest signal acquisition device also includes a chest pulse wave sensor, which is connected to the data processing device. The chest pulse wave sensor is used to acquire the user's aortic pulse wave signal and send the aortic pulse wave signal to the data processing device, so that the data processing device can obtain the user's blood pressure signal based on the aortic pulse wave signal.

4. The pulse wave transmission velocity measurement system according to claim 1, characterized in that, The pulse wave transmission velocity measurement system further includes a blood pressure signal acquisition device, which is connected to the data processing device. The blood pressure signal acquisition device is used to acquire blood pressure signals and send the blood pressure signals to the data processing device, so that the data processing device can determine the pulse wave transmission velocity based on the first signal, the second signal, the third signal, and the blood pressure signal.

5. The pulse wave transmission velocity measurement system according to claim 4, characterized in that, The blood pressure signal acquisition device is an arm-type blood pressure acquisition device.

6. The pulse wave transmission velocity measurement system according to claim 1, characterized in that, The wrist signal acquisition device includes a photoplethysmography sensor, which is connected to the data processing device; the photoplethysmography sensor is used to acquire the second signal and send the second signal to the data processing device.

7. The pulse wave transmission velocity measurement system according to claim 1, characterized in that, The finger signal acquisition device is a finger clip / finger sleeve type acquisition device.

8. The pulse wave transmission velocity measurement system according to claim 7, characterized in that, The finger clip / finger sleeve type acquisition device adjusts the length of the finger clip / finger sleeve through stepless adjustment, and records and stores the length of the finger clip / finger sleeve through an electrical signal to the data processing device.

9. A method for measuring pulse wave transmission velocity, characterized in that, include: Acquire the user's target detection signal, which includes at least an electrocardiogram signal, a wrist pulse wave signal, a finger pulse wave signal, and a blood pressure signal; The first pulse wave transmission time is determined based on the electrocardiogram signal, the wrist pulse wave signal, and the finger pulse wave signal. The second pulse wave transmission time is determined based on the electrocardiogram signal, the wrist pulse wave signal, the finger pulse wave signal, and the blood pressure signal. The pulse wave transmission distance between the user's wrist and fingers is obtained, and the pulse wave transmission speed is determined based on the first pulse wave transmission time, the second pulse wave transmission time, and the pulse wave transmission distance. Determining the pulse wave transmission speed based on the first pulse wave transmission time, the second pulse wave transmission time, and the pulse wave transmission distance includes: Obtain multiple first pulse wave transmission times within a preset period and establish a set of first pulse wave transmission times; Obtain multiple second pulse wave transmission times within a preset period and establish a set of second pulse wave transmission times; Determine the correlation coefficient between the first pulse wave transit time set and the second pulse wave transit time set. If the correlation coefficient is less than or equal to a preset threshold, then the first pulse wave transmission time and the second pulse wave transmission time are reacquired. If the correlation coefficient is greater than a preset threshold, then the first average pulse wave transmission time is determined based on the first pulse wave transmission time set; and the second average pulse wave transmission time is determined based on the second pulse wave transmission time set. The target transmission time is determined based on the first average pulse wave transmission time and the second average pulse wave transmission time. The pulse wave transmission speed is determined based on the target transmission time and the pulse wave transmission distance.

10. The pulse wave transmission velocity measurement method according to claim 9, characterized in that, Determining the first pulse wave transmission time based on the electrocardiogram signal, the wrist pulse wave signal, and the finger pulse wave signal includes: The first transmission time is determined based on the time interval between the corresponding peaks of the electrocardiogram signal and the wrist pulse wave signal; The second transmission time is determined based on the time interval between the corresponding peaks of the electrocardiogram signal and the finger pulse wave signal; The first pulse wave transmission time is determined based on the first transmission time and the second transmission time.

Images