WO2020182010A1 - 确定脉搏传输时间的方法、动脉硬化检测设备及系统 - Google Patents

确定脉搏传输时间的方法、动脉硬化检测设备及系统 Download PDF

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WO2020182010A1
WO2020182010A1 PCT/CN2020/077513 CN2020077513W WO2020182010A1 WO 2020182010 A1 WO2020182010 A1 WO 2020182010A1 CN 2020077513 W CN2020077513 W CN 2020077513W WO 2020182010 A1 WO2020182010 A1 WO 2020182010A1
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arteriosclerosis
pulse wave
signal
pulse
slave
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PCT/CN2020/077513
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English (en)
French (fr)
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杜辉
刘金叶
曹帅
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京东方科技集团股份有限公司
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Priority to US16/963,706 priority Critical patent/US20210369235A1/en
Publication of WO2020182010A1 publication Critical patent/WO2020182010A1/zh

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • A61B5/0004—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by the type of physiological signal transmitted
    • A61B5/0006—ECG or EEG signals
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/02007—Evaluating blood vessel condition, e.g. elasticity, compliance
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/021—Measuring pressure in heart or blood vessels
    • A61B5/02108—Measuring pressure in heart or blood vessels from analysis of pulse wave characteristics
    • A61B5/02125—Measuring pressure in heart or blood vessels from analysis of pulse wave characteristics of pulse wave propagation time
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/33—Heart-related electrical modalities, e.g. electrocardiography [ECG] specially adapted for cooperation with other devices
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/346—Analysis of electrocardiograms
    • A61B5/349—Detecting specific parameters of the electrocardiograph cycle
    • A61B5/352—Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/02—Measuring pulse or heart rate
    • A—HUMAN NECESSITIES
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    • A61B8/08—Detecting organic movements or changes, e.g. tumours, cysts, swellings
    • A61B8/0891—Detecting organic movements or changes, e.g. tumours, cysts, swellings for diagnosis of blood vessels
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/5215—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data
    • A61B8/5223—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data for extracting a diagnostic or physiological parameter from medical diagnostic data
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
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    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/48—Diagnostic techniques
    • A61B8/485—Diagnostic techniques involving measuring strain or elastic properties

Definitions

  • the present disclosure relates to a method for determining pulse wave transmission time, arteriosclerosis detection equipment and system.
  • Cardiovascular deaths account for more than 40% of the residents’ disease deaths, ranking first, much higher than tumors and other diseases.
  • Arteriosclerosis testing equipment is an important means for cardiovascular disease risk screening.
  • arteriosclerosis detection methods mainly use blood pressure and ECG signals to judge the degree of arteriosclerosis, and the accuracy is not high enough.
  • the existing arteriosclerosis detection equipment mainly consists of limb blood pressure measurement modules, ECG detectors, heart sound modules and other modules.
  • most of the optional Doppler ultrasound is used for carotid femoral artery transmission speed measurement, resulting in the overall equipment is large in size, expensive, and cumbersome to operate, and is not suitable for promotion in primary medical and physical examination institutions.
  • a method for determining the pulse transmission time comprising: receiving a single-lead ECG signal; receiving a pulse wave signal of at least one body part, the pulse wave signal being set in a corresponding The body part is detected by the miniature ultrasonic detector; the R wave of the single-lead ECG signal is used as the starting point and the characteristic point of the pulse wave signal of at least one body part is used as the end point to determine the pulse transmission time.
  • the characteristic points of the pulse wave signal include at least one of a valley of the pulse wave, a maximum point of a slope rise based on the valley, and a peak.
  • the at least one body part includes limbs.
  • an arteriosclerosis detection device including: a communication interface configured to receive a single-lead ECG signal and an ultrasonic pulse wave signal of at least one body part; a processor, including a memory, on which Computer-executable instructions are stored, and when the processor executes the computer-executable instructions, the method for determining the pulse transmission time according to any one of the embodiments of the first aspect of the present disclosure is implemented.
  • the processor further implements the following steps when executing the computer-executable instructions: based on the pulse transmission time of each body part and the sensing point of the single-lead ECG signal and the pulse wave signal The distance between the sensing points determines the pulse transmission speed from the heart to each body part.
  • the at least one body part includes limbs
  • the processor further implements the following step when executing the computer-executable instructions: determining the blood pressure BP of the corresponding limbs according to the pulse transmission time PTT of the limbs and the following formula:
  • ⁇ is a quantity characterizing blood vessel characteristics, and the value range is 0.016-0.018mmHg -1 , and S is the distance between the sensing point of the single-lead ECG signal and the sensing point of the pulse wave signal, E 0 is the elastic modulus when the pressure of the blood vessel wall is zero, BP is the blood pressure, PTT is the pulse transit time, ⁇ is the density of the blood, d is the inner diameter of the blood vessel, and a is the coefficient related to individual characteristics and can pass actual measurement data Fitted;
  • the processor further implements the following steps when executing the computer-executable instructions: the blood pressure BP of the limbs, the pulse transit time PTT of the limbs, the cardiac output per minute CO and the peripheral resistance TPR are used as arteries.
  • SV is the cardiac output per stroke
  • K is the pulse wave waveform value
  • T is the pulse wave period
  • P s is the systolic blood pressure
  • P d is the diastolic blood pressure
  • P m is the average arterial pressure
  • CO is the cardiac output per minute
  • TPR is the peripheral resistance.
  • the processor further implements the following steps when executing the computer-executable instructions: determining the damage index of each arteriosclerosis-related parameter to evaluate the degree of arteriosclerosis, and the damage index F of each arteriosclerosis-related parameter is used as follows Formula to calculate:
  • V is the actual value of arteriosclerosis-related parameters
  • RC is the upper limit of the normal range of arteriosclerosis-related parameters
  • RF is the lower limit of the normal range of arteriosclerosis-related parameters
  • F is the damage index of arteriosclerosis-related parameters
  • ⁇ and ⁇ are It is obtained by fitting a data set based on clinically measured arteriosclerosis related parameters and clinically estimated corresponding damage index.
  • an arteriosclerosis detection system including the arteriosclerosis detection device according to any one of the embodiments of the second aspect of the present disclosure, and the system further includes: a first slave, including The ECG detector is configured to sense a single-lead ECG signal of the user; the second slave machine, including a miniature ultrasonic detector, is configured to be worn on at least one body part of the user to detect its ultrasonic pulse wave signal.
  • the first slave further includes: a first microprocessor configured to process the single-lead ECG signal to obtain R wave information of the single-lead ECG signal; A communication circuit configured to transmit the R wave information of the single-lead ECG signal; the second slave computer further includes: a second microprocessor configured to process the ultrasonic pulse wave signal to obtain The feature point of the ultrasonic pulse wave signal; the second communication circuit is configured to transmit the feature point of the ultrasonic pulse wave signal.
  • each of the first slave machine and the second slave machine includes a timer configured to determine the first time information of the corresponding slave machine, and the arteriosclerosis detection device communicates with the second slave machine via the communication interface.
  • a slave and a second slave send second time information, and each of the first and second microprocessors is also configured to calculate the first time information of the corresponding slave and the first time information.
  • the first communication circuit and the second communication circuit are each further configured to send their respective time deviation information to the arteriosclerosis detection device.
  • the communication interface of the arteriosclerosis detection device is further configured to receive the time offset information; the processor of the arteriosclerosis detection device is further configured to: compare the time offset information to the first slave The signal transmitted by the second slave is compensated accordingly.
  • the micro ultrasonic detector is further configured to sense a blood vessel wall signal and a blood flow signal; the second microprocessor is further configured to at least be based on the blood vessel wall signal and the blood flow signal Obtain one of the following parameters: arterial elastic coefficient, blood vessel wall thickness, and blood viscosity.
  • the number of the second slaves is at least four, and they are respectively configured to obtain the ultrasonic pulse wave signals of the limbs.
  • the arteriosclerosis detection system further includes a power supply configured to supply power to the arteriosclerosis detection system.
  • the arteriosclerosis detection system further includes: a display configured to display evaluation information of the degree of arteriosclerosis.
  • Fig. 1 is a flowchart of a method for determining pulse transmission time according to an embodiment of the present disclosure
  • FIG. 2 is a schematic diagram of the R-wave interval of the ECG signal as a reference and the pulse transmission time calculated by using the characteristic points of the pulse wave signal according to an embodiment of the present disclosure
  • Figure 3 is a comparison diagram of pulse wave transmission in the two conditions of good blood vessels and vascular hardening
  • FIG. 4 is a schematic structural diagram of an arteriosclerosis detection device according to an embodiment of the present disclosure.
  • Figure 5 is a schematic diagram of the relationship between pulse transmission time and pulse transmission speed and the degree of vascular stiffness
  • Figure 6 is a periodic waveform diagram of the pulse wave
  • Fig. 7 is a schematic structural diagram of an arteriosclerosis detection system according to an embodiment of the present disclosure.
  • FIG. 8 is a schematic structural diagram of an arteriosclerosis detection system according to an embodiment of the present disclosure.
  • Fig. 9 is a working flow chart of the arteriosclerosis detection system according to an embodiment of the present disclosure.
  • the present disclosure provides a method for determining pulse wave transmission time, arteriosclerosis detection equipment and system, which can more accurately determine pulse transmission based on single-lead ECG signals and ultrasonic pulse wave signals Time
  • arteriosclerosis detection equipment can be integrated with single-lead ECG detector and miniature ultrasonic pulse wave detection module to obtain arteriosclerosis detection system, which can easily and accurately determine the important parameters of arteriosclerosis, including pulse transmission time, for further
  • the device is small in size, low in price, easy to use, and high in accuracy.
  • the method for determining pulse wave transmission time, arteriosclerosis detection equipment and system can determine the pulse transmission time more accurately based on single-lead ECG signals and ultrasonic pulse wave signals.
  • the arteriosclerosis detection equipment can be compared with single-lead ECG signals.
  • the detector and the micro ultrasonic pulse wave detection module are integrated to obtain an arteriosclerosis detection system, which can conveniently and accurately determine the parameters that are important to the degree of arteriosclerosis, including pulse transmission time, so as to further determine the degree of arteriosclerosis.
  • the system is small in size and expensive Low, easy to use, and high accuracy.
  • Fig. 1 is a flowchart of a method for determining a pulse transmission time according to an embodiment of the present disclosure. As shown in Fig. 1, the present disclosure provides a method for determining a pulse transmission time. The method includes steps S101 to S103:
  • a single-lead ECG signal is received.
  • the single-lead ECG signal may be the ECG signal of any lead such as limb leads and chest leads, which is not specifically limited herein.
  • some portable ECG detection devices such as smart watches that include ECG detection functions
  • a pulse wave signal of at least one body part is received, and the pulse wave signal is detected by a micro ultrasonic detector disposed at the corresponding body part, such as the user's wrist, neck, ankle, and so on.
  • the miniature ultrasonic detector can, for example, use a miniaturized miniature ultrasonic sensor to accurately capture the arterial pulsation of the local measurement site via Doppler ultrasound. Compared with other pulse wave signal detection devices, the size is small and the positioning in the time domain is more accurate. .
  • the miniature ultrasonic sensor can be flexibly loaded on the end parts of the body, such as limbs, etc., so as to ensure a sufficient distance between the sensing position of the pulse wave signal and the sensing position of the ECG signal, which is beneficial to reduce the error of signal processing and pulse transmission Time disturbance can reduce the calculation error of pulse transmission time.
  • the R wave of the single-lead ECG signal is used as the starting point and the characteristic point of the pulse wave signal of at least one body part is used as the end point to determine the pulse transmission time.
  • the two signals are first preprocessed, such as filtering noise, removing baseline drift, etc., and then extracting the R-wave information and pulse of the single-lead ECG signal.
  • the characteristic points of the wave signal, and the methods for extracting the R wave information of the ECG signal and the characteristic points of the pulse wave signal include multiple methods, which are not specifically limited here.
  • the method for determining the pulse wave transmission time takes the R wave of the single-lead ECG signal as the starting point and the characteristic point of the pulse wave signal of the body part detected by the micro ultrasonic detector as the end point, starting from the heart pumping start point Start timing to determine the pulse transmission time more accurately.
  • this method uses the signals collected by the single-lead ECG detector and the micro ultrasonic detector, which are more user-friendly to wear and use, so that it can improve the user experience while accurately detecting the important significance of arterial stiffness. Pulse transit time.
  • the characteristic point of the pulse wave signal includes at least one of a trough of the pulse wave, a maximum point of a slope rise based on the trough, and a peak. Shows the R-wave interval (labeled RR) of the ECG signal as a reference, and the pulse transmission time calculated using the trough of the pulse wave, the maximum point of the slope rise based on the trough as the base point, and the peak as the characteristic points ( Identified as PTT1, PTT2 and PTT3).
  • the peak of the pulse wave is used as the end point to calculate the pulse transmission time.
  • the inventor conducted a large number of clinical trials based on these three characteristic points, and found that the pulse transmission time calculated by using the peak of the pulse wave as the end point can be derived (the derivation method will be described in detail below, and will not be repeated here. ) More accurate blood pressure value of the corresponding body part, and the highest correlation with arteriosclerosis.
  • At least one body part includes limbs, so as to analyze the vascular condition of the user’s limbs according to the pulse transmission time of the limbs, and the limbs are far away from the heart, which helps to reduce the disturbance of the pulse transmission time caused by the error of signal processing. In turn, the calculation error of the pulse transit time can be reduced.
  • the pulse transit time reflects the degree of vascular stiffness to a certain extent. As shown in Figure 3, healthy people's blood vessels have better elasticity, pulse transmission time is relatively long, arterial blood vessels have hardened, and pulse transmission time is short.
  • the arteriosclerosis detection device 100 includes a communication interface 110 and a processor 120, Wherein, the communication interface 110 is configured to receive a single-lead ECG signal and an ultrasonic pulse wave signal of at least one body part.
  • the processor 120 further includes a memory 121.
  • the memory 121 stores computer executable instructions. The processor 120 executes the computer When the instruction is executed, the method for determining the pulse transmission time as described in any of the embodiments of the present disclosure is realized.
  • the single-lead ECG signal and the ultrasonic pulse wave signal received by the communication interface 110 may be signals that have been pre-processed or signals that have not been pre-processed. If these two signals have not been pre-processed, the processing The device 120 needs to first preprocess the single-lead ECG signal and the ultrasound pulse wave signal of the body part received via the communication interface 110, such as removing noise, removing baseline drift, etc., and then extract the preprocessed single-lead ECG signal The characteristic points of R wave information and pulse wave signal.
  • the preprocessing including the extraction of R wave information and pulse wave signal characteristic points can also be performed by the processing units of the single-lead ECG detector and the micro ultrasonic pulse detector. .
  • the computer executable instructions stored in the memory 121 are executed.
  • the R wave information of the single-lead ECG signal and the characteristic points of the pulse wave signal determine the pulse transmission time.
  • the pulse transmission time has a high correlation with the degree of arteriosclerosis. In this way, each body can be qualitatively determined according to the pulse transmission time. The degree of arterial stiffness of the site.
  • the arteriosclerosis detection device 100 provided in the present disclosure can relatively accurately determine the pulse transmission time based on the single-lead ECG signal and the ultrasonic pulse wave signal, and can conveniently and accurately obtain important parameters related to the degree of arteriosclerosis according to the determined pulse transmission time. The accuracy of determining the degree of arteriosclerosis is high.
  • the processor 120 also implements the following steps when executing the computer-executable instructions: based on the pulse transmission time of each body part and the distance between the sensing point of the single-lead ECG signal and the sensing point of the pulse wave signal The distance to determine the pulse transmission speed from the heart to each body part.
  • the processor 120 also implements the following steps when executing the computer-executable instructions: based on the pulse transmission time of each body part and the distance between the sensing point of the single-lead ECG signal and the sensing point of the pulse wave signal The distance to determine the pulse transmission speed from the heart to each body part.
  • the processor 120 also implements the following steps when executing the computer-executable instructions: based on the pulse transmission time of each body part and the distance between the sensing point of the single-lead ECG signal and the sensing point of the pulse wave signal The distance to determine the pulse transmission speed from the heart to each body part.
  • the pulse transmission velocity (baPWV) will increase accordingly, and the pulse transmission velocity ( The faster
  • At least one body part includes limbs, so as to determine the degree of arteriosclerosis of the limbs according to the pulse transmission time of the limbs, and the processor 120 further implements the following steps when executing the computer-executable instructions: according to the pulse transmission time PTT of the limbs Use the following formula to determine the blood pressure BP of the corresponding limbs:
  • ⁇ is a quantity that characterizes blood vessels, and the value range is 0.016-0.018mmHg -1 , S is the distance between the single-lead ECG signal sensing point and the pulse wave signal sensing point, E 0 is the blood vessel
  • the elastic modulus when the wall pressure is zero BP is the blood pressure
  • PTT is the pulse transit time
  • ⁇ is the density of the blood
  • d is the inner diameter of the blood vessel
  • ⁇ is the coefficient related to individual characteristics and can be obtained by fitting the actual measurement data;
  • Determine the ankle-brachial index SBP ankle /SBP upper arm according to the blood pressure of each limb, where the SBP ankle is the systolic pressure of the ankle, and the SBP upper arm is the systolic pressure of the upper arm.
  • real data of various parameters related to blood vessels can be measured by a miniature ultrasonic pulse wave detector, such as the inner diameter d of the blood vessel. Based on these real data, the blood pressure of the limbs is relative to the passing data.
  • the blood pressure obtained by the modeling is more accurate, and the ankle-brachial index obtained is also more accurate.
  • the ankle-brachial index is used to evaluate the degree of arteriosclerosis of the lower extremities.
  • a value of the ankle-brachial index greater than 1.30 indicates arterial stiffness, a value between 1.00 and 1.29 indicates that the artery is normal, and a value between 0.91 and 0.99 indicates that the current artery is in the critical range between normal and hard , Between 0.41-0.90, it means that the user has mild to moderate arterial disease, and between 0.00-0.40, it means that the user has severe peripheral arterial disease.
  • the processor 120 also implements the following steps when executing the computer-executable instructions: based on the blood pressure of the limbs, the pulse transit time of the limbs, the cardiac output per minute CO and the peripheral resistance TPR as parameters related to arteriosclerosis To evaluate the degree of arteriosclerosis, among which,
  • SV is the cardiac output per stroke
  • K is the pulse wave waveform value
  • T is the pulse wave period
  • P s is the systolic blood pressure
  • P d is the diastolic blood pressure
  • P m is the mean arterial pressure (as shown in Figure 6)
  • CO is the cardiac output per minute
  • TPR is the peripheral resistance.
  • the size of K depends on the area of the periodic waveform of the pulse wave, and is a dimensionless value. K will vary greatly under different physiological conditions.
  • the peripheral resistance TPR reflects the patency of the blood vessels, and the cardiac output per minute CO reflects The efficiency of the body's blood circulatory system, combined with pulse wave waveform value K, cardiac output per minute CO and peripheral resistance TPR to comprehensively evaluate the degree of arteriosclerosis, making the evaluation of arterial stiffness more accurate.
  • the degree of arteriosclerosis of the patient may not be significantly reflected in a certain arteriosclerosis-related parameter.
  • the four types of arteriosclerosis are related to the integration of limb blood pressure BP, limb pulse transit time PTT, cardiac output per minute CO, and peripheral resistance TPR. Parameter, can fully and accurately grasp the degree of arteriosclerosis, to avoid missed or wrong detection.
  • the processor 120 also implements the following steps when executing the computer-executable instructions: determining the damage index F of each arteriosclerosis-related parameter to evaluate the degree of arteriosclerosis, and the damage index of each arteriosclerosis-related parameter is calculated using the following formula Calculation:
  • V is the actual value of arteriosclerosis-related parameters
  • RC is the upper limit of the normal range of arteriosclerosis-related parameters
  • RF is the lower limit of the normal range of arteriosclerosis-related parameters.
  • the normal range of cardiac output CO is 4500ml-6000ml, that is, the upper limit RC of the normal range of cardiac output CO per minute is 6000
  • the lower limit RF is 4500
  • F is the damage index of arteriosclerosis related parameters
  • ⁇ and ⁇ It is a constant and is obtained by fitting a data set of clinically measured arteriosclerosis-related parameters and clinically estimated corresponding damage index.
  • processing each arteriosclerosis-related parameter as a damage index it is convenient for the user to quantitatively and intuitively determine the degree of arteriosclerosis.
  • the development of arteriosclerosis can be accurately determined under a unified standard.
  • FIG. 7 is a schematic structural diagram of an arteriosclerosis detection system according to an embodiment of the present disclosure.
  • the present disclosure also provides an arteriosclerosis detection system 200, including the arteriosclerosis detection system according to any embodiment of the present disclosure
  • the detection device 100, the arteriosclerosis detection system 200 further includes a first slave 210 and a second slave 220, wherein the first slave 210 includes an ECG detector 211, configured to sense a single-lead ECG signal of the user
  • the second slave 220 includes a miniature ultrasonic detector 221, which is configured to be worn on at least one body part of the user to detect the ultrasonic pulse wave signal of the body part.
  • the first slave and the second slave further include a communication circuit (not shown in FIG. 7) that communicates with the arteriosclerosis detection device 100 to send the sensed single-lead ECG signal and the ultrasonic pulse wave signal to Arteriosclerosis detection equipment 100.
  • the micro ultrasonic detector 221 by processing the image data obtained by the micro ultrasonic detector 221, not only the pulse wave signal can be detected, but also various parameters related to the blood vessel such as the inner diameter of the arterial blood vessel can be obtained, and the degree of arteriosclerosis can be evaluated based on these real measurement data.
  • the evaluation results obtained are more accurate, and when the micro ultrasonic detector 221 is used to detect the pulse wave signal, it does not need to be tied to the part of the user's body to be detected like the blood pressure measurement module in the existing arteriosclerosis device, which can improve The user's comfort is convenient and fast, and the miniature ultrasonic detector 221 has a small size and is integrated on the arteriosclerosis detection system 200, so that the arteriosclerosis detection system 200 has a smaller volume and lower price.
  • the arteriosclerosis detection system 200 integrates the arteriosclerosis detection device 100 with a single-lead ECG detector and a miniature ultrasonic pulse wave detector, which can conveniently and accurately determine parameters that are important to the degree of arteriosclerosis, including pulse transmission time.
  • the system is small in size, low in price, easy to use, and high in accuracy.
  • the first slave 210 further includes a first microprocessor 212 and a first communication circuit 213, wherein the first microprocessor 212 is configured to detect the sensed single-lead
  • the ECG signal is processed to obtain the R wave information of the single-lead ECG signal.
  • the first microprocessor 212 first preprocesses the single-lead ECG signal, such as removing myoelectric interference, power frequency interference, baseline drift, etc.
  • the first communication circuit 213 is configured to transmit the R wave information of the single-lead ECG signal to the processor 120 of the artery detection device 100;
  • the second slave 220 also includes a second microprocessor 222 and a second communication circuit 223.
  • the second microprocessor 222 is configured to process the detected ultrasonic pulse wave signal and extract the characteristic points of the preprocessed ultrasonic pulse wave signal.
  • the second communication circuit 223 is configured to transmit the data of the characteristic points of the ultrasonic pulse wave signal to the processor 120 of the arterial detection device 100, so that the processor 120 is based on the R wave information of the single-lead ECG signal and the ultrasonic pulse wave signal
  • the characteristic points determine the pulse transit time, and then evaluate the degree of arteriosclerosis.
  • each of the first slave 210 and the second slave 220 includes a timer 230 configured to determine the first time information of the corresponding slave, and the arteriosclerosis detection device 100 passes through The communication interface 110 sends second time information to the first slave and the second slave.
  • Each of the first microprocessor 212 and the second microprocessor 222 is also configured to calculate the first time of the corresponding slave.
  • the first communication circuit 213 and the second communication circuit 223 are each further configured to send their respective time deviation information to the arteriosclerosis detection device 100.
  • the second time information is the current time information of the arteriosclerosis detection device 100
  • the first time information is the current time information of the corresponding slave. According to the time deviation of the two time information, the arteriosclerosis detection device 100 and the The synchronization of each slave.
  • the communication interface 110 of the arteriosclerosis detection device 100 is further configured to receive time deviation information, and the processor 120 performs corresponding time compensation on the signals transmitted by the first slave and the second slave according to the time deviation information, and compensates The manner may be to add a delay operation to the processor 120 to ensure the synchronization of the arteriosclerosis detection device 100 and each slave machine.
  • the micro ultrasonic detector 221 is further configured to sense the blood vessel wall signal and the blood flow signal; the second microprocessor 222 is further configured to obtain at least one of the following parameters based on the blood vessel wall signal and the blood flow signal: Arterial elasticity coefficient, blood vessel wall thickness and blood viscosity. For example, according to parameters such as arterial elastic system, blood vessel wall thickness, blood viscosity, etc., combined with arteriosclerosis degree parameters can better evaluate arteriosclerosis and predict the risk of arteriosclerosis.
  • the number of the second slaves 220 is at least four, and they are respectively configured to obtain the ultrasonic pulse wave signals of the extremities, so as to determine the degree of arteriosclerosis of the extremities according to the pulse transmission time of the extremities, and improve the prediction of arteriosclerosis.
  • the accuracy of the risk of sclerosis disease is at least four, and they are respectively configured to obtain the ultrasonic pulse wave signals of the extremities, so as to determine the degree of arteriosclerosis of the extremities according to the pulse transmission time of the extremities, and improve the prediction of arteriosclerosis.
  • the arteriosclerosis detection system 200 further includes a power source 240 configured to supply power to the arteriosclerosis detection system 200.
  • the arteriosclerosis detection system 200 further includes a display 250 configured to display evaluation information of the degree of arteriosclerosis, and the display 250 may display the degree of arteriosclerosis in various forms such as curves and tables. In order to clearly and concisely display the evaluation information of the degree of arteriosclerosis to users.
  • step S201 the single-lead ECG signal collected by the ECG detector 211 and the pulse wave signal of the limbs detected by the micro ultrasonic detector 221 are obtained.
  • step S202 extract the R-wave information of the single-lead ECG signal and the characteristic points of the pulse wave signal of the limbs
  • step S203 calculate according to the R-wave information of the single-lead ECG signal and the characteristic points of the pulse wave signal of the limbs Pulse transit time, cardiac output per minute, peripheral resistance, and ankle-brachial index
  • step S204 the damage index of the parameter index calculated in step S203 is calculated, and combined with the arterial elasticity coefficient obtained from the micro ultrasonic detector 221,
  • the thickness of the blood vessel wall and the viscosity of the blood complete the assessment of the degree of arteriosclerosis and predict the risk of suffering from arteriosclerosis.

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Abstract

一种确定脉搏传输时间的方法、动脉硬化检测设备及系统，该方法包括：接收单导心电信号；接收至少一个身体部位的脉搏波信号，脉搏波信号经由设置在相应身体部位处的微型超声模块检测得到；以单导心电信号的R波为起点并且以至少一个身体部位的脉搏波信号的特征点为终点，来确定脉搏传输时间。该方法及相应的动脉硬化检测设备及系统基于单导心电信号和超声脉搏波信号较为准确的确定脉搏传输时间，动脉硬化检测系统能够方便准确地确定包括脉搏传输时间等对动脉硬化程度重要的参数，以便进一步确定动脉硬化程度。相应的动脉硬化检测系统的体积小，价格较低，使用便捷，且准确度较高。

Description

确定脉搏传输时间的方法、动脉硬化检测设备及系统
交叉引用
本公开要求于2019年3月11日提交的中国专利申请第201910181877.8号的优先权，其全部内容通过引用合并于此。
技术领域
本公开涉及一种确定脉搏波传输时间的方法、动脉硬化检测设备及系统。
背景技术
我国心脑血管病患病率及死亡率仍处于上升阶段，心血管病死亡占居民疾病死亡构成的40％以上，位居首位，远高于肿瘤及其他疾病。动脉硬化检测设备是进行心血管疾病风险筛查的重要手段，
目前，动脉硬化检测方法主要通过血压和心电信号来判断动脉硬化程度，准确度不够高，而现有的动脉硬化检测设备主要由四肢血压测量模块、心电检测器、心音模块等模块组成，同时，大部分提供选配的多普勒超声用来进行颈股动脉传输速度测量，导致整体设备的体积大、价格昂贵，且操作较为繁琐，不适宜在基层医疗、体检机构进行推广。
发明内容
根据本公开的第一方面，提供了一种确定脉搏传输时间的方法，所述方法包括：接收单导心电信号；接收至少一个身体部位的脉搏波信号，所述脉搏波信号经由设置在相应身体部位处的微型超声检测器检测得到；以单导心电信号的R波为起点并且以至少一个身体部位的脉搏波信号的特征点为终点，来确定脉搏传输时间。
在一些实施例中，所述脉搏波信号的特征点包括脉搏波的波谷、以波谷为基点的斜率上升的最大点以及波峰中的至少一个。
在一些实施例中，所述至少一个身体部位包括四肢。
根据本公开的第二方面，提供了一种动脉硬化检测设备，包括：通信接口，被配置为接收单导心电信号和至少一个身体部位的超声脉搏波信号；处理器，包括存储器，其上存储有计算机可执行指令，所述处理器执行所述计算机可执行指令时，实现如本公开的第一方面中任一实施例所述的确定脉搏传输时间的方法。
在一些实施例中，所述处理器执行所述计算机可执行指令时还实现如下步骤：基于各个身体部位的脉搏传输时间和所述单导心电信号的感测点与所述脉搏波信号的感测点之间的距离，确定心脏至各个身体部位的脉搏传输速度。
在一些实施例中，所述至少一个身体部位包括四肢，所述处理器执行所述计算机可执行指令时还实现如下步骤：根据四肢的脉搏传输时间PTT和如下公式确定相应四肢部位的血压BP：
Figure PCTCN2020077513-appb-000001
其中，γ为表征血管特征的一个量，且数值范围为0.016-0.018mmHg -1，S为所述单导心电信号的感测点与所述脉搏波信号的感测点之间的距离，E 0为血管壁的压力为零时的弹性模量，BP为血压，PTT为脉搏传输时间，ρ表示血液的密度，d表示血管内径，a为与个体特性相关的系数且能够通过实际测量数据拟合得到；
根据各个四肢部位的血压确定踝臂指数＝SBP 踝部/SBP 上臂，其中，SBP 踝部为踝部的收缩压，SBP 上臂为上臂的收缩压。
在一些实施例中，所述处理器执行所述计算机可执行指令时还实现如下步骤：基于四肢部位的血压BP、四肢的脉搏传输时间PTT、每分钟的心输出量CO和外周阻力TPR作为动脉硬化相关参数来评价动脉硬化程度，其中，
SV＝0.283/K 2×T×(P s-P d)，
Figure PCTCN2020077513-appb-000002
TPR＝P m/CO，
CO＝SV×60/T，
K＝(P m-P d)/(P s-P d)，
其中，SV为每搏的心输出量，K为脉搏波波形值，T为脉搏波周期，P s为收缩压，P d为舒张压，P m为平均动脉压，CO为每分钟的心输出量，TPR为外周阻力。
在一些实施例中，所述处理器执行所述计算机可执行指令时还实现如下步骤：确定各个动脉硬化相关参数的损害指数，以评价动脉硬化程度，各个动脉硬化相关参数的损害指数F利用如下公式来计算：
Figure PCTCN2020077513-appb-000003
其中，V为动脉硬化相关参数的实际值，RC为动脉硬化相关参数的正常范围的上限，RF为动脉硬化相关参数的正常范围的下限，F为动脉硬化相关参数的损害指数，α和β是常数且根据临床测得的动脉硬化相关参数与临床估测的相应损害指数的数据集拟合得到。
根据本公开的第三方面，提供了一种动脉硬化检测系统，包括如本公开的第二方面中任一实施例所述的动脉硬化检测设备，所述系统还包括：第一从机，包括心电检测器，被配置为感测用户的单导心电信号；第二从机，包括微型超声检测器，被配置为佩戴在所述用户的至少一个身体部位以检测其超声脉搏波信号。
在一些实施例中，所述第一从机还包括：第一微处理器，被配置为对所述单导心电信号进行处理，以得到所述单导心电信号的R波信息；第一通信电路，被配置为传输所述单导心电信号的R波信息；所述第二从机还包括：第二微处理器，被配置为对所述超声脉搏波信号进行处理，以得到所述超声脉搏波信号的特征点；第二通信电路，被配置为传输所述超声脉搏波信号的特征点。
在一些实施例中，所述第一从机和第二从机中的每个包括配置为确定相应从机的第一时间信息的计时器，所述动脉硬化检测设备经由所述通信接口向第一从机和第二从机发送第二时间信息，所述第一微处理器和第二微处理器中的每个微处理器还配置为计算相应从机的第一时间信息与所述第二时间信息之间的时间偏差情况，所述第一通信电路和所述第二通信电路各自进一步配置为将各自的时间偏差信息发送给所述动脉硬化检测设备。
在一些实施例中，所述动脉硬化检测设备的通信接口还被配置为接收所述时间偏差信息；所述动脉硬化检测设备的处理器进一步配置为：根据所述时间偏差信息对第一从机和第二从机传输的信号进行相应的时间补偿。
在一些实施例中，所述微型超声检测器进一步被配置为感测血管壁信号和血流信号；所述第二微处理器进一步被配置为基于所述血管壁信号和所述血流信号至少获取以下参数之一：动脉弹性系数、血管壁厚度以及血液粘稠度。
在一些实施例中，所述第二从机的数量至少为四个，分别被配置为获取四肢的超声脉搏波信号。
在一些实施例中，所述动脉硬化检测系统还包括：电源，被配置为向所述动脉硬化检测系统供电。
在一些实施例中，所述动脉硬化检测系统还包括：显示器，被配置为显示动脉硬化程度的评价信息。
应当理解，前面的一般描述和以下详细描述都仅是示例性和说明性的，而不是用于限制本公开。
本节提供本公开中描述的技术的各种实现或示例的概述，并不是所公开技术的全部范围或所有特征的全面公开。
附图说明
为了更清楚地说明本公开实施例的技术方案，下面将对实施例的附图作简单地介绍，显而易见地，下面描述中的附图仅仅涉及本公开的一些实施例，而非对本公开的限制。
图1为根据本公开实施例的确定脉搏传输时间的方法的流程图；
图2为根据本公开实施例的作为基准的心电信号的R波间期和利用脉搏波信号的特征点计算的脉搏传输时间的示意图；
图3为血管良好和血管硬化两种情况下脉搏波传输的对比图；
图4为根据本公开实施例的动脉硬化检测设备的结构示意图；
图5为脉搏传输时间与脉搏传输速度和血管硬化程度的关系示意图；
图6为脉搏波的周期波形图；
图7为根据本公开实施例的动脉硬化检测系统的结构示意图；
图8为根据本公开实施例的动脉硬化检测系统的结构示意图；
图9为根据本公开实施例的动脉硬化检测系统的工作流程图。
具体实施方式
为了使得本公开实施例的目的、技术方案和优点更加清楚，下面将结合本公开实施例的附图，对本公开实施例的技术方案进行清楚、完整地描述。显然，所描述的实施例是本公开的一部分实施例，而不是全部的实施例。基于所描述的本公开的实施例，本领域普通技术人员在无需创造性劳动的前提下所获得的所有其他实施例，都属于本公开保护的范围。
除非另外定义，本公开使用的技术术语或者科学术语应当为本公开所属领域内具有一般技能的人士所理解的通常意义。“包括”或者“包含”等类似的词语意指出现该词前面的元件或者物件涵盖出现在该词后面列举的元件或者物件及其等同，而不排除其他元件或者物件。“连接”或者“相连”等类似的词语并非限定于物理的或者机械的连接，而是可以包括电性的连接，不管是直接的还是间接的。“上”、“下”、“左”、“右”等仅用于表示相对位置关系，当被描述对象的绝对位置改变后，则该相对位置关系也可能相应地改变。
为了保持本公开实施例的以下说明清楚且简明，本公开省略了已知功能和已知部件的详细说明。
针对现有技术中存在的上述技术问题，本公开提供了一种确定脉搏波传输时间的方法、动脉硬化检测设备及系统，能够基于单导心电信号和超声脉搏波信号较为准确的确定脉搏传输时间，动脉硬化检测设备能够与单导心电检测器和微型超声脉搏波检测模块整合以得到动脉硬化检测系统，其能够方便准确地确定包括脉搏传输时间等对动脉硬化程度重要的 参数，以便进一步确定动脉硬化程度，该设备的体积小，价格较低，使用便捷，且准确度较高。
与现有技术相比，本公开的有益效果在于：
本公开所提供的确定脉搏波传输时间的方法、动脉硬化检测设备及系统，能够基于单导心电信号和超声脉搏波信号较为准确的确定脉搏传输时间，动脉硬化检测设备能够与单导心电检测器和微型超声脉搏波检测模块整合以得到动脉硬化检测系统，其能够方便准确地确定包括脉搏传输时间等对动脉硬化程度重要的参数，以便进一步确定动脉硬化程度，该系统的体积小，价格较低，使用便捷，且准确度较高。
图1为根据本公开实施例的确定脉搏传输时间的方法的流程图，如图1所示，本公开提供了一种确定脉搏传输时间的方法，所述方法包括步骤S101至S103：
在步骤S101，接收单导心电信号。在一些实施例中，单导心电信号可以为肢体导联、胸导联等任一导联的心电信号，在此不做具体限定。不同于多导联心电信号，一些便携式心电检测装置(例如包括心电检测功能的智能腕表)就包含单导心电检测器或具有单导心电信号采集功能，因此可以从广泛的各种便携式心电检测装置接收单导心电信号。
在步骤S102，接收至少一个身体部位的脉搏波信号，该脉搏波信号经由设置在相应身体部位处的微型超声检测器检测得到，相应身体部位例如为用户的腕部、颈部、踝部等。微型超声检测器例如可以采用小型化的微型超声传感器经由多普勒超声准确地捕捉局部测量部位的动脉搏动情况，相比其他脉搏波信号检测装置，尺寸小，且在时域上的定位更准确。并且，微型超声传感器可以灵活加载于身体末端部位，比如四肢等，如此确保脉搏波信号的感测位置与心电信号的感测位置之间的充足距离，有利于降低信号处理的误差对脉搏传输时间的扰动，进而能够降低脉搏传输时间的计算误差。
在步骤S103，以单导心电信号的R波为起点并且以至少一个身体部位的脉搏波信号的特征点为终点，来确定脉搏传输时间。例如，在接收到单导心电信号和脉搏波信号后，首先对这两种信号做预处理，如滤除噪声、去除基线漂移等，然后提取该单导心电信号的R波信息以及脉搏波信号的特征点，提取心电信号的R波信息和脉搏波信号的特征点的方法包括多种，在此不做具体限定。
本公开所提供的确定脉搏波传输时间的方法以单导心电信号的R波作为起点和利用微型超声检测器检测得到的身体部位的脉搏波信号的特征点作为终点，从心脏泵血起始点开始计时，能够更准确的确定脉搏传输时间。此外，该方法利用对于用户佩戴和使用更友好的单导心电检测器和微型超声检测器所分别采集的信号，因此能够在改善用户体验的同时，准确地检测对于动脉硬化程度具重要意义的脉搏传输时间。
在一些实施例中，脉搏波信号的特征点包括脉搏波的波谷、以波谷为基点的斜率上升的最大点以及波峰中的至少一个。示出了作为基准的心电信号的R波间期(标识为RR)， 以及分别利用脉搏波的波谷、以波谷为基点的斜率上升的最大点以及波峰作为特征点所计算的脉搏传输时间(分别标识为PTT1、PTT2和PTT3)。
示例性地，采用脉搏波的波峰作为终点来计算脉搏传输时间。发明人基于这三种特征点进行了大量临床试验，结果发现，采用脉搏波的波峰作为终点所计算得到的脉搏传输时间，能够推导得出(推导方式在下文中会进行详细描述，在此不赘述)更准确的相应身体部位的血压值，且与动脉硬化的相关性最高。
在一些实施例中，至少一个身体部位包括四肢，以便于根据四肢的脉搏传输时间分析用户的四肢的血管情况，并且四肢距离心脏较远，有利于降低信号处理的误差对脉搏传输时间的扰动，进而能够降低脉搏传输时间的计算误差。
例如，脉搏传输时间在一定程度上反应了血管硬化程度。如图3所示，健康者的血管弹性较好，脉搏传输时间相对较长，动脉血管出现硬化等情况，脉搏传输时间较短。
图4为根据本公开实施例的动脉硬化检测设备的结构示意图，如图4所示，本公开提供了一种动脉硬化检测设备100，该动脉硬化检测设备100包括通信接口110和处理器120，其中，通信接口110被配置为接收单导心电信号和至少一个身体部位的超声脉搏波信号，处理器120还包括存储器121，存储器121上存储有计算机可执行指令，处理器120执行该计算机可执行指令时，实现如本公开中任一项实施例所述的确定脉搏传输时间的方法。可选的，通信接口110接收到的单导心电信号和超声脉搏波信号可以为已经经过预处理的信号，也可以为未经过预处理的信号，如果这两种信号未经过预处理，处理器120需要首先对经由通信接口110接收到的单导心电信号和身体部位的超声脉搏波信号进行预处理，例如去除噪声、去除基线漂移等，然后提取预处理后的单导心电信号的R波信息和脉搏波信号的特征点，当然，包括R波信息和脉搏波信号特征点的提取的预处理也可以分别利用单导心电检测器和微型超声脉搏检测器自身的处理单元来执行。
例如，预处理的方法和提取单导心电信号的R波信息以及脉搏波信号的特征点的方法有多种，在此不做具体限定，之后执行存储器121上存储的计算机可执行指令，根据单导心电信号的R波信息和脉搏波信号的特征点确定脉搏传输时间，其中，脉搏传输时间与动脉硬化程度具有较高的相关性，如此，可以根据该脉搏传输时间定性地确定各身体部位的动脉硬化程度。
本公开所提供动脉硬化检测设备100能够基于单导心电信号和超声脉搏波信号较为准确的确定脉搏传输时间，并能够方便准确地根据确定的脉搏传输时间得到与动脉硬化程度相关的重要参数，确定动脉硬化程度的准确度较高。
在一些实施例中，处理器120执行所述计算机可执行指令时还实现如下步骤：基于各个身体部位的脉搏传输时间和单导心电信号的感测点与脉搏波信号的感测点之间的距离，确定心脏至各个身体部位的脉搏传输速度。例如，根据图5可以得出，动脉血管壁的弹性 越好，脉搏传输速度(baPWV)相对较慢，在动脉血管壁出现硬化时，脉搏传输速度(baPWV)会相应加快，且脉搏传输速度(baPWV)越快，表明动脉血管壁的硬化程度越高。
在一些实施例中，至少一个身体部位包括四肢，以便根据四肢的脉搏传输时间确定四肢的动脉硬化程度，处理器120执行所述计算机可执行指令时还实现如下步骤：根据四肢的脉搏传输时间PTT和如下公式确定相应四肢部位的血压BP：
Figure PCTCN2020077513-appb-000004
其中，γ为表征血管特征的一个量，且数值范围为0.016-0.018mmHg -1，S为单导心电信号的感测点与脉搏波信号的感测点之间的距离，E 0为血管壁的压力为零时的弹性模量，BP为血压，PTT为脉搏传输时间，ρ表示血液的密度，d表示血管内径，α为与个体特性相关的系数且能够通过实际测量数据拟合得到；根据各个四肢部位的血压确定踝臂指数＝SBP 踝部/SBP 上臂，其中，SBP 踝部为踝部的收缩压，SBP 上臂为上臂的收缩压。例如，在本公开的实施例中，可以通过微型超声脉搏波检测器测量得到与血管相关的多种参数的真实数据，如血管内径d，基于这些真实数据得到的四肢部位的血压相对于通过数据建模得到的血压更为准确，进而得到的踝臂指数也更为准确。例如，踝臂指数用于评价下肢动脉硬化程度，踝臂指数的数值大于1.30表征动脉僵硬，在1.00-1.29之间表征动脉正常，在0.91-0.99之间表征当前动脉处于正常和硬化的临界范围，在0.41-0.90之间表征用户具有轻到中度的动脉疾病，在0.00-0.40之间表征用户具有严重外周动脉疾病。
在一些实施例中，处理器120执行所述计算机可执行指令时还实现如下步骤：基于四肢部位的血压、四肢的脉搏传输时间、每分钟的心输出量CO和外周阻力TPR作为动脉硬化相关参数来评价动脉硬化程度，其中，
SV＝0.283/K 2×T×(P s-P d)，
Figure PCTCN2020077513-appb-000005
TPR＝P m/CO，
CO＝SV×60/T，
K＝(P m-P d)/(P s-P d)，
其中，SV为每搏的心输出量，K为脉搏波波形值，T为脉搏波周期，P s为收缩压，P d为舒张压，P m为平均动脉压(如图6所示)，CO为每分钟的心输出量，TPR为外周阻力。
例如，K的大小取决于脉搏波的周期波形图面积，是一个无量纲的值，不同生理状态下K会有很大变化，外周阻力TPR反映血管的通畅程度，每分钟的心输出量CO反映身体的血液循环系统的效率，结合脉搏波波形值K、每分钟的心输出量CO和外周阻力TPR来综合评价动脉硬化程度，使得动脉硬化程度的评价更准确。有时，患者的动脉硬化程度在某个 动脉硬化相关参数上可能没有显著体现，整合四肢的血压BP、四肢的脉搏传输时间PTT、每分钟的心输出量CO和外周阻力TPR这四种动脉硬化相关参数，能够全面准确地把握动脉硬化程度，以避免漏检或错检。
在一些实施例中，处理器120执行所述计算机可执行指令时还实现如下步骤：确定各个动脉硬化相关参数的损害指数F以评价动脉硬化程度，各个动脉硬化相关参数的损害指数利用如下公式来计算：
Figure PCTCN2020077513-appb-000006
其中，V为动脉硬化相关参数的实际值，RC为动脉硬化相关参数的正常范围的上限，RF为动脉硬化相关参数的正常范围的下限，例如，在心率平均为每分钟75次时，每分钟的心输出量CO的正常范围为4500ml-6000ml，即，每分钟的心输出量CO的正常范围的上限RC为6000，其下限RF为4500，F为动脉硬化相关参数的损害指数，α和β是常数且根据临床测得的动脉硬化相关参数与临床估测的相应损害指数的数据集拟合得到。
发明人通过临床对比试验发现，由上述F的定义所计算得到的各个动脉硬化相关参数的损害指数与患者实际的动脉硬化程度吻合度较高，且F的数值越大，表示患有动脉硬化疾病的风险越高。通过将各个动脉硬化相关参数处理为损害指数，便于用户定量且直观地确定动脉硬化程度。此外，通过对同一用户的各个动脉硬化相关参数的损害指数的持续跟踪，能够在统一标准下准确地确定动脉硬化病情的发展情况。
图7为根据本公开实施例的动脉硬化检测系统的结构示意图，如图7所示，本公开还提供了一种动脉硬化检测系统200，包括如本公开中任一实施例所述的动脉硬化检测设备100，该动脉硬化检测系统200还包括第一从机210和第二从机220，其中，第一从机210包括心电检测器211，被配置为感测用户的单导心电信号，第二从机220包括微型超声检测器221，被配置为佩戴在用户的至少一个身体部位以检测该身体部位的超声脉搏波信号。例如，第一从机和第二从机还包括与动脉硬化检测设备100通信的通信电路(图7中未示出)，以将感测到的单导心电信号和超声脉搏波信号发送给动脉硬化检测设备100。
例如，对微型超声检测器221获取到的图像数据进行处理，不仅能够检测到脉搏波信号，还可以获得动脉血管的内径等与血管相关的多种参数，基于这些真实测量数据评价动脉硬化程度，得到的评价结果的准确度更高，并且，采用微型超声检测器221检测脉搏波信号时不需要如现有的动脉硬化装置中的血压测量模块那样束缚于用户身体的待检测部位上，能够提升用户的舒适度，方便快捷，且微型超声检测器221的尺寸较小，集成于动脉硬化检测系统200上，使得动脉硬化检测系统200的体积较小，价格也较低。
本公开所提供的动脉硬化检测系统200将动脉硬化检测设备100与单导心电检测器和微型超声脉搏波检测器进行整合，能够方便准确地确定包括脉搏传输时间等对动脉硬化程度重要的参数，以便进一步确定动脉硬化程度，该系统的体积小，价格较低，使用便捷，且准确度较高。
在一些实施例中，如图8所示，第一从机210还包括第一微处理器212和第一通信电路213，其中，第一微处理器212被配置为对感测到的单导心电信号进行处理，以得到单导心电信号的R波信息，例如，第一微处理器212首先对单导心电信号进行预处理，例如去除肌电干扰、工频干扰、基线漂移等，然后提取预处理后的单导心电信号的R波信息，第一通信电路213被配置为将单导心电信号的R波信息传输给动脉检测设备100的处理器120；第二从机220还包括第二微处理器222和第二通信电路223，第二微处理器222被配置为对检测到的超声脉搏波信号进行处理，提取经过预处理后的超声脉搏波信号的的特征点，第二通信电路223被配置为将超声脉搏波信号的特征点的数据传输给动脉检测设备100的处理器120，以使处理器120根据单导心电信号的R波信息和超声脉搏波信号的特征点确定脉搏传输时间，进而评价动脉硬化程度。
在一些实施例中，如图8所示，第一从机210和第二从机220中的每个包括配置为确定相应从机的第一时间信息的计时器230，动脉硬化检测设备100经由通信接口110向第一从机和第二从机发送第二时间信息，第一微处理器212和第二微处理器222中的每个微处理器还配置为计算相应从机的第一时间信息与第二时间信息之间的时间偏差情况，第一通信电路213和第二通信电路223各自进一步配置为将各自的时间偏差信息发送给动脉硬化检测设备100。具体说来，第二时间信息为动脉硬化检测设备100的当前时间信息，第一时间信息为相应从机的当前时间信息，根据这两个时间信息的时间偏差情况可以得到动脉硬化检测设备100与各从机的同步情况。
在一些实施例中，动脉硬化检测设备100的通信接口110还被配置为接收时间偏差信息，处理器120根据时间偏差信息对第一从机和第二从机传输的信号进行相应时间补偿，补偿方式可以为向处理器120中添加延时操作，以保证动脉硬化检测设备100和各个从机工作的同步性。
在一些实施例中，微型超声检测器221进一步被配置为感测血管壁信号和血流信号；第二微处理器222进一步被配置为基于血管壁信号和血流信号至少获取以下参数之一：动脉弹性系数、血管壁厚度以及血液粘稠度。例如，根据动脉弹性系统、血管壁厚度、血液粘稠度等参数结合动脉硬化程度参数能够更好的评价动脉硬化情况以及预测患有动脉硬化疾病的风险。
在一些实施例中，第二从机220的数量至少为四个，分别被配置为获取四肢的超声脉搏波信号，以便于根据四肢的脉搏传输时间确定四肢的动脉硬化程度，提高预测患有动脉硬化疾病的风险的准确性。
在一些实施例中，如图8所示，动脉硬化检测系统200还包括电源240，电源240被配置为向动脉硬化检测系统200供电。
在一些实施例中，如图8所示，动脉硬化检测系统200还包括显示器250，显示器250被配置为显示动脉硬化程度的评价信息，显示器250可以通过曲线、表格等多种形式显示动脉硬化程度的评价信息，以便于清楚、简洁的将动脉硬化程度的评价信息展示给用户。
例如，动脉硬化检测系统200的工作流程如图9所示，首先，在步骤S201，获取心电检测器211采集到的单导心电信号和微型超声检测器221检测到的四肢的脉搏波信号；然后在步骤S202，提取单导心电信号的R波信息和四肢的脉搏波信号的特征点；在步骤S203，根据单导心电信号的R波信息和四肢的脉搏波信号的特征点计算脉搏传输时间、每分钟的心输出量、外周阻力和踝臂指数；最后在步骤S204，计算步骤S203中算出的参数指标的损害指数，并结合根据微型超声检测器221获取到的动脉弹性系数、血管壁厚度以及血液粘稠度完成动脉硬化程度评价，并预测患有动脉硬化疾病的风险。
以上描述旨在是说明性的而不是限制性的。例如，上述示例(或其一个或更多方案)可以彼此组合使用。例如本领域普通技术人员在阅读上述描述时可以使用其它实施例。另外，在上述具体实施方式中，各种特征可以被分组在一起以简单化本公开。这不应解释为一种不要求保护的公开的特征对于任一权利要求是必要的意图。相反，本公开的主题可以少于特定的公开的实施例的全部特征。从而，以下权利要求书作为示例或实施例在此并入具体实施方式中，其中每个权利要求独立地作为单独的实施例，并且考虑这些实施例可以以各种组合或排列彼此组合。本公开的范围应参照所附权利要求以及这些权利要求赋权的等同形式的全部范围来确定。
以上实施例仅为本公开的示例性实施例，不用于限制本公开，本公开的保护范围由权利要求书限定。本领域技术人员可以在本公开的实质和保护范围内，对本公开做出各种修改或等同替换，这种修改或等同替换也应视为落在本公开的保护范围内。

Claims (16)

  1. 一种确定脉搏传输时间的方法，包括：
    接收单导心电信号；
    接收至少一个身体部位的脉搏波信号，所述脉搏波信号经由设置在相应身体部位处的微型超声检测器检测得到；以及
    以单导心电信号的R波为起点并且以至少一个身体部位的脉搏波信号的特征点为终点，来确定脉搏传输时间。
  2. 根据权利要求1所述的确定脉搏传输时间的方法，其中，所述脉搏波信号的特征点包括脉搏波的波谷、以波谷为基点的斜率上升的最大点以及波峰中的至少一个。
  3. 根据权利要求2所述的确定脉搏传输时间的方法，其中，所述至少一个身体部位包括四肢。
  4. 一种动脉硬化检测设备，包括：
    通信接口，被配置为接收单导心电信号和至少一个身体部位的超声脉搏波信号；
    处理器，包括存储器，其上存储有计算机可执行指令，所述处理器执行所述计算机可执行指令时，实现如权利要求1-3中任一项所述的确定脉搏传输时间的方法。
  5. 根据权利要求4所述的动脉硬化检测设备，其中，所述处理器执行所述计算机可执行指令时还实现如下步骤：
    基于各个身体部位的脉搏传输时间和所述单导心电信号的感测点与所述脉搏波信号的感测点之间的距离，确定心脏至各个身体部位的脉搏传输速度。
  6. 根据权利要求5所述的动脉硬化检测设备，其中，所述至少一个身体部位包括四肢，所述处理器执行所述计算机可执行指令时还实现如下步骤：
    根据四肢的脉搏传输时间PTT和如下公式确定相应四肢部位的血压BP：
    Figure PCTCN2020077513-appb-100001
    其中，γ为表征血管特征的一个量，且数值范围为0.016-0.018mmHg -1，S为所述单导心电信号的感测点与所述脉搏波信号的感测点之间的距离，E 0为血管壁的压力为零时的弹性模量，BP为血压，PTT为脉搏传输时间，ρ表示血液的密度，d表示血管内径，a为与个体特性相关的系数且能够通过实际测量数据拟合得到；
    根据各个四肢部位的血压确定踝臂指数＝SBP 踝部/SBP 上臂，其中，SBP 踝部为踝部的收缩压，SBP 上臂为上臂的收缩压。
  7. 根据权利要求6所述的动脉硬化检测设备，其中，所述处理器执行所述计算机可执行指令时还实现如下步骤：基于四肢部位的血压BP、四肢的脉搏传输时间PTT、每分钟的心输出量CO和外周阻力TPR作为动脉硬化相关参数来评价动脉硬化程度，其中，
    SV＝0.283/K 2×T×（P s-P d)，
    Figure PCTCN2020077513-appb-100002
    TPR＝Ｐ "/CO，
    CO＝SV×60/T，
    K＝(P "-P d)/(P s-P d)，
    其中，SV为每搏的心输出量，K为脉搏波波形值，T为脉搏波周期，P s为收缩压，P d为舒张压，P "为平均动脉压，CO为每分钟的心输出量，TPR为外周阻力。
  8. 根据权利要求7所述的动脉硬化检测设备，其中，所述处理器执行所述计算机可执行指令时还实现如下步骤：确定各个动脉硬化相关参数的损害指数以评价动脉硬化程度，各个动脉硬化相关参数的损害指数F利用如下公式来计算：
    Figure PCTCN2020077513-appb-100003
    其中，V为动脉硬化相关参数的实际值，RC为动脉硬化相关参数的正常范围的上限，RF为动脉硬化相关参数的正常范围的下限，F为动脉硬化相关参数的损害指数，α和β是常数且根据临床测得的动脉硬化相关参数与临床估测的相应损害指数的数据集拟合得到。
  9. 一种动脉硬化检测系统，包括如权利要求8所述的动脉硬化检测设备，所述系统还包括：第一从机，包括心电检测器，被配置为感测用户的单导心电信号；第二从机，包括微型超声检测器，被配置为佩戴在所述用户的至少一个身体部位以检测其超声脉搏波信号。
  10. 根据权利要求9所述的动脉硬化检测系统，其中，所述第一从机还包括：第一微处理器，被配置为对所述单导心电信号进行处理，以得到所述单导心电信号的R波信息；第一通信电路，被配置为传输所述单导心电信号的R波信息；所述第二从机还包括：第二微处理器，被配置为对所述超声脉搏波信号进行处理，以得到所述超声脉搏波信号的特征点；第二通信电路，被配置为传输所述超声脉搏波信号的特征点。
  11. 根据权利要求10所述的动脉硬化检测系统，其中，所述第一从机和第二从机中的每个包括配置为确定相应从机的第一时间信息的计时器，所述动脉硬化检测设备经由所述通信接口向第一从机和第二从机发送第二时间信息，所述第一微处理器和第二微处理器 中的每个微处理器还配置为计算相应从机的第一时间信息与所述第二时间信息之间的时间偏差情况，所述第一通信电路和所述第二通信电路各自进一步配置为将各自的时间偏差信息发送给所述动脉硬化检测设备。
  12. 根据权利要求11所述的动脉硬化检测系统，其中，所述动脉硬化检测设备的通信接口还被配置为接收所述时间偏差信息；
    所述动脉硬化检测设备的处理器进一步配置为：根据所述时间偏差信息对第一从机和第二从机传输的信号进行相应的时间补偿。
  13. 根据权利要求10所述的动脉硬化检测系统，其中，所述微型超声检测器进一步被配置为感测血管壁信号和血流信号；所述第二微处理器进一步被配置为基于所述血管壁信号和所述血流信号至少获取以下参数之一：动脉弹性系数、血管壁厚度以及血液粘稠度。
  14. 根据权利要求10所述的动脉硬化检测系统，其中，所述第二从机的数量至少为四个，分别被配置为获取四肢的超声脉搏波信号。
  15. 根据权利要求9所述的动脉硬化检测系统，其中，所述动脉硬化检测系统还包括：电源，被配置为向所述动脉硬化检测系统供电。
  16. 根据权利要求9所述的动脉硬化检测系统，其中，所述动脉硬化检测系统还包括：显示器，被配置为显示动脉硬化程度的评价信息。
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CN110652318B (zh) * 2019-07-19 2022-09-13 飞依诺科技股份有限公司 基于超声设备获得动脉硬化指标的测量方法及系统
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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140187941A1 (en) * 2010-01-31 2014-07-03 Vladimir Shusterman Evaluating arterial pressure, vasomotor activity and their response to diagnostic tests
CN105310724A (zh) * 2015-09-28 2016-02-10 何宗彦 一种测量脉搏波传播速度的方法及系统
US20170238909A1 (en) * 2016-02-22 2017-08-24 Jae Yul Shin Method and apparatus for video interpretation of carotid intima-media thickness
CN108175387A (zh) * 2017-12-19 2018-06-19 桂林电子科技大学 一种基于心电和脉搏波形态学参数的血管外周阻力检测装置及检测方法
CN109069031A (zh) * 2016-10-20 2018-12-21 京东方科技集团股份有限公司 用于确定对象血压的设备和方法
CN109730723A (zh) * 2019-03-11 2019-05-10 京东方科技集团股份有限公司 确定脉搏传输时间的方法、动脉硬化检测设备及系统

Family Cites Families (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2003010317A (ja) * 2001-07-02 2003-01-14 Nippon Colin Co Ltd 透析装置
US6964640B2 (en) * 2002-01-22 2005-11-15 P M G Medica L I D System and method for detection of motion
US20080015451A1 (en) * 2006-07-13 2008-01-17 Hatib Feras S Method and Apparatus for Continuous Assessment of a Cardiovascular Parameter Using the Arterial Pulse Pressure Propagation Time and Waveform
CN101067833A (zh) * 2007-05-09 2007-11-07 冯连元 将临床医学上各种检测或化验结果的正常范围参考值及其实际测量值统一标化的方法
CN201088579Y (zh) * 2007-08-06 2008-07-23 北京麦邦光电仪器有限公司 一种动脉硬化检测和评估装置
WO2009081331A1 (en) * 2007-12-19 2009-07-02 Koninklijke Philips Electronics N.V. Apparatus, method and computer program for measuring properties of an object
CN104952000A (zh) * 2015-07-01 2015-09-30 华侨大学 基于马尔科夫链的风电机组运行状态模糊综合评价方法
CN105160181B (zh) * 2015-09-02 2018-02-23 华中科技大学 一种数控系统指令域序列异常数据检测方法
US11589758B2 (en) * 2016-01-25 2023-02-28 Fitbit, Inc. Calibration of pulse-transit-time to blood pressure model using multiple physiological sensors and various methods for blood pressure variation
CN107391083A (zh) * 2017-06-16 2017-11-24 桂林电子科技大学 一种空间异常信息的复数变换隐藏及复原方法
CN107961001A (zh) * 2017-12-20 2018-04-27 中国科学院深圳先进技术研究院 动脉硬化程度的评估方法、装置及动脉硬化检测仪
CN109222941A (zh) * 2018-11-09 2019-01-18 中科数字健康科学研究院（南京）有限公司 一种脉搏波传播时间的测量方法和测量设备
CN109431475A (zh) * 2018-12-19 2019-03-08 海南和家健康科技有限公司 评价外周动脉血管硬化情况的健康腕表及其使用方法

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140187941A1 (en) * 2010-01-31 2014-07-03 Vladimir Shusterman Evaluating arterial pressure, vasomotor activity and their response to diagnostic tests
CN105310724A (zh) * 2015-09-28 2016-02-10 何宗彦 一种测量脉搏波传播速度的方法及系统
US20170238909A1 (en) * 2016-02-22 2017-08-24 Jae Yul Shin Method and apparatus for video interpretation of carotid intima-media thickness
CN109069031A (zh) * 2016-10-20 2018-12-21 京东方科技集团股份有限公司 用于确定对象血压的设备和方法
CN108175387A (zh) * 2017-12-19 2018-06-19 桂林电子科技大学 一种基于心电和脉搏波形态学参数的血管外周阻力检测装置及检测方法
CN109730723A (zh) * 2019-03-11 2019-05-10 京东方科技集团股份有限公司 确定脉搏传输时间的方法、动脉硬化检测设备及系统

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