CN104138253B - A kind of noinvasive arteriotony method for continuous measuring and equipment - Google Patents
A kind of noinvasive arteriotony method for continuous measuring and equipment Download PDFInfo
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Abstract
Disclosure one noinvasive human body artery blood pressure continuous measurement method and apparatus. Noinvasive human body central aortic blood pressure continuous measurement method includes: the method being calculated measured arteries network model personalizing parameters by the radial artery gathered and brachial pulse waveform, the method that radial artery blood pressure shrinks pressure, diastolic pressure and blood pressure waveform is calculated by radial pulse wave velocity and arteries network parameter, calculate ascending aorta-radial artery transmission function, and and then the method that calculates central aortic blood pressure. Noinvasive human body central aortic blood pressure continuous measurement equipment is made up of signal processing and analyzing unit, the pulse wave being worn in wrist and motor message collecting unit and the electrocardio worn on the breast and motor message collecting unit. The present invention monitors electrocardio, radial artery blood pressure and central aortic blood pressure pressure and motion and attitude simultaneously, heart rate and electrocardio morphological parameters is analyzed under various kinestates, analyze tremulous pulse network model parameter and blood pressure parameter, particularly central aortic pressure waveform parameter, for the preventing and treating of high-risk disease such as cardiovascular diseases, particularly hypertension, coronary heart disease etc. with control significant.
Description
Technical Field
The invention belongs to the technical field of medical detection, and particularly relates to a noninvasive continuous blood pressure measuring and monitoring system.
Background
Continuous measurement of blood pressure is a need for the prevention, diagnosis, treatment and management of hypertension. Hypertension is an important risk factor for cardiovascular diseases. Patients with hypertension, however, often do not have significant clinical manifestations and become conscious until Target Organ Damage (TOD) occurs. Therefore, it is very important to monitor and find hypertension early and start treatment before TOD. The traditional 24-hour blood pressure monitor on the market adopts an inflation method, and uses a program to measure and record blood pressure at regular time. The disadvantage is that the accuracy is low, the measured person is disturbed and continuous measurement cannot be obtained. Chinese patent CN1477942A, filed by singapore healthcare international, is a flat measurement of blood pressure. A pressure sensor is added on the radial artery, when the blood vessel is pressed to be flat, the pressure born by the sensor is equal to the pressure of the inner wall of the blood vessel. The disadvantage is that it requires precise wearing and is uncomfortable to wear for long periods of time. Us patent 6413223 discloses a method based on photoplethysmograph (PPG) measured blood volume signals and hemodynamics, however, it has not been used clinically and has not been used practically. The invention of us patent 5865755 uses the measured ecg and PPG signals to calculate the pulse wave arrival time, PPG waveform and heart rate, and further calculates the blood pressure. This method based on the pulse wave propagation velocity can only obtain one mean blood pressure or systolic pressure. Moreover, the blood pressure is calculated by the electrocardio signal and the PPG signal, the principle is not clear, and the measurement precision is not guaranteed, so the technology is not really applied.
The central arterial pressure (Centralaorticpressure) refers to the ascending aortic root blood pressure. In recent years, central arterial pressure has been gaining increasing attention in the medical community, and the guidelines for hypertension management, which are jointly issued by the european hypertension association and the european heart disease association, have been given central arterial pressure as a single index for blood pressure management.
The existing methods for continuously acquiring the central arterial blood pressure are only invasive. It adopts the catheter intervention method to directly measure the blood pressure in the blood vessel by using a pressure gauge. The method is mainly used in the fields of first aid, cardiovascular surgery, intensive care unit and the like. It is accurate, continuous, traumatic, requires professional operation, and is impossible to apply in a large range.
The central artery blood pressure of a human body can not be measured in a non-invasive manner, and the central artery blood pressure is estimated mainly by analyzing physiological signals such as radial artery blood pressure waveforms and the like in the non-invasive manner. Us patent 5,265,011 proposes a General Transfer Function (GTF) method, which estimates a general transfer function of central artery pressure to radial artery pressure by analyzing large sample data, and estimates the central artery blood pressure of a subject from the measured radial artery blood pressure by using the GTF. This method has been adopted by SphygmoCor, a product of atcorpedical, australia. Similar techniques also include us patent 7,628,758, etc. The Singapore HealthSTATS provides a multi-point moving average (N-PointMovingAverage) method, and the human body central arterial blood pressure waveform is obtained after N-point moving average processing (N is one fourth of the sampling rate) is carried out on the human body radial arterial blood pressure waveform. Although the above method has been verified by a large number of clinical trials, the following problems have been encountered: (1) the general transfer function method and the multipoint moving average method are from clinical experience and have no theoretical support. (2) The assumption of both methods is that the transfer function of central arterial pressure to radial arterial pressure is the same regardless of age, sex, and physical condition. This assumption ignores the fact that each individual's vascular parameters differ by age, sex, and disease, which must be reflected in the transfer function. The accuracy of the results of the two methods is certainly problematic, and important diagnostic information is lost.
The Chinese patent 'a non-invasive central artery measuring method and equipment' applied by the applicant of the present patent, application number: 201210584475, the inventive method for measuring the central artery blood pressure of the human body without wound comprises: the method comprises the steps of measuring pulse wave signals of radial artery and brachial artery and arm blood pressure values, calculating personalized parameters of the artery network model of a measured person, calculating an ascending aorta-radial artery transfer function, and calculating a central artery blood pressure waveform from the measured radial artery blood pressure waveform. The non-invasive human central artery blood pressure continuous measuring equipment consists of a pulse wave signal processing and analyzing unit and a radial artery and brachial artery pulse wave signal acquisition unit which is worn on the wrist.
The invention discloses a method and a device for non-invasive continuous arterial blood pressure measurement, which are used for continuous blood pressure measurement and monitoring of a human arterial blood vessel network model based on viscous fluid mechanics. The invention provides a formula, a method and equipment for accurately deducing blood pressure from pulse wave velocity according to an artery network model.
2.3 hundred million hypertension patients exist in China, and continuous blood pressure measurement is a key technology for preventing, diagnosing, treating and controlling hypertension. Therefore, the invention relates to a method and a device for non-invasive continuous arterial blood pressure measurement.
Disclosure of Invention
The invention is different from the prior art, the invention is a method and a device for non-invasive continuous arterial blood pressure measurement, and the technical scheme comprises the following steps:
the non-invasive arterial blood pressure continuous measuring method comprises the following steps: the method comprises the steps of calculating parameters of a radial artery blood vessel model by using pulse wave sequences of a radial artery and a brachial artery which are measured synchronously, calculating average blood pressure, systolic pressure and diastolic pressure by using pulse wave velocities of the radial artery, calculating a pulse wave velocity proportional relation of each segment of blood vessel in a blood vessel network, calculating a transfer function from an ascending aorta to the radial artery, and calculating the blood pressure of a central artery by using the blood pressure of the radial artery.
The non-invasive arterial blood pressure continuous measuring device comprises: the pulse wave and motion signal acquisition unit comprises a sensor for acquiring pulse waves of a radial artery and a brachial artery, a motion sensor, a controller and an attachment device, acquires pulse wave signals of the radial artery and the brachial artery of a measured person and motion signals of a forearm under the conditions of various motions and postures, and amplifies and digitizes the measured signals.
Further comprising: a signal processing and analyzing unit which is connected with the pulse wave and motion signal collecting unit in a wired or wireless way, synchronously controls the pulse wave and motion signal collecting unit in real time, synchronously collects and processes the pulse wave signals of the radial artery and the brachial artery in real time, calculates the artery network model parameters according to the collected pulse wave signal pairs of the radial artery and the brachial artery, calculates the wave velocity of the pulse wave of the radial artery and the brachial artery of each pair of continuously collected pulse waves and the distance between two corresponding sensors, further calculates the blood pressure value and the wave shape, calculates the transfer function from the ascending aorta to the radial artery, further calculates the blood pressure and the wave shape of the central artery, calculates the reflection wave inflection point and the Amplification Index (AIX) of the blood pressure wave shape of the central artery, classifies the motion types, the intensity, the posture and the pitch angle of the trunk and the forearm according to the motion data of the human body and the forearm, processes and analyzes the blood pressure and the electrocardio data under different motions and postures, and uploading data and calculating and analyzing results to a computer or a server.
Further comprising: and the computer or the server is connected with and manages a plurality of noninvasive arterial blood pressure continuous measuring devices, receives and analyzes electrocardio, blood pressure and respiratory data of the wearer in different motion states and postures and at different times, calculates a series of indexes such as cardiopulmonary health indexes and the like, and provides reports and consultations according to the age, sex and medical history of the wearer.
The non-invasive artery blood pressure continuous measurement device also comprises a second embodiment, namely, the wave speed of the radial artery pulse wave is calculated by the electrocardiosignal and the radial artery pulse wave. The non-invasive central blood pressure continuous measurement method and the equipment adopting the technical scheme comprise: the pulse wave and motion signal acquisition unit comprises a sensor for acquiring pulse waves of a radial artery and a brachial artery, a motion sensor, a controller and an attachment device, acquires a radial artery pulse wave signal and a motion signal of a forearm of a measured person under various motion and posture conditions, synchronously measures pulse wave sequence signals of the radial artery and the brachial artery at the beginning of measurement, and amplifies and digitizes the measured signals.
The second embodiment of the non-invasive arterial blood pressure continuous measuring device also comprises an electrocardio and motion signal acquisition unit, which comprises an electrode for measuring electrocardio, a motion sensor, a controller and a wearing device, wherein the electrocardio signal acquisition unit acquires, amplifies and converts into a digital signal, and the device is simultaneously embedded into the motion sensor to measure the motion and posture signals of the trunk of the human body.
The second implementation technical scheme of the non-invasive arterial blood pressure continuous measurement device also comprises a signal processing and analyzing unit which is connected with the pulse wave and motion signal acquisition unit and the electrocardio and motion signal acquisition unit in a wired or wireless mode, synchronously controls the pulse wave and motion signal acquisition unit and the electrocardio and motion signal acquisition unit in real time, synchronously acquires and processes the radial artery pulse wave and the brachial artery pulse wave and the electrocardio and motion signal in real time, calculates arterial network model parameters according to the acquired radial artery and brachial artery pulse wave signal pair sequence, calculates the radial artery pulse wave velocity and further calculates blood pressure and wave shape according to each pair of continuously measured radial artery pulse wave and electrocardio signal wave shape, calculates the transfer function from ascending aorta to radial artery and further calculates central artery blood pressure and wave shape, calculates the reflection wave inflection point and Amplification Index (AIX) of the central artery blood pressure wave shape, according to the motion data of the human body and the forearm, the motion types, the strength, the postures and the pitch angles of the trunk and the forearm are classified, the blood pressure and the electrocardio data under different motions and postures are processed and analyzed, and the data and the calculation analysis result are uploaded to a computer or a server.
The second embodiment of the non-invasive arterial blood pressure continuous measuring device also comprises a computer or a server which is connected with and manages a plurality of non-invasive arterial blood pressure continuous measuring devices, receives and analyzes electrocardio, blood pressure and respiratory data of a wearer under different motion states and postures and different time, calculates a series of indexes such as a heart-lung health index and the like, and provides reports and consultations according to the age, the sex and the medical history of the wearer.
According to an embodiment of the invention, the pulse wave and motion signal acquisition unit is a micro embedded data acquisition system worn on the wrist, which comprises a sensor for measuring pulse waves of radial artery and brachial artery, a motion sensor, a preamplifier, an analog-to-digital converter and a controller, wherein the radial artery sensor is ensured to be stably contacted with the appearance of the radial artery by an attachment device and is not or little influenced by motion and other factors so as to stably measure the pulse wave signals of the radial artery for a long time, the distance between the sensors for measuring the pulse waves of the radial artery and the brachial artery is measured while synchronously and continuously measuring the pulse waves of the brachial artery, and the measured pulse wave signals are amplified by the preamplifier and converted into digital signals which are sent to the signal processing and analyzing unit together with the motion sensor signals in the device.
According to the embodiment of the invention, the forearm arterial blood pressure reference value has two acquisition methods, one is that a manual or automatic pressurizing device is arranged on a radial artery sensor in a pulse wave and motion signal acquisition unit, so that the radial artery pulse wave sensor crushes radial artery blood vessels to reach the condition that the blood pressure value measured by the radial artery pulse wave sensor is equal to the blood pressure value in the blood vessels, and the other is that a conventional sphygmomanometer is used for measuring the forearm blood pressure value.
According to the second implementation scheme of the embodiment of the invention, the electrocardio-and-motion signal acquisition device is a micro embedded system which is worn on the chest by a chest belt, in order to ensure the quality of electrocardio signals, one electrode is arranged at the position of an electrocardio chest lead V3 or V4, the acquired electrocardio signals are pre-amplified and then converted into digital signals, the digital signals and the signals of a motion sensor in the device are sent to the micro signal processing device together, the motion sensor comprises a 3-axis accelerometer, the three-dimensional angle estimation precision of a trunk and a forearm can be improved by adding a gyroscope and a magnetometer, the brachial artery pulse wave sensor is only operated by an operator or a tested person at the beginning to synchronously measure the pulse wave sequences of the radial artery and the brachial artery, and the pulse wave sequences are used for calculating the parameters of an arterial network.
According to a second implementation scheme of the embodiment of the invention, the electrocardiosignal acquisition device further comprises a respiratory wave measurement method based on a thoracic impedance measurement method, the constant-amplitude modulation current source is excited to the human body, and the voltage generated by the current is measured to obtain the thoracic impedance of the human body, and the impedance changes along with the respiration of the human body, so that the respiratory wave is derived.
According to the embodiment of the invention, the signal processing and analyzing unit is a microcomputer device which is worn on the wrist in a watch-like manner or worn on the waist and is connected with the pulse wave and motion signal acquisition unit and the electrocardio and motion signal acquisition unit in a wired or wireless manner, the pulse wave signal acquisition unit and the electrocardio signal acquisition unit are synchronously controlled in real time, the radial artery and brachial artery pulse waves and the electrocardio and motion signals are synchronously acquired and processed in real time, the artery network model parameters are calculated, the radial artery blood pressure and the central artery blood pressure are continuously calculated, the motion and the posture of the trunk and the forearm of the human body are analyzed, data are stored and reported, and the data are uploaded to a computer or a server in a wired or wireless manner.
According to an embodiment of the invention, the non-invasive arterial blood pressure continuous measurement method comprises the following steps: an arterial blood vessel model based on viscous fluid mechanics is established, the radial artery and brachial artery pulse wave sequences which are synchronously measured are used for calculating parameters of the radial artery blood vessel model, namely the blood flow resistance, the blood flow inertia and the blood vessel compliance of the radial artery, establishes the relationship between the blood pressure and the pulse wave velocity of a section of uniform blood vessel without bifurcation, namely the radial artery based on an arterial vessel model, and a formula for calculating average blood pressure, systolic pressure and diastolic pressure according to the pulse wave velocity, and establishing a pulse wave velocity proportional relation of each segment of blood vessel in the blood vessel network, thereby expanding the relationship between the blood pressure and the pulse wave velocity to any blood vessel segment in the artery network, including a central artery to a radial artery, the pulse wave velocity can be calculated from the electrocardiogram and the radial artery pulse wave waveform, a method for calculating the transfer function from the ascending aorta to the radial artery based on an artery blood vessel network model and a formula for calculating the central artery blood pressure from the radial artery blood pressure are established.
According to the embodiment of the invention, the signal processing and analyzing unit obtains the electrocardio data and the respiratory wave data from the electrocardio and motion signal acquisition unit, filters the electrocardio data and the respiratory wave data, removes baseline drift, extracts QRS waves and ST segments from electrocardio signals, detects electrocardio abnormality, and calculates heart rate and heart rate variability.
According to the embodiment of the invention, the signal processing and analyzing unit obtains the human body trunk movement signals from the electrocardio and movement signal acquisition unit, wherein the human body trunk movement signals comprise accelerometer signals, a gyroscope and magnetometer signals, and the human body posture and movement type are deduced according to one group of signals or by fusing a plurality of groups of signals, and the method comprises the following steps: lying, sitting, standing, walking, running, falling, sitting up, lying down, standing up, sitting down, and the step frequency during walking and running, calculating the pitch angle and posture of the trunk, analyzing the motion and static state of the forearm from the forearm motion data obtained by the pulse wave and motion signal acquisition unit, and calculating the pitch angle and posture of the forearm.
According to the embodiment of the invention, the acquired pulse wave signal pair sequences of the radial artery and the brachial artery are processed, a proper wave point sequence pair is found out, a parameter matrix and an observation matrix are listed, and the parameters of an artery network model, including radial artery blood flow resistance, blood flow inertia and blood vessel compliance, are solved by using a least square algorithm.
According to the embodiment of the invention, the radial artery pulse wave propagation speed is calculated by each pair of continuously measured radial artery and brachial artery pulse waves and the distance between two corresponding sensors, or the average propagation speed of the pulse waves from the central artery to the radial artery is calculated by each pair of continuously measured radial artery pulse waves and electrocardiosignal waveforms, then the pulse wave propagation speed of the radial artery is obtained according to the proportional relation of the pulse wave propagation speeds between blood vessels in an artery network, the systolic pressure, the diastolic pressure and the waveform of the radial artery are calculated according to the relation formula of the pulse wave propagation speed and the blood pressure, the transfer function from the ascending aorta to the radial artery is calculated according to a human artery blood vessel network model, and then the central artery blood pressure waveform is calculated.
According to the embodiment of the invention, the variation of blood pressure of the radial artery and the cardiac artery with time and the movement and the posture is analyzed and displayed according to the measured and calculated parameters of the artery network model, the continuous blood pressure of the radial artery and the central artery and the wave form thereof, the movement type, the strength, the posture and the pitch angle data of the trunk and the forearm, and the time label, and the arteriosclerosis index, the health index of the heart-lung system, the wave form inflection point of the central artery blood pressure and the Amplification Index (AIX) are calculated and displayed as the diagnosis basis of hypertension.
According to the embodiment of the invention, blood pressure, electrocardio and respiratory signals and changes of the signals along with time and movement are fused according to the motion and posture types of the human body and the small arm, and multi-organ variability parameters of the wearer are calculated and used as the heart and lung system health index of the wearer to represent the health condition of the wearer and predict possible diseases.
According to the embodiment of the invention, each continuous arterial blood pressure measuring device can operate independently, or can be connected with a computer or a server through a wireless or wired (such as USB) mode, measured and calculated data, and instant states of the continuous arterial blood pressure measuring devices, such as battery level, pulse wave and electrocardio sampling rate, working states and self-checking results of all units, are uploaded to the computer or the server, the computer or the server is connected with and manages a plurality of noninvasive arterial blood pressure continuous measuring devices, electrocardio, respiration and blood pressure data of a wearer in different motion states and postures and different time-of-day are received and analyzed, a comprehensive report is provided according to age, sex and medical history of the wearer, and health conditions and medical conditions are analyzed and tracked for specific individuals, and health and disease occurrence, development, and diagnosis of different populations of the cardiopulmonary system and diseases are researched for all people, The prevention and cure and the rehabilitation are tracked and deeply researched.
Drawings
FIG. 1 is a system block diagram of a non-invasive continuous arterial blood pressure measurement method and apparatus;
FIG. 2 is a schematic diagram of the system configuration and wearing mode of the non-invasive continuous arterial blood pressure measuring method and device;
FIG. 3 is a system block diagram of a second embodiment of a non-invasive continuous arterial blood pressure measurement method and apparatus;
FIG. 4 is a schematic diagram of the construction and wearing of a second embodiment of the system of the method and apparatus for non-invasive continuous arterial blood pressure measurement;
FIG. 5, the left radial artery blood vessel equivalent circuit;
FIG. 6 shows the selection of a pulse wave reference point during the calculation of the pulse wave transmission time;
fig. 7, three coordinate axes of the acceleration sensor worn on the chest and the calculation of the human body pitch angle.
Detailed Description
The present invention will be described in detail below with reference to the attached drawings, and it should be noted that the described embodiments are only intended to facilitate understanding of the present invention, and do not have any limiting effect thereon.
The system block diagram of the non-invasive continuous arterial blood pressure measuring method and the device is shown in figure 1, and the system constitution and the wearing mode are schematically shown in figure 2. The system block diagram of the second embodiment of the non-invasive continuous arterial blood pressure measuring method and device is shown in fig. 3, and the system constitution and wearing mode are schematically shown in fig. 4. The basic scheme of the non-invasive continuous arterial blood pressure measuring method and apparatus differs from the second embodiment only in that the basic scheme calculates the radial pulse wave velocity with the continuously measured pairs of radial pulse waves and brachial pulse waves, and the second embodiment calculates the radial pulse wave velocity with the continuously measured pairs of radial pulse waves and electrocardiographic signals. For convenience of description, we will focus on the second embodiment, the basic scheme only excluding the acquisition, processing and application parts of the electrocardiogram and movement signals.
The invention relates to wearable real-time continuous arterial blood pressure, electrocardiogram and respiration monitoring system hardware and software based on a body sensing network. The whole continuous arterial blood pressure measuring method and device consists of a wearable continuous arterial blood pressure measuring device 100 and a computer/server 200. The continuous arterial blood pressure measuring apparatus 100 is composed of a pulse wave and motion signal collecting unit 110, an electrocardiogram and motion signal collecting unit 120, and a signal processing and analyzing unit 130.
The pulse wave and motion signal acquisition unit 110 is arranged on the pulse wave sensor attachment device and comprises a controller, a preamplifier, a forearm motion sensor 113, a radial pulse wave sensor 111 and a brachial artery pulse wave sensor 112. The forearm motion sensor consists of a triaxial accelerometer, the acceleration signal consists of two parts, namely earth gravity acceleration, and the pitching angle of the forearm relative to the ground plane can be calculated through components of the acceleration sensor on three coordinate axes. The second is the acceleration of the sensor itself, i.e. the forearm itself, which represents the state of motion of the forearm. The separation of the gravity acceleration and the self acceleration in the acceleration signal, and the calculation of the motion state and the pitch angle of the forearm can be performed in the pulse wave and motion signal acquisition unit 110, and the acceleration signal can also be sent to the signal processing and analyzing unit 130 for performing. The pulse wave and motion signal acquisition unit 110 acquires pulse wave signals through the radial pulse wave sensor 111 and the brachial pulse wave sensor 112, and sends the pulse wave signals to the micro signal processing and analyzing unit 130 after amplification and digitization. The radial artery pulse wave sensor 111 needs to continuously collect signals, and in order to ensure the stability of signal collection, the sensor is fastened on the wrist by an attachment device to ensure that the sensor is aligned with the radial artery. At the same time, the sensor is equipped with automatic means for pressing the sensor against the radial artery in order to obtain the radial artery blood pressure. When the radial artery was flattened, the radial artery blood pressure waveform at that time was obtained as a reference blood pressure for continuous measurement. Such a measurement operation needs only one time and is performed by an operator or a subject.
When the brachial artery pulse wave sensor 112 collects pulse waves, an operator or a subject places the brachial artery pulse wave sensor, and simultaneously, the distance between the radial artery pulse wave sensor 111 and the brachial artery pulse wave sensor 112 is measured.
The pulse wave sensor can be made of various pressure sensors, such as deformation sensors, piezoresistors, polyvinylidene fluoride sensors, and the like, and can also be made of sensors based on optics and electromagnetism. Since the optimal measurement location for the radial artery is small, an array of sensors may also be used in order to reduce measurement errors caused by small movements in the sensor location.
The pulse wave and motion signal acquisition unit 110 synchronously acquires radial artery and brachial artery pulse wave signals and evaluates the signals so as to avoid signal distortion caused by improper sensor placement or other reasons and influence on measurement results. When the pulse wave and motion signal acquisition unit 110 obtains a certain number of radial artery and brachial artery pulse wave signal sequences with quality meeting the requirements, the pulse wave and motion signal acquisition unit 110 gives a signal for completing pulse wave acquisition of the brachial artery, and an operator can stop pulse wave acquisition of the brachial artery.
The electrocardiographic and motion signal acquisition unit 120 comprises a controller, a preamplifier, a motion sensor 122, and an electrocardiographic electrode 121. The electrocardiosignal is acquired by the electrocardio-electrode 121 according to the conventional dynamic electrocardiogram electrode connection method, and the number of leads can be varied from 1 to 12 according to requirements. Since the main chest lead is used in blood pressure measurement, one of the electrodes should be placed at chest lead points V3 or V4. The measurement of thoracic impedance and the electrocardiography share two electrodes. A constant-amplitude modulation current source is excited to the human body through the two electrodes, the voltage generated by the current is measured, the chest impedance of the human body is obtained, and the impedance changes along with the respiration of the human body, so that the respiratory wave is pushed out. The impedance also changes with the cardiac ejection, and therefore, it is of some significance in determining the cardiac ejection point. The electrocardiographic and motion signal acquisition unit 120 is fixed in the chest or waist by means of a chest belt or adhesive. The motion sensors include a three-axis accelerometer, a gyroscope, and a magnetometer. Some or all of the sensors may be used as necessary. The posture and the motion type of the human body can be obtained by analyzing the data of the three-axis acceleration sensor: the method comprises the following steps: lying, sitting, standing, walking, running, falling, sitting up, lying down, standing up, sitting down, and the frequency of steps while walking and running. The gyroscope is added to obtain a three-dimensional angle more accurately, and the magnetometer is added to obtain an azimuth angle.
The signal processing and analyzing unit 130 receives signals from the pulse wave and motion signal collecting unit 110 and the electrocardiogram and motion signal collecting unit 120 while monitoring, controlling and synchronizing the operations of the two units. The signal processing and analysis unit 130 runs on a microcomputer device, which may be worn on the wrist like a watch. The signal processing and analyzing unit 130 can be connected with the pulse wave and motion signal collecting unit 110 and the electrocardio and motion signal collecting unit 120 in a wireless or wired manner.
The signal processing and analyzing unit 130 includes a pulse wave and electrocardiogram processing module 131, an arterial network model calculating module 132, a pulse wave velocity and blood pressure calculating module 133, a motion and posture analyzing module 134, a storage and reporting module 135, and a local database 136. It processes and analyzes the pulse wave of radial artery and pulse wave of brachial artery, calculates the network parameter of artery of the person to be measured, processes and analyzes the electrocardiosignal and pulse wave of radial artery, calculates the wave velocity of pulse wave, calculates the blood pressure of radial artery and the blood pressure of central artery.
Each successive arterial blood pressure measurement device may operate independently or may be coupled to a computer or server 200 via wireless or wired (e.g., USB). The computer or server 200 will provide system monitoring and further data analysis of the continuous arterial blood pressure measurement device, providing health advice and services to the wearer.
The following detailed description of embodiments of the invention:
1. blood vessel model based on viscous fluid mechanics
The vascular network of the human body from the radial artery to the central artery comprises several parts of ascending aorta, brachial artery, radial artery and peripheral capillary, wherein, besides the peripheral artery, other sections of the artery conform to the same model of aortic and aortic vessels, but the parameters are different. We will build two models, a large middle artery model, and a peripheral capillary artery model, and then build the desired vascular network through the cascade. Chinese patent 'a method and equipment for measuring central artery without wound', application number: 201210584475, the entire human arterial network and its equations are derived using viscous fluid mechanics. From the results, we can use the pulse wave sequences of the radial artery and the brachial artery which are synchronously measured to calculate the parameters of the radial artery blood vessel model as follows:
refer to the left radial artery equivalent circuit of FIG. 5, whereinIs the resistance to blood flow in the radial artery;is the blood flow inertia of the radial artery;vascular compliance of the radial artery;peripheral resistance representing the arteriole vascular network connected to the radial artery;is the blood pressure at the beginning of the radial artery;is the blood pressure at the end of the radial artery;the blood flow quantity flowing into the starting end of the radial artery;the blood flow out of the distal radial artery. Model parameters、、、The estimation method of (2) is as follows.
(1) Left radial artery model peripheral resistance estimation
The human blood finally flows to a network of arteriole vessels cascaded by a plurality of segments of arterial vessels. The flow of blood through the artery into the arteriolar vascular network is recorded as. Total peripheral resistance of human bodyIs represented as follows:
then, according to the blood vessel parameters discussed above and the proportional relation of the model parameters, the peripheral resistance cascaded by the left radial artery blood vessel model is obtained，
(2) Radial artery model parameters, estimation
From the radial artery model, we can obtain the following mathematical expression:
finishing formula (3.6) to obtain
Wherein the parameters、、Can be estimated by a general least squares algorithm.
(3) Observation matrix for parameter estimation
Known from the left radial artery model;i.e., the blood flow at the end of the left radial artery is linear with blood pressure. The blood flow curve can be measured by the pressure sensor in the radial artery of the left wrist, but the absolute position, requires calibration. Calculation formula combined with left radial artery blood flow value
The result of the above formula is used for calibrating the curve of the radial artery blood flow rate, and the left radial artery blood flow rate can be obtained。
Meanwhile, the blood pressure curve at the beginning of the left radial artery can be measured at the tail end of the brachial artery at the elbow of the left arm by a pressure sensor. Further, the pressure curve is calibrated through forearm systolic pressure and diastolic pressure measured by mercury column method, or the radial artery blood pressure waveform is synchronously measured by automatic pressurizing device on radial artery pulse wave sensor by using flat method principle to obtain left radial artery blood pressure。
Finally, the following observation matrix can be obtained:
the following parameter matrix is defined:
obtaining a relation equation of a parameter matrix and an observation matrix
Wherein,to observe errors. If there isThe secondary observation, i.e. synchronously acquiring m sampling point data of radial artery and brachial artery pulse wave signal waveforms from the pulse wave and motion acquisition unit 110, makesThen, there are:
wherein:
the idea of the least square algorithm is to find oneIs estimated value ofMake each observationAnd is composed ofEstimated ofThe sum of the squares of the differences is minimal.Least squares estimationComprises the following steps:
solving the equation to obtain the parameters、、Is described in (1).
Blood pressure monitoring based on radial artery model
(1) Radial artery blood pressure and pulse wave velocity relation based on blood vessel model
The pulse wave velocity is determined by the mechanical properties of the arterial wall (viscosity and elasticity), the geometrical characteristics (diameter and wall thickness) and the density of the blood. Since blood in the elastic conduit (artery) is an incompressible liquid, energy transfer is mainly conducted through the vessel wall, and thus the function of the vessel is a major factor affecting the velocity of the pulse wave. Their relationship can be expressed by the Moens-Korteweg equation:
in the formula,is the velocity of the pulse wave and the velocity of the pulse wave,is the modulus of elasticity of the vessel wall,is the density of the blood and is,is the thickness of the blood vessel wall,is the vessel inner diameter. There is also a relationship between blood pressure and elastic modulus of the vessel wall as follows:
in the formula,is the modulus of elasticity at zero pressure,is the blood pressure (mmHg),is a parameter for characterizing blood vessels, and the value range is about 0.016-0.018 (mmHg).
The mean radial artery blood pressure can be deduced from the above two formulasAnd radial pulse wave velocityThe relationship between them is as follows:
wherein,is a characteristic parameter of the radial artery blood vessel,is the inner diameter of a radial artery blood vessel,is the density of the blood in the radial artery,is the thickness of the radial artery vessel wall,is the elastic modulus of the radial artery vessel wall. The above parameters are individual parameters, and the values thereof vary from person to person.
(2) Continuous mean blood pressure estimation at the radial artery
For a length ofRadial artery blood vesselThe pulse wave velocity can be expressed as:
in the formula,the time of pulse wave propagation in the radial artery. Further can obtain
Vascular compliance according to radial artery vascular modelAnd the inertia of blood flowDefinition of (c) we can convert the formula as follows:
the above formula is a radial artery continuous blood pressure estimation formula based on a blood vessel model: we can determine the transmission time of beat-to-beat pulse wave in radial arteryEstimating continuous radial artery mean blood pressure. Where vessel compliance and blood flow inertia are known. Characteristic parameters of blood vesselsCan be made up of a group of radial arteryAnd corresponding pulse wave transit timeAnd (6) obtaining calibration.
(3) Systolic and diastolic pressure estimates at the radial artery
During diastole, the valve closes and blood flow into the radial artery is approximately zero, i.e.. I.e. in diastole: (，For the moment of the start of the diastole,the end of diastole time) we have:
wherein,=. Solving the ordinary differential equation to obtain the end blood pressure of the radial artery in diastole as follows:
wherein,the blood pressure at the end of the radial artery at the beginning of diastole (i.e. systolic pressure). Further, the radial artery end diastolic pressure is known as:
for each pulse wave, we can determine the transmission time of the pulse wave in the radial arteryCalculating the average blood pressure of the pulse wave. And because of the even and uniform pulse waveAnd systolic pressureDiastolic blood pressureThe following relationships exist:
whereinThe pulse wave shape coefficient can be calculated from the pulse wave shape. The two formulas obtain a systolic pressure calculation formula of beat-to-beat pulse waves:
further, the diastolic pressure is calculated as:
3. pulse wave velocity proportional relation of each section of blood vessel in blood vessel network
The above formula of deriving blood pressure from pulse wave propagation time or pulse wave velocity is only applicable to a uniform section of blood vessel without bifurcation, such as radial artery. However, the length of the blood vessel is relatively short, the measurement error is not easy to control, and the measurement is difficult. In the following, we show that in the human artery and blood vessel network, knowing the pulse wave velocity in any section of blood vessel, the pulse wave velocity of the radial artery can be derived, and then the blood pressure value can be calculated. The formula is given below by taking the ascending aorta-radial pulse wave transit time as an example:
the pulse wave velocity is determined by the mechanical properties of the arterial wall (viscosity and elasticity), the geometrical characteristics (diameter and wall thickness) and the density of the blood. Since blood in the elastic conduit (artery) is an incompressible liquid, energy transfer is mainly conducted through the vessel wall, and thus the function of the vessel is a major factor affecting the velocity of the pulse wave. Their relationship can be expressed by the Moens-Korteweg equation and yields:
therefore, the pulse wave transmission time in any blood vessel section is as follows:
whereinThe vessel segments are numbered. Ascending aorta-radial pulse wave transit timeFor the pulse wave in the ascending aorta () Aortic arch I: () Aortic arch II: () The left subclavian artery I: () Left subclavian artery II: (A)) And the radial artery () The sum of the transit times of (a) and then we can getThe formula of (c) is derived as:
further, the formula is adjusted according to the known pulse wave transmission time of ascending aorta-radial arteryOn the premise of (1), we can calculate the transit time of the pulse wave in the radial artery as follows:
now assume the blood densities of the different vessels in the formulaBlood vessel characteristic parameterAnd blood pressureSimilarly, then the above formula can be simplified as:
wherein、、、Is a blood vesselThe vascular parameter ratios of (A) are obtainable from the documents Westerhof, N.et.et.E., Analogstosoftheman systems and systems, journal of vascular dynamics, 1969.2(2): p.121-134, and Wang, J.J.and K.H.Parker, Waveproparation of vascular diagnosis, journal of vascular dynamics, 2004.37(4): p.457-470.
The great use of obtaining the proportional relation of the pulse wave velocities is that the pulse wave velocity parameters of a specific section of blood vessel can be deduced through the measured pulse wave velocities after the cascade connection of a plurality of sections of blood vessels. For example, the pulse wave velocity measured by using the R wave (or cardiac impedance waveform) of the electrocardiogram and the pulse wave at the end of the radial artery is the average pulse wave velocity of the blood vessel cascade of three segments, namely the central artery, the brachial artery and the radial artery, and the pulse wave velocity of each segment is different, so that it is not appropriate to calculate the blood pressure by directly using the average. Through the proportional relation of the pulse wave velocity in the three sections of blood vessels, the pulse wave velocity of each section of blood vessel can be specifically calculated, and the blood pressure value can be deduced by using the pulse wave velocity. The pulse wave velocity of a certain section is derived by using the average pulse wave velocity, which is easier to implement than directly measuring the pulse wave velocity of the section of blood vessel, because the pulse waves or signals are not easy to be measured simultaneously at the initial section and the tail end of most blood vessels. For example, the terminal artery of the radial artery is easy to measure, and the interference is small, but the pulse wave of the initial segment of the radial artery is not easy to measure.
Transfer function based on arterial blood vessel network model and central arterial pressure estimation
The transfer function of the blood pressure between any nodes in the human artery blood vessel network model is recorded as:(whereinIn the representation modelBlood pressure of node number). According to the network model, the electric network is equivalent, and the voltage transfer function is calculated to obtain the transfer function. In particular, the blood pressure at the beginning of the ascending aorta model can be obtained () For input, the blood pressure at the end of the radial artery model () As a transfer function of the output。
Radial artery blood pressure waveformAnd the blood pressure waveform of the cardiac arteryThe relation between can be used in the frequency domain（) And (4) showing. The relational expression is as follows:
thus, the central arterial blood pressure estimation formula is as follows:
5. motion and pose detection of human body and forearm
The non-invasive and non-inflatable human central arterial blood pressure continuous measuring equipment continuously measures the blood pressure of the upper limbs of the human body and simultaneously continuously obtains the central arterial blood pressure waveform. Meanwhile, electrocardiosignals, respiration signals and body motion and posture information including dynamic information and pitch angle information of the forearm are obtained.
Among the types of motion we want to classify, three major categories can be classified: lying, sitting and standing are of the type of stationary movement, rising, lying, standing and sitting are of the type of transitional movement, walkingAnd running as a type of dynamic motion. Three characteristics of signal amplitude area, accelerometer axis orientation and accumulated variation are adopted as the basis of classification for the three motion types. The signal amplitude area reflects the intensity of the current human motion according to the size of the human motion acceleration fluctuation area, and is defined as:
the accumulated variation is used for describing the characteristics of the transitional motion type, and the characteristic is proposed based on the characteristic that the acceleration has continuous variation when the human body makes transitional motion action, and the variation amplitude is large. In the process of the human body doing transition movement, the posture is often changed, and the changed posture enables the decomposed acceleration values of the gravity acceleration component on the three axes of the accelerometer to show a trend of continuously changing (increasing or decreasing) towards a certain direction within a certain duration.
To map features to a particular type of motion, the data needs to be segmented first. The segmentation interval depends on the shortest duration of the body movement, which is typically done over 1 second, so the segmentation window is positioned for 1 second, i.e. 100 sample points at a sampling rate of 100 Hz. After the data segmentation is completed, the three features will be extracted for the acceleration data of each data segment. And subsequent classification is carried out according to the characteristics corresponding to the data segment to determine the motion state of the human body corresponding to the data segment at the time.
Because the accelerometer can measure the acceleration of gravity, when the human body posture changes, the acceleration of gravity is decomposed to each axis of the accelerometer so as to calculate the included angle between each axis and the gravity direction, and the posture of the human body can be identified according to the position of each axis. The position of the accelerometer and the orientation of the three axes of the accelerometer when the human body is standing are shown in fig. 7. When the human body is in a standing posture, the x-axis points to the back of the body, the y-axis points to the right of the body and the z-axis points to the head opposite to the direction of gravity. When the postures of the human body are different, such as standing and lying, the direction of the z axis is almost opposite to the gravity direction when the human body stands, and the measured included angle between the z axis and the gravity direction is about 180 degrees; when lying flat, the z-axis is perpendicular to the direction of gravity, and the measured angle with the direction of gravity is about 90 degrees. Since the orientations of the three axes of different attitude accelerometers are also different, the accelerometer axis orientations can be used as features for distinguishing human body attitudes. The orientation of the accelerometer axes is often determined from the resolved components of the gravitational acceleration in each axis, from which the pitch angles of the torso and forearm of the body, i.e. the attitude, can be measured.
Noninvasive continuous arterial blood pressure measurement step
1) The whole device is worn as per fig. 2. And adjusting the position of the radial artery pulse wave sensor to align the radial artery pulse wave sensor to the radial artery, so as to obtain a stable radial artery pulse wave waveform.
2) The brachial artery pulse wave sensor is arranged at the starting end of the radial artery (namely the tail end of the brachial artery) to obtain a satisfactory string of pulse wave signals. Meanwhile, the distance between the start and end of the radial artery is measured, and the measured value is input to the signal processing and analyzing unit 130.
3) And starting an automatic pressure adjusting device on the radial artery sensor or manually adjusting until the radial artery blood vessel is flattened to obtain a radial artery blood pressure waveform. Or by other blood pressure measurement methods, and input to the signal processing and analysis unit 130. The blood pressure value measured by one of the two methods is used for the following calculation of artery network model parameters and the calculation of continuous blood pressure of the radial artery.
4) After the operation is finished, the system is switched to a continuous measurement mode, and the following operation is automatically carried out;
a) the pulse wave and electrocardiogram processing 131 performs filtering processing on the pulse wave and the electrocardiogram signal to obtain a brachial artery and radial artery pulse wave signal pair sequence and continuous electrocardiogram and radial artery waveform signals, which are respectively sent to an artery network model calculation 132 and a pulse wave velocity and blood pressure calculation 133, and simultaneously the data are stored in a local database 136.
b) The artery network model calculation 132 calculates model parameters including vascular compliance, blood flow inertia, peripheral vascular resistance and blood flow resistance of the subject's left radial artery model from the sequence of brachial and radial pulse wave signal pairs from the pulse wave and electrocardiogram processing 131 using the methods and formulas in the "viscous fluid mechanics based vascular model" described above. And sends the model parameters to the pulse wave velocity and blood pressure calculation 133. While storing the vessel model parameters in the local database 136.
c) The pulse wave velocity and blood pressure calculation 133 uses the pulse wave and the pair of continuous electrocardiograph and radial pulse wave waveform signals from the electrocardiograph processing 131 to calculate the radial pulse wave velocity using the method and formula in the above "proportional relationship of pulse wave velocity of each segment of blood vessel in the blood vessel network". The arterial network model parameters sent are further calculated 132 using the arterial network model, and the radial artery blood pressure values and waveforms are calculated using the method and formula in "blood pressure monitoring based on radial artery model" above, and the central artery blood pressure and waveforms are further calculated using the method and formula in "transfer function based on arterial blood vessel network model and estimation of central artery pressure" above. The calculation results are sent to the local database 136.
d) If the basic scheme of the non-invasive continuous arterial blood pressure measuring method and device is adopted, the pulse wave velocity and blood pressure calculation 133 uses the waveform signal pair of the continuous brachial artery pulse wave and the radial artery pulse wave sent by the pulse wave processing 131, uses the method in the figure 6 and the measured distance between the radial artery sensor and the brachial artery sensor to measure the radial artery pulse wave velocity, and uses the method and formula in the 'pulse wave velocity proportional relation of each segment of blood vessel in the blood vessel network' to calculate the radial artery pulse wave velocity. The arterial network model parameters sent are further calculated 132 using the arterial network model, and the radial artery blood pressure values and waveforms are calculated using the method and formula in "blood pressure monitoring based on radial artery model" above, and the central artery blood pressure and waveforms are further calculated using the method and formula in "transfer function based on arterial blood vessel network model and estimation of central artery pressure" above. The calculation results are sent to the local database 136.
e) The motion and posture analysis 134 receives the forearm motion sensor (mainly, acceleration sensor) signal from the pulse wave and motion acquisition unit 110 and the trunk motion sensor (mainly, acceleration sensor) signal from the electrocardiograph and motion acquisition unit 120, respectively, and classifies the motion type, intensity, posture and pitch angle of the trunk and forearm according to the method in the above-mentioned "motion and posture detection of the human body and forearm". The results are sent to the local database 136.
f) The storage and report 135 reads arterial network model parameters, radial and central arterial blood pressure and waveforms, type of motion, strength, attitude and pitch data of the torso and forearm from the local database 136. According to the time label, the variation curves of the blood pressure of the radial artery and the cardiac artery along with the time, the movement and the posture are drawn and displayed, and the arteriosclerosis index, the health index of the heart-lung system, the central artery blood pressure waveform parameter and the like are calculated and displayed.
5) Each continuous arterial blood pressure measuring device 100 can operate independently, or can be connected with a computer or server 200 through wireless or wired connection (such as a USB port), and the data in the local database 136 and the instant states of the continuous arterial blood pressure measuring device 100, such as the battery level, the pulse wave and electrocardio sampling rate, the working state and the self-test result of each unit, are uploaded to the computer or server 200. The computer or server 200 will provide system monitoring and further data analysis for the continuous arterial blood pressure measurement device 100, providing health advice and services to the wearer.
Health index of the pulmonary system in the centers of daily life, work and exercise
Research and medical experiments prove that the heart-lung system is a dynamic system, is controlled by autonomic nerves, and has the function of adaptively regulating the heart beat, blood supply and oxygen supply of a person along with the change of physical conditions, movement, external conditions and the like of the person. Medical workers also find that a plurality of serious cardiovascular diseases, such as coronary heart disease and cerebral apoplexy, have high correlation with heart rate variability, respiration, blood pressure change and the like. For people of a specific age and sex, for example, the state of the heart-lung system (normal, coronary heart disease, arrhythmia, myocardial ischemia …) and the measured electrocardio, respiration, blood pressure and the like are represented by a Bayesian network, and the probability of the cause of the state of the heart-lung system under the given factors and measured values is proportional to the product of the likelihood of the three measurements of the electrocardio, the respiration and the blood pressure. That is, if people of different ages and sexes are selected, the electrocardio, respiration and blood pressure are measured while the movement is measured, and the time of day is taken into consideration; and then the measured electrocardio, respiration, blood pressure and motion signals are processed to obtain the likelihood ratio of some specific diseases under all the factor conditions. With these likelihoods, the probability of a person suffering from a disease can be calculated for a set of measurements of the person. That is, these likelihoods can be used as an index of the health of the cardiopulmonary system and as an indicator of early warning and diagnosis of certain diseases. The following is a method of finding a health index of the cardiopulmonary system:
and (5) motion segmentation. The first step after preprocessing the obtained electrocardiographic, respiratory and blood pressure data is further processing, namely motion segmentation, by taking the motion type, intensity and posture as scene conditions. The necessity of this treatment is very evident: the heart-lung system is greatly influenced by movement, and the heart rate, the breathing rate and the blood pressure are different under different movements; sudden changes in the posture of a person can lead to sudden changes in the measurement results, not only because the changes in posture lead to reactions of the cardiopulmonary system, but also because the position of the measuring instrument relative to the body changes, thereby generating measurement noise and errors; even in a static state, the blood pressure sensor does not have the same relative position with the heart, and the blood pressure measurement results are different.
As mentioned previously, we can classify the types of movements as: lying (lying, left side, right side), sitting, standing, walking (step frequency), running (step frequency); the motion changes are as follows: throwing, sitting up, standing up, sitting down, lying down, accelerating and decelerating; and the height of the blood pressure sensor relative to the heart. Firstly, segmenting all electrocardio, respiration and blood pressure data streams by motion types and motion changes to obtain two main data sequences: one is a data sequence when motion changes occur, which is an important data source for diseases caused by some sudden motions. The other is a data sequence of electrocardiogram, respiration and blood pressure in a static posture or in a constant intensity motion scenario.
And (5) feature extraction. The electrocardiographic, respiratory and blood pressure data sequences under specific motion and posture need further feature extraction so as to obtain feature measurement with direct and obvious medical significance. For example, the medical significance of electrocardiograms is not obvious, and we extract from them RR-gap (heart rate) sequences and ST-segment sequences, which characterize the dynamics of the heart and are associated with arrhythmias and myocardial ischemia, respectively.
Because the time sequence is driven by a plurality of factors and is nonlinear and non-stationary, especially when an individual moves or has physiological abnormality, in order to propose different change characteristics, the time sequence decomposition processing is carried out on the sequence signal, and the decomposition is divided into three parts: trend (Trend), Outlier (Outlier), and Fluctuation (Fluctuation) components.
A physiological cycle. The cardiovascular system changes over time during the day representing a physiological cycle. As a typical example, a day's blood pressure changes in a hypertensive patient are valuable for diagnosis and medication. For this reason, we adopt a method of one hour every two hours to obtain a 24-hour feature metric vector array:
{ [ Fecg, Fresp, Fbp ] (t, act), t =1,2,3, … 12, act = (attitude, motion) }
The characteristics in brackets in the above formula are the characteristics of electrocardio, respiration and blood pressure in turn, including heart rate variation degree, electrocardiogram ST segment, respiration rate variation degree, blood pressure variation degree and the like. For a person, the measured values of the characteristics under a certain time, a certain motion state and a certain motion amount form a characteristic array, and after a normal value and the likelihood of diseases are obtained, the characteristic array becomes an index for judging the health of the heart-lung system of the body and an important index for early warning of the heart-lung system diseases, monitoring of treatment effects, discharge observation and follow-up.
Claims (11)
1. A non-invasive continuous arterial blood pressure measurement device comprising:
a method for calculating radial artery blood vessel model parameters by using pulse wave sequences of a radial artery and a brachial artery which are synchronously measured, a method for calculating average blood pressure, systolic pressure and diastolic pressure by using pulse wave velocity of the radial artery, a method for calculating a transfer function from ascending aorta to the radial artery according to the pulse wave velocity proportional relation of each segment of blood vessel in a blood vessel network, and a method for calculating central artery blood pressure by using the radial artery blood pressure;
the pulse wave and motion signal acquisition unit comprises a sensor for acquiring pulse waves of a radial artery and a brachial artery, a motion sensor, a controller and an attachment device, acquires pulse wave signals of the radial artery and the brachial artery of a measured person and motion signals of a forearm under the conditions of various motions and postures, and amplifies and digitizes the measured signals;
a signal processing and analyzing unit which is connected with the pulse wave and motion signal collecting unit in a wired or wireless way, synchronously controls the pulse wave and motion signal collecting unit in real time, synchronously collects and processes the pulse wave signals of the radial artery and the brachial artery in real time, calculates the parameters of an artery network model by the collected pulse wave signal pairs of the radial artery and the brachial artery, calculates the wave velocity of the pulse wave of the radial artery and the brachial artery by each pair of continuously collected pulse waves of the radial artery and the brachial artery and the distance between two corresponding sensors, further calculates the blood pressure value and the wave shape, calculates the transfer function from the ascending aorta to the radial artery, further calculates the blood pressure and the wave shape of the central artery, calculates the reflection wave inflection point and the amplification index of the blood pressure wave shape of the central artery, classifies the motion types, the intensity, the postures and the pitch angles of the trunk and the brachial arms according to the motion data of the human body and the brachial arms, processes and analyzes the, uploading data and calculating and analyzing results to a computer or a server;
and the computer or the server is connected with and manages a plurality of noninvasive arterial blood pressure continuous measuring devices, receives and analyzes the electrocardio, blood pressure and respiratory data of the wearer under different motion states and postures and at different times, calculates the heart-lung health index, and provides reports and consultations according to the age, sex and medical history of the wearer.
2. The non-invasive arterial blood pressure continuous measuring apparatus according to claim 1, characterized in that: the pulse wave and motion signal acquisition unit is a miniature embedded data acquisition system worn on the wrist, and comprises a sensor for measuring pulse waves of a radial artery and a brachial artery, a motion sensor, a preamplifier, an analog-to-digital converter and a controller, wherein the radial artery sensor is ensured to be stably contacted with the outer surface of the radial artery by an attachment device and is not influenced or hardly influenced by motion so as to stably measure pulse wave signals of the radial artery in a long time, the distance between the sensors for measuring the pulse waves of the radial artery and the brachial artery is measured while the pulse waves of the brachial artery are synchronously and continuously measured, the measured pulse wave signals are amplified by the preamplifier and converted into digital signals, and the digital signals are sent to the signal processing and analyzing unit together with the motion sensor signals in the device.
3. The non-invasive arterial blood pressure continuous measuring apparatus according to claim 1, characterized in that: there are two methods for obtaining the brachial artery blood pressure reference value, one is to install manual or automatic pressurizing device on the radial artery sensor in the pulse wave and movement signal collecting unit to make the radial artery pulse wave sensor flatten the radial artery blood vessel to make the blood pressure value measured by the radial artery pulse wave sensor equal to the blood pressure value in the blood vessel, and the other is to measure the brachial artery blood pressure value by the conventional sphygmomanometer.
4. The non-invasive arterial blood pressure continuous measuring apparatus according to claim 1, characterized in that: the signal processing and analyzing unit is a microcomputer device and is connected with the pulse wave and motion signal acquisition unit in a wired or wireless mode, the pulse wave signal acquisition unit is synchronously controlled in real time, radial artery and brachial artery pulse waves and motion signals are synchronously acquired and processed in real time, artery network model parameters are calculated, radial artery blood pressure and central artery blood pressure are continuously calculated, motion and postures of the trunk and the forearm of a human body are analyzed, data are stored, a report is provided, and data are uploaded to a computer or a server in a wired or wireless mode.
5. The non-invasive arterial blood pressure continuous measuring apparatus according to claim 1, characterized in that: the non-invasive arterial blood pressure continuous measurement method comprises the following steps: an arterial blood vessel model based on viscous fluid mechanics is established, the pulse wave sequences of the radial artery and the brachial artery which are synchronously measured are used for calculating parameters of the radial artery blood vessel model, namely the blood flow resistance, the blood flow inertia and the blood vessel compliance of the radial artery, the relation between the blood pressure of a section of uniform blood vessel without bifurcation of the radial artery based on the arterial blood vessel model and the pulse wave velocity is established, and formulas for calculating the average blood pressure, the systolic pressure and the diastolic pressure according to the pulse wave velocity are established; establishing a pulse wave velocity proportional relation of each section of blood vessel in the blood vessel network, thereby expanding the relation of blood pressure and pulse wave velocity to any blood vessel section in the artery network, including a central artery to a radial artery; a method for calculating a transfer function from ascending aorta to radial artery based on an artery blood vessel network model and a formula for calculating the central artery blood pressure from the radial artery blood pressure are established.
6. The non-invasive continuous arterial blood pressure measuring apparatus according to claim 4, characterized by: the signal processing and analyzing unit processes the acquired radial artery and brachial artery pulse wave signal pair sequence, finds out a proper wave point sequence pair, lists a parameter matrix and an observation matrix, and uses a least square algorithm to solve artery network model parameters including radial artery blood flow resistance, blood flow inertia and blood vessel compliance.
7. The non-invasive arterial blood pressure continuous measuring apparatus according to claim 4, characterized in that: the signal processing and analyzing unit calculates the radial pulse wave propagation speed by each pair of continuously measured radial and brachial artery pulse waves and the distance between two corresponding sensors, calculates the average propagation speed of the pulse waves from the central artery to the radial artery, obtains the pulse wave propagation speed of the radial artery according to the proportional relation of the pulse wave propagation speeds between blood vessels in an artery network, calculates the systolic pressure, the diastolic pressure and the waveform of the radial artery blood pressure according to the relational formula of the pulse wave propagation speed and the blood pressure, calculates the transfer function from the ascending aorta to the radial artery according to a human artery blood vessel network model, and further calculates the central artery blood pressure waveform.
8. The non-invasive arterial blood pressure continuous measuring apparatus according to claim 4, characterized in that: and the signal processing and analyzing unit analyzes and displays the blood pressure of the radial artery and the cardiac artery along with time and the change of the motion and the posture according to the measured and calculated parameters of the arterial network model, the continuous blood pressure of the radial artery and the cardiac artery and the waveforms thereof, the motion types, the intensity, the posture and the pitch angle data of the trunk and the forearm, and the time labels, and calculates and displays an arteriosclerosis index, a health index of the heart-lung system, a reflection wave inflection point of the waveform of the central artery blood pressure and an amplification index as a diagnosis basis of the hypertension.
9. The non-invasive arterial blood pressure continuous measuring apparatus according to claim 1, characterized in that: according to the motion and posture types of the human body and the forearm, blood pressure, electrocardio signals, respiratory signals and changes of the blood pressure, the electrocardio signals and the respiratory signals along with time and motion are fused, multi-organ variability parameters of the wearer are calculated and used as heart and lung system health indexes of the wearer to represent the health condition of the wearer and predict possible diseases.
10. The non-invasive arterial blood pressure continuous measuring apparatus according to claim 1, characterized in that: each continuous arterial blood pressure measuring device can run independently, and can also be connected with a computer or a server through wireless or wired connection, the measured and calculated data and the instant state of the continuous arterial blood pressure measuring device are uploaded to the computer or the server, the computer or the server is connected with and manages a plurality of noninvasive arterial blood pressure continuous measuring devices, the electrocardio, respiration and blood pressure data of a wearer in different motion states and postures and different time periods are received and analyzed, a comprehensive report is provided according to the age, sex and medical history of the wearer, a health condition and an illness state are analyzed and tracked for specific individuals, and all people are tracked and deeply researched for the occurrence, development, prevention and treatment and rehabilitation of different people for the health and diseases of the cardiopulmonary system.
11. A non-invasive continuous arterial blood pressure measurement device comprising:
a method for calculating radial artery blood vessel model parameters by using pulse wave sequences of a radial artery and a brachial artery which are synchronously measured, a method for calculating average blood pressure, systolic pressure and diastolic pressure by using pulse wave velocity of the radial artery, a pulse wave velocity proportional relation of each segment of blood vessel in a blood vessel network, a method for calculating a transfer function from an ascending aorta to the radial artery, and a method for calculating central artery blood pressure by using the radial artery blood pressure;
the pulse wave and motion signal acquisition unit comprises a sensor for acquiring pulse waves of a radial artery and a brachial artery, a motion sensor, a controller and an attachment device, acquires a radial artery pulse wave signal and a motion signal of a forearm of a measured person under various motion and posture conditions, synchronously measures pulse wave sequence signals of the radial artery and the brachial artery at the beginning of measurement, and amplifies and digitizes the measured signals;
the electrocardio and motion signal acquisition unit comprises an electrode for measuring electrocardio, a motion sensor, a controller and a wearing device, acquires and amplifies electrocardio signals and converts the electrocardio signals into digital signals, and the wearing device is embedded with the motion sensor at the same time and measures motion and posture signals of the trunk of a human body;
a signal processing and analyzing unit which is connected with the pulse wave and motion signal acquisition unit and the electrocardio and motion signal acquisition unit in a wired or wireless way, synchronously controls the pulse wave and motion signal acquisition unit and the electrocardio and motion signal acquisition unit in real time, synchronously acquires and processes the pulse waves of the radial artery and the brachial artery and the electrocardio and motion signals in real time, calculates artery network model parameters by the acquired pulse wave signal pair sequence of the radial artery and the brachial artery, calculates the speed of the pulse wave of the radial artery and further calculates the blood pressure and the wave shape by each pair of continuously measured pulse waves of the radial artery and the electrocardio signal wave shape of the radial artery, calculates the transfer function from the ascending aorta to the radial artery and further calculates the blood pressure and the wave shape of the central artery, calculates the reflected wave of the blood pressure wave shape of the central artery and the inflection point amplification index, classifies the motion types of the trunk and the forearm according to the motion data of the human, Intensity, posture and pitch angle, processing and analyzing blood pressure and electrocardio data under different motions and postures, and uploading the data and calculating and analyzing results to a computer or a server;
the electrocardio and motion signal acquisition device is a micro embedded system worn in front of the chest, the acquired electrocardio signals are pre-amplified and then converted into digital signals, and the digital signals and the signals of a motion sensor in the electrocardio and motion signal acquisition device are sent to the micro signal processing device together, the motion sensor comprises a 3-axis accelerometer, a gyroscope and a magnetometer, the brachial artery pulse wave sensor is only operated by an operator or a testee at the beginning to synchronously measure the pulse wave sequences of the radial artery and the brachial artery for calculating the artery network parameters;
and the computer or the server is connected with and manages a plurality of noninvasive arterial blood pressure continuous measuring devices, receives and analyzes the electrocardio, blood pressure and respiratory data of the wearer under different motion states and postures and at different times, calculates the heart-lung health index, and provides reports and consultations according to the age, sex and medical history of the wearer.
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