CN104138253A - Noninvasive continuous arterial blood pressure measuring method and equipment - Google Patents
Noninvasive continuous arterial blood pressure measuring method and equipment Download PDFInfo
- Publication number
- CN104138253A CN104138253A CN201310172583.1A CN201310172583A CN104138253A CN 104138253 A CN104138253 A CN 104138253A CN 201310172583 A CN201310172583 A CN 201310172583A CN 104138253 A CN104138253 A CN 104138253A
- Authority
- CN
- China
- Prior art keywords
- radial artery
- pulse wave
- pulse
- arteriotony
- blood pressure
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Landscapes
- Measuring Pulse, Heart Rate, Blood Pressure Or Blood Flow (AREA)
Abstract
The invention discloses a noninvasive continuous human body arterial blood pressure measuring method and equipment. The noninvasive continuous human body central arterial blood pressure measuring method comprises the steps as follows: calculating individualization parameters of a to-be-measured person artery blood vessel network model according to acquired pulse wave forms of radial arteries and brachial arteries; calculating radial artery blood pressure systolic pressure, diastolic pressure and blood pressure wave forms according to radial artery pulse wave speeds and artery blood vessel network parameters; calculating ascending aorta-radial artery transfer functions; further calculating central arterial blood pressure. The noninvasive continuous human body central arterial blood pressure measuring equipment consists of a signal processing and analyzing unit, a pulse wave and motion signal acquisition unit worn on the wrist as well as an electro-cardio and motion signal acquisition unit worn in front of the chest. According to the method and the equipment, electrocardiograms, the radial artery blood pressure, the central arterial blood pressure as well as motions and postures are monitored simultaneously, heart rate and electro-cardio morphological parameters are analyzed in various motion states, artery network model parameters and blood pressure parameters, particularly central arterial pressure wave form parameters, are analyzed, and the method and the equipment have great significance for prevention and control on cardiovascular diseases, particularly for prevention and control on high-risk diseases such as the hypertension, the coronary heart disease and the like.
Description
Technical field
The invention belongs to technical field of medical detection, particularly relate to a kind of noinvasive continuous BP measurement and monitoring system.
Background technology
The continuous measurement of blood pressure is to prevent, diagnose, treat and control hypertensive needs.Hypertension is the important risk factor of cardiovascular disease.But patients with hypertension usually arouses attention until there is target organ damage (Target Organ Damage, TOD) the obvious clinical manifestation of Shi Caiyou.So early monitoring and discovery hypertension, and before TOD, be begin treatment, tool is of great significance.Traditional 24 hours blood pressure monitors adopt aeration, service routine Timing measurement and recording blood pressure on the market now.Its shortcoming is that precision is low, disturbs measured, can not obtain continuous measurement.Chinese patent CN1477942A by Singapore's strong money international application is the flat measurement method of blood pressure.It adds a pressure transducer on radial artery, and vascular pressure when flat, is made to sensor pressure etc. and blood vessel pressure.Its shortcoming is to wear accurately, and long-term pressure causes uncomfortable.United States Patent (USP) 6413223 has been invented a kind of volumetric blood signal recording based on light plethysmograph (PPG) and hemodynamic method, yet does not pass through clinically, also there is no practical application.The invention of United States Patent (USP) 5865755, is used electrocardiosignal and the PPG signal record, calculates pulse wave time of advent, PPG waveform and heart rate, further calculating blood pressure.This method based on pulse wave velocity, can only obtain a mean blood pressure or systolic pressure.And, by electrocardiosignal and PPG signal, carry out calculating blood pressure, its principle is unclear, and certainty of measurement can not get guarantee, and therefore, this technology is not really applied yet.
Center arterial pressure (Central aortic pressure) refers to root of ascending aorta blood pressure.In recent years, center arterial pressure has obtained medical profession and has more and more paid attention to, and the hypertension management guidance handbook that the sick association of European hypertension association and heart of Europe combines issue is the independent index using center arterial pressure as blood pressure management.
The existing method of obtaining continuously center arteriotony is divided only for there being wound mode.It adopts conduit to get involved method and directly uses manometry internal blood vessel blood pressure.The method is mainly used in the fields such as first aid field, cardiovascular surgery and intensive care unit(ICU).It has traumaticly accurately, continuously simultaneously, needs professional to operate, can not widespread adoption.
Human body center arteriotony can not non-invasive measurement, and non-invasive methods, mainly by the analysis to physiological signals such as radial artery blood corrugatings, estimates to obtain center arteriotony.United States Patent (USP) 5,265,011 has proposed a kind of general transfer function (GTF) method, by the analysis to big-sample data, estimate to obtain the general transfer function of center arterial pressure-pressure of the radial artery, from the radial artery blood pressure measuring, utilize GTF to estimate to obtain subjects's center arteriotony.The method is adopted by the product SphygmoCor of Australian AtCor Medical company.Similar techniques also comprises United States Patent (USP) 7,628,758 etc.Singapore HealthSTATS has proposed average (the N-Point Moving Average) method of Multipoint movable, and human body radial artery blood corrugating is carried out obtaining human body center arteriotony waveform after N point rolling average processing (1/4th that N is sample rate).Although said method has obtained the checking of a large amount of clinical trials, there is following problem: (1) general transfer function method and Multipoint movable averaging method, all from clinical experience, do not have theory support.(2) all, no matter age, sex, health are how, the transfer function of center arterial pressure-pressure of the radial artery of people is all the same to the supposed premise of these two kinds of methods.This hypothesis has been ignored a fact, and everyone blood vessel parameter is because of age, sex, disease difference difference, and this is bound to reaction in transfer function.The accuracy of these two kinds of methods and resultses necessarily has problem, has also lost the important information of diagnosis.
Chinese patent " a kind of noinvasive center artery measurement method and apparatus " by applicant application, application number: 201210584475, the noinvasive human body center arteriotony measuring method of inventing comprises: the human body artery blood vessel network model based on mechanics of viscous fluids, by the pulse wave signal of the radial artery of measuring and brachial artery and arm pressure value, calculated the method for measured's arteries network model personalizing parameters, calculate the method for ascending aorta-radial artery transfer function, from the radial artery blood corrugating of measuring, calculate the method for center arteriotony waveform.Radial artery and brachial pulse ripple signal gathering unit that arteriotony continuous measurement equipment in noinvasive human body center is worn in wrist by a pulse wave signal processing and analytic unit and form.
Disclosed by the invention is the continuous arteriotony measuring method of noinvasive and equipment, is continuous BP measurement and the monitoring of the human body artery blood vessel network model based on mechanics of viscous fluids.The present invention is according to tremulous pulse network model, provided accurately formula, method and apparatus by pulse wave velocity derivation blood pressure.
There are 2.3 hundred million hypertensive patients in China, and continuous BP measurement is the key technology of prevention, diagnosis, treatment and the control of hypertension.Therefore, the present invention " the continuous arteriotony measuring method of a kind of noinvasive and equipment " is significant.
Summary of the invention
Be different from prior art, the present invention is noinvasive arteriotony method for continuous measuring and equipment, and its technical scheme comprises:
Noinvasive arteriotony method for continuous measuring: the radial artery that use synchronously records and brachial pulse wave train are calculated the method for Artery Vein model parameter, by radial pulse velocity of wave, calculated the method for mean blood pressure, systolic pressure and diastolic pressure, the pulse wave of every section of blood vessel speed proportionate relationship in blood vessel network, calculate ascending aorta to the method for the transfer function of radial artery, and by the method for radial artery blood pressure computer center arteriotony.
Noinvasive arteriotony continuous measurement equipment comprises: pulse wave and motor message collecting unit, comprise the sensor, motion sensor, controller and the attachment device that gather radial artery and brachial pulse ripple, in various motions and attitude situation, gather the motor message of measured's radial artery, brachial pulse ripple signal and forearm, amplify and the measured signal of digitized.
Further comprise: signal processing and analyzing unit, in wired or wireless mode, be connected with motor message collecting unit with pulse wave, real-time synchronization is controlled pulse wave and motor message collecting unit, real-time synchronization acquisition and processing radial artery and brachial pulse ripple signal, by the radial artery collecting and brachial pulse ripple signal, sequence is calculated to tremulous pulse network model parameter, every a pair of radial artery and brachial pulse by continuous acquisition involve corresponding two sensor distance calculating radial artery pulse wave velocity of wave, and and then calculating blood pressure value and waveform, calculate ascending aorta to the transfer function of radial artery also and then computer center's arteriotony and waveform, computer center's arteriotony waveform echo flex point and augmentation index (AIX), according to human body and forearm exercise data, the type of sports of classification trunk and forearm, intensity, attitude and the angle of pitch, process and analyze blood pressure and the electrocardiogram (ECG) data under different motion and attitude, to computer or server uploading data and Calculation results.
Also comprise: computer or server, connect and manage a plurality of noinvasive arteriotony continuous measurement equipment, receive and analyze wearer under different motion state and attitude, the different division of day and night, electrocardio, blood pressure and breath data, calculate a series of indexs such as cardiovascular fitness index, according to wearer's age, sex, medical history, provide report and advisory opinion.
Noinvasive arteriotony continuous measurement equipment also comprises the second embodiment,, with electrocardiosignal and radial artery pulse wave, calculates radial artery pulse wave velocity of wave that is.The noinvasive center blood pressure continuous measurement method and apparatus of this technical scheme, comprise: pulse wave and motor message collecting unit, comprise the sensor, motion sensor, controller and the attachment device that gather radial artery and brachial pulse ripple, in various motions and attitude situation, gather measured's radial artery pulse wave signal and the motor message of forearm, measuring at first, synchro measure radial artery and brachial pulse wave train signal, amplify and the measured signal of digitized.
The second embodiment of noinvasive arteriotony continuous measurement equipment also comprises electrocardio and motor message collecting unit, comprise and measure cardiac electrical electrode, motion sensor, controller and wearable device, gather, amplify electrocardiosignal and be converted to digital signal, this device embeds motion sensor simultaneously, measures motion and the attitude signal of trunk.
The second of noinvasive arteriotony continuous measurement equipment is implemented technical scheme and is also comprised signal processing and analyzing unit, in wired or wireless mode, be connected with motor message collecting unit with motor message collecting unit and electrocardio with pulse wave, real-time synchronization is controlled pulse wave and motor message collecting unit and electrocardio and motor message collecting unit, real-time synchronization acquisition and processing radial artery and brachial pulse ripple and electrocardio and motor message, by the radial artery collecting and brachial pulse ripple signal, sequence is calculated to tremulous pulse network model parameter, every a pair of radial artery pulse wave and electrocardiosignal waveform by continuous measurement, calculating radial pulse wave velocity goes forward side by side and calculating blood pressure and waveform, calculate ascending aorta to the transfer function of radial artery also and then computer center's arteriotony and waveform, computer center's arteriotony waveform echo flex point and augmentation index (AIX), according to human body and forearm exercise data, the type of sports of classification trunk and forearm, intensity, attitude and the angle of pitch, process and analyze blood pressure and the electrocardiogram (ECG) data under different motion and attitude, to computer or server uploading data and Calculation results.
The second embodiment of noinvasive arteriotony continuous measurement equipment also comprises computer or server, connect and manage a plurality of noinvasive arteriotony continuous measurement equipment, receive and analyze wearer under different motion state and attitude, the different division of day and night, electrocardio, blood pressure and breath data, calculate a series of indexs such as cardiovascular fitness index, according to wearer's age, sex, medical history, provide report and advisory opinion.
According to embodiments of the invention, pulse wave and motor message collecting unit are the micro embedded data collecting systems being worn in wrist, it comprises the sensor of measuring radial artery and brachial pulse ripple, motion sensor, preamplifier, analog digital conversion and controller, wherein radial artery sensor is stablized and is contacted by an attachment device assurance sensor and radial artery appearance, be not subject to or be seldom subject to motion and other factors to affect, so that stably measured radial artery pulse wave signal in long-time, synchronously, in the time of continuous measurement brachial pulse ripple, measure the distance between radial artery and the sensor of brachial pulse ripple, the pulse wave signal of surveying through preamplifier, amplify and be converted to digital signal, with this device in motion sensor signal together with, be sent to signal processing and analyzing unit.
According to embodiments of the invention; forearm arteriotony reference value has two kinds of acquisition methods; on the radial artery sensor of the first in pulse wave and motor message collecting unit, pressue device is manually or automatically housed; radial pulse wave sensor is flattened Artery Vein; reach the pressure value that radial pulse wave sensor records and equate with pressure value in blood vessel, it two is with conventional sphygomanometer measurement forearm pressure value.
According to embodiments of the invention the second embodiment, electrocardio and motor message harvester are the micro embedded systems of front that is worn on a pectoral girdle, in order to guarantee electrocardiosignal quality, one of them electrode should be placed in electrocardio breast and lead V3 or V4 position, after the premenstrual storing of electrocardiosignal gathering greatly, be converted to again digital signal, deliver to miniature signal processing apparatus with together with motion sensor signal in this device, motion sensor comprises 3 axis accelerometers, increase gyroscope and magnetometer and can increase trunk and forearm three-dimensional perspective estimated accuracy, brachial pulse wave sensor is only operated by operator or measured oneself when starting, synchro measure radial artery and brachial pulse wave train, for calculating tremulous pulse network parameter.
According to embodiments of the invention the second embodiment, electrocardiogram signal acquisition device, further comprise based on breast impedance measurement method and measure respiratory wave, the modulation current source of constant amplitude is activated to human body, and measure the voltage that electric current produces, obtain the chest impedance of human body, this impedance changes along with human body respiration, thereby releases respiratory wave.
According to embodiments of the invention, signal processing and analyzing unit is a microcomputer, mode with similar wrist-watch is worn on wrist, or wear in loins, it is connected with motor message collecting unit with electrocardio with motor message collecting unit with pulse wave in wired or wireless mode, real-time synchronization is controlled pulse wave signal collecting unit and electrocardio signal collecting unit, real-time synchronization acquisition and processing radial artery and brachial pulse ripple and electrocardio and motor message, calculate tremulous pulse network model parameter, calculate continuously radial artery blood pressure and center arteriotony, analyze motion and the attitude of trunk and forearm, storage data, report is provided, in wired or wireless mode to computer or server uploading data.
According to embodiments of the invention, noinvasive arteriotony method for continuous measuring comprises: set up the arteries model based on mechanics of viscous fluids, use the radial artery and the brachial pulse wave train that synchronously record, calculate Artery Vein model parameter, it is the resistance of blood flow of radial artery, blood flow inertia and vascular compliance, set up this section of radial artery based on arteries model without blood pressure and the pulse velocity of wave relation of the even blood vessel of bifurcated, and calculate mean blood pressure by pulse velocity of wave, the formula of systolic pressure and diastolic pressure, set up the pulse wave speed proportionate relationship of every section of blood vessel in blood vessel network, thereby blood pressure and pulse velocity of wave relation are expanded to any vessels section in tremulous pulse network, comprise that center tremulous pulse is to radial artery, can go out pulse wave velocity from electrocardiogram and radial artery pulse wave waveshape, set up based on arteries network model and calculated ascending aorta to the method for the transfer function of radial artery, and by the formula of radial artery blood pressure computer center arteriotony.
According to embodiments of the invention, signal processing and analyzing unit obtains electrocardiogram (ECG) data and respiratory wave data from electrocardio and motor message collecting unit, it is carried out filtering, removes baseline drift, electrocardiosignal is extracted QRS ripple, ST section, detects anomalous ecg, calculated heart rate, heart rate variability degree.
According to embodiments of the invention, signal processing and analyzing unit obtains trunk motor message from electrocardio and motor message collecting unit, comprise accelerometer signal, gyroscope and magnetometer signals, according to one group of signal wherein, or merge to organize signals more, infer human body attitude and type of sports, comprise: lie, sit, stand, walk, run, fall, sit up, lie down, stand, sit down, and the cadence when walking and running, calculate the angle of pitch and the attitude of trunk, from the forearm exercise data of pulse wave and the acquisition of motor message collecting unit, analyze the motion and standstill state of forearm, calculate the angle of pitch and the attitude of forearm.
According to embodiments of the invention, the radial artery that processing collects and brachial pulse ripple signal are to sequence, find out suitable data point sequence pair, list parameter matrix and observing matrix, use least-squares algorithm, obtain tremulous pulse network model parameter, comprise radial artery blood flow resistance, blood flow inertia and vascular compliance.
According to embodiments of the invention, every a pair of radial artery and brachial pulse by continuous measurement involve corresponding two sensor distance calculating radial pulse velocity of wave propagation, or by every a pair of radial artery pulse wave and the electrocardiosignal waveform of continuous measurement, computer center's tremulous pulse is to the pulse wave the mean propagation velocity of radial artery, again according to the proportionate relationship of the pulse wave velocity between tremulous pulse network medium vessels, obtain the pulse wave velocity of radial artery, according to the relation formula of pulse wave velocity and blood pressure, calculate radial artery blood pressure systolic pressure and diastolic pressure and waveform, according to human body artery blood vessel network model, calculate ascending aorta to the transfer function of radial artery, and and then computer center's arteriotony wave mode.
According to embodiments of the invention, type of sports, intensity, attitude and the pitch angle data of the tremulous pulse network model parameter going out according to measurements and calculations, radial artery and center tremulous pulse continuous blood pressure and waveform, trunk and forearm, and time tag, analyze and show radial artery and center arteriotony in time, and the variation of motion and attitude, calculate and show atherogenic index, cardiorespiratory system health index, center arteriotony waveform echo flex point, augmentation index (AIX), as the diagnosis basis of hypertension.
According to embodiments of the invention, according to human body and forearm motion and attitude type, merge blood pressure, electrocardio, breath signal and they with the variation of division of day and night and motion, calculate many organs variability parameter of wearer, as its cardiorespiratory system health index, characterize this wearer's health status, predict possible disease.
According to embodiments of the invention, each continuous arteriotony measurement device can independent operating, also can connect with computer or server by wireless or wired (as USB), the data that measurements and calculations are gone out, and the immediate status of continuous arteriotony measurement device, as battery levels, pulse wave and electrocardio sample rate, the duty of each unit and self-detection result, upload to computer or server, computer or server connect and manage a plurality of noinvasive arteriotony continuous measurement equipment, accept and analyze wearer under different motion state and attitude, the different division of day and night, electrocardio, breathe and blood pressure data, according to wearer's age, sex, medical history, comprehensive report is provided, to unique individual, analyze and follow the tracks of health status and the state of an illness, to all personnel, research cardiorespiratory system health and the generation of disease to different crowd, development, control, rehabilitation is followed the tracks of and is furtherd investigate.
Accompanying drawing explanation
The system block diagram of Fig. 1, the continuous arteriotony measuring method of noinvasive and equipment;
The system of Fig. 2, the continuous arteriotony measuring method of noinvasive and equipment forms and wearing mode schematic diagram;
The system block diagram of Fig. 3, the continuous arteriotony measuring method of noinvasive and equipment the second embodiment;
System second embodiment of Fig. 4, the continuous arteriotony measuring method of noinvasive and equipment forms and wearing mode schematic diagram;
Fig. 5, left radial artery blood vessel equivalent circuit;
When Fig. 6, pulse wave transmission time calculate, pulse wave reference point chooses;
Fig. 7, three coordinate axess and the human body angle of pitch that are worn on the acceleration transducer of front calculate.
The specific embodiment
Below in conjunction with accompanying drawing, the present invention is described in detail, be to be noted that described embodiment is only intended to be convenient to the understanding of the present invention, and it is not played to any restriction effect.
As shown in Figure 1, its system formation and wearing mode schematic diagram are as Fig. 2 for the system block diagram of the continuous arteriotony measuring method of noinvasive and equipment.As shown in Figure 3, its system formation and wearing mode schematic diagram are as Fig. 4 for the second embodiment system block diagram of the continuous arteriotony measuring method of noinvasive and equipment.The continuous arteriotony measuring method of noinvasive and the basic scheme of equipment and the difference of the second embodiment are only, basic scheme with the radial artery of continuous measurement and brachial pulse ripple to calculating radial artery pulse wave velocity of wave, the second embodiment with the radial artery pulse wave of continuous measurement and electrocardiosignal to calculating radial artery pulse wave velocity of wave.For the convenience of narrating, we narrate the second embodiment by emphasis, and basic scheme does not just comprise collection, processing and the applying portion of electrocardio and motor message.
The present invention is a kind of Wearable real-time continuous arteriotony, electrocardio and respiratory monitoring system hardware and software based on health sensing network.Whole continuous arteriotony measuring method and equipment are comprised of the continuous arteriotony measurement device 100 of Wearable and computer/server 200.Continuously arteriotony measurement device 100 is comprised of pulse wave and motor message collecting unit 110, electrocardio and motor message collecting unit 120 and signal processing and analyzing unit 130.
Pulse wave and motor message collecting unit 110 are placed on pulse wave sensor attachment device, comprise controller, preamplifier, forearm motion sensor 113, radial pulse wave sensor 111, brachial pulse wave sensor 112.Forearm motion sensor is comprised of a three axis accelerometer, and this acceleration signal is comprised of two parts, and the one, the earth acceleration of gravity, its component on three coordinate axess of acceleration transducer can be calculated forearm with respect to the angle of pitch of ground level.The 2nd, sensor itself, is also the acceleration of forearm itself, and it represents the kinestate of forearm.In acceleration signal, acceleration of gravity and acceleration own is separated, and the calculating of forearm kinestate and the angle of pitch can carry out in pulse wave and motor message collecting unit 110, also can degree of will speed up signal delivers in signal processing and analyzing unit 130 and carries out.Pulse wave and motor message collecting unit 110 gather pulse wave signal by radial pulse wave sensor 111 and brachial pulse wave sensor 112, after amplification and digitized, deliver to miniature signal processing and analyzing unit 130.Radial pulse wave sensor 111 is acquired signal continuously, for guaranteeing the stability of signals collecting, by an attachment device, sensor is fastened in wrist, guarantees sensor alignment position of radial artery.Meanwhile, in order to obtain radial artery blood pressure, sensor is equipped with the automaton that sensor is pressed to radial artery simultaneously.When radial artery is flattened, obtain now radial artery blood corrugating, as the reference blood pressure of continuous measurement.Such measuring operation only needs once, by operator or measured, is operated.
Brachial pulse wave sensor 112, when gathering pulse wave, is placed brachial pulse wave sensor by operator or measured and is completed, simultaneously the also distance between taking a radial pulse wave sensor 111 and brachial pulse wave sensor 112.
Pulse wave sensor can be selected the pressure transducer of various materials, comprises deformation, varistor, polyvinylidene fluoride etc., also can adopt based on optics and electromagnetic sensor.Because the best measurement position of radial artery is less, the measurement error of bringing in order to reduce the minute movement of sensing station, also can adopt sensor array.
Pulse wave and motor message collecting unit 110 synchronous acquisition radial arterys and brachial pulse ripple signal, and these signals are assessed, in order to avoid because sensor placement is improper or other reason causes distorted signals, affect measurement result.When pulse wave and the motor message collecting unit 110 acquisition satisfactory radial arterys of some quality and brachial pulse ripple signal sequence, pulse wave and motor message collecting unit 110 have provided the signal that brachial pulse ripple gathers, and operator can stop the collection of brachial pulse ripple.
Electrocardio and motor message collecting unit 120 comprise that controller, preamplifier, motion sensor 122 and electrocardioelectrode 121 form.It gathers electrocardiosignal by electrocardioelectrode 121 according to conventional electrode of dynamic electrocardiogram method of attachment, as required, the number that leads can from 1 to 12 not etc.Due to what use in blood pressure measurement, be that main breast is led, therefore, one of them electrode should be placed in chest lead point V3 or V4.The measurement of breast impedance and electrocardio share two electrodes.The modulation current source of constant amplitude is passed through to these two electrode excitations to human body, measure the voltage that electric current produces, obtain the chest impedance of human body, this impedance changes along with human body respiration, thereby releases respiratory wave.This impedance also changes along with cardiac ejection, therefore, on definite cardiac ejection point, has the certain significance.Electrocardio and motor message collecting unit 120 are fixed on front or loins with pectoral girdle or the mode of pasting.Motion sensor wherein comprises three axis accelerometer, gyroscope and magnetometer.Optionally can adopt wherein part or all of sensor.Analyze attitude and type of sports that 3-axis acceleration sensor data can obtain human body: comprising: lie, sit, stand, walk, run, fall, sit up, lie down, stand, sit down, and the cadence when walking and running.Add gyroscope to obtain comparatively exactly three-dimensional perspective, add magnetometer can obtain azimuth.
Signal processing and analyzing unit 130, from pulse wave and motor message collecting unit 110 and electrocardio and motor message collecting unit 120 reception signals, is monitored simultaneously, is controlled and the synchronously operation of these two unit.Signal processing and analyzing unit 130 operates on microcomputer, and this microcomputer can be worn in wrist as wrist-watch.Between signal processing and analyzing unit 130 and pulse wave and motor message collecting unit 110 and electrocardio and motor message collecting unit 120, can adopt wireless or wired connection mode.
Signal processing and analyzing unit 130 comprises pulse wave and electrocardiogram processing module 131, tremulous pulse network model computation module 132, pulse velocity of wave and blood pressure computing module 133, motion and posture analysis module 134, storage and reporting modules 135, and local data base 136.It processes and analyzes radial artery pulse wave and brachial pulse ripple, calculates measured's tremulous pulse network parameter, processes and analyze electrocardiosignal and radial artery pulse wave, calculates pulse wave velocity, calculates radial artery blood pressure, and center arteriotony.
Each continuous arteriotony measurement device can independent operating, also can connect with computer or server 200 by wireless or wired (as USB).Computer or server 200 will provide system monitoring and further data analysis to this continuous arteriotony measurement device, for wearer provides health consultation and service.
Introduce in detail embodiments of the invention below:
1, the vascular pattern based on mechanics of viscous fluids
From radial artery to cardio-arterial human vas network packet containing ascending aorta, brachial artery, radial artery and the several parts of periphery blood capillary, wherein, except Peripheral arteries, other several sections of tremulous pulsies meet same big-and-middle arteries model, just parameter is different.So we will set up two kinds of models, be divided into big-and-middle artery model, and periphery capillary artery model, then by cascade, form required blood vessel network.Chinese patent " a kind of noinvasive center artery measurement method and apparatus ", application number: 201210584475, use mechanics of viscous fluids, derived whole human body artery network and equation thereof.Use its result, we can use radial artery and the brachial pulse wave train synchronously recording, and calculate Artery Vein model parameter, as follows:
With reference to the left radial artery blood vessel equivalent circuit of Fig. 5, wherein
resistance of blood flow for radial artery;
blood flow inertia for radial artery;
vascular compliance for radial artery;
for the Peripheral resistance that represents little arteriole blood vessel network being connected with radial artery;
blood pressure for radial artery top;
blood pressure for radial artery end;
blood flow for the inflow of radial artery top;
blood flow for the outflow of radial artery end.Model parameter
,
,
,
method of estimation as follows.
(1) left radial artery vascular pattern Peripheral resistance is estimated
Blood of human body finally flows to the little arteriole blood vessel network of multistage arteries institute cascade.The blood flow that flows into little arteriole blood vessel network by above-mentioned tremulous pulse is designated as
.By human body total peripheral resistance
be expressed as follows:
Then according to blood vessel parameter discussed above, and the proportionate relationship of model parameter, obtain the Peripheral resistance of left radial artery vascular pattern institute cascade
,
(2) Artery Vein model parameter,, estimate
According to radial artery blood tube model, we can obtain following mathematic(al) representation:
Arrangement formula (3.6)
Wherein, parameter
,
,
can estimate to obtain by ordinary least square algorithm.
(3) observing matrix of parameter estimation
From left radial artery vascular pattern;
, the blood flow of left radial artery end and blood pressure are linear.Blood flow curve can by pressure transducer leftward the radial artery of wrist measure, but absolute value position needs calibration to obtain.Computing formula in conjunction with left radial artery blood flow value
Calibration by the result of above formula for radial artery blood flow quantity curve, can obtain left radial artery blood flow
.
Meanwhile, the blood pressure curve at left radial artery top can be measured at left arm ancon brachial artery end by pressure transducer.Further, the forearm systolic pressure and the diastolic pressure that by mercury column method, record are calibrated above-mentioned pressure curve, or by the automatic pressurizing device on radial pulse wave sensor, use flat method principle, synchronously record radial artery blood corrugating, obtain left radial artery blood pressure
.
Finally, can obtain following observing matrix:
Be defined as follows parameter matrix:
Obtain the relation equation of parameter matrix and observing matrix
Wherein,
for observation error.If had
inferior observation, also, from m sampling number certificate of pulse wave and motion collecting unit 110 synchronous acquisition radial arterys and brachial pulse ripple signal waveform, makes
, have:
Wherein:
The thought of least-squares algorithm is found one exactly
estimated value
, make each observation
with by
estimate
the quadratic sum of difference minimum.
least-squares estimation
for:
Solve an equation and obtain parameter
,
,
expression formula.
, the monitoring of blood pressure based on radial artery blood tube model
(1) the radial artery blood pressure based on vascular pattern and pulse velocity of wave relation
Pulse velocity of wave is determined by the density of arterial wall mechanical characteristic (viscosity and elasticity), geometric features (diameter and pipe thickness) and blood.Because elastic pipeline (tremulous pulse) inner blood is incompressible liquid, energy delivery is mainly conducted by blood vessel wall, so vascular function is the principal element that affects pulse velocity of wave.Their relation can be used Moens-Korteweg the Representation Equation:
In formula,
pulse wave velocity,
the elastic modelling quantity of blood vessel wall,
density of blood,
blood vessel wall thickness,
it is vessel diameter.Have again the relation between blood pressure and vessel wall elasticity modulus as follows:
In formula,
the elastic modelling quantity of pressure while being zero,
blood pressure (mmHg),
be a parameter that characterizes blood vessel feature, numerical range is about 0.016～0.018(mmHg).
By two formulas above, can derive radial artery mean blood pressure
with radial pulse velocity of wave
between relation as follows:
Wherein,
for Artery Vein characteristic parameter,
for radial artery blood bore,
for radial artery density of blood,
for radial artery blood pipe thickness,
elastic modelling quantity for radial artery blood tube wall.Above-mentioned parameter is personalizing parameters, and its value varies with each individual.
(2) the consecutive mean blood pressure at radial artery place is estimated
For length, be
artery Vein
, pulse wave velocity can be expressed as:
In formula,
for the time of pulse wave in radial artery propagation.Further can obtain
According to the vascular compliance of radial artery blood tube model
with blood flow inertia
definition we can transform as follows formula:
Above-mentioned formula is the radial artery continuous blood pressure estimation formulas based on vascular pattern: we can be according to the passing time of pulse wave in radial artery by shooting
estimate to obtain continuous radial artery mean blood pressure
.Wherein, vascular compliance and blood flow inertia are known.Blood vessel characteristic parameter
can be by one group of radial artery mean blood pressure
with corresponding pulse wave passing time
calibration obtains.
(3) systolic pressure at radial artery place and diastolic pressure are estimated
At diastole, arterial valve is closed, and the blood flow that flows into Artery Vein is approximately zero,
.Relaxing period (
,
for relaxing period initial time,
for relaxing period finish time), we have:
Wherein,
=
.Separating the radial artery end blood pressure that above-mentioned ordinary differential equation obtains relaxing period is:
Wherein,
blood pressure (being systolic pressure) for relaxing period initial time radial artery end.And then can know that radial artery end diastolic pressure is:
For each, clap pulse wave, we are the passing time at radial artery according to pulse wave
, calculate the mean blood pressure of this pulse wave
.Again because pulse wave mean pressure
with systolic pressure
, diastolic pressure
there is following relation:
Wherein
for pulse waveform coefficient, can be calculated by pulse waveform.Above-mentioned two formula obtain the systolic pressure computing formula of pulse wave by shooting:
And then diastolic pressure computing formula is:
3, the pulse wave of every section of blood vessel speed proportionate relationship in blood vessel network
The formula by pulse wave propagate time or pulse velocity of wave derivation blood pressure above, is only applicable to one section of even blood vessel without bifurcated, as radial artery.But this section of blood vessel is shorter, the bad control of its measurement error, and measure to get up to have any problem.Below, we are given in human body artery blood vessel network, and the pulse velocity of wave in known any one section of blood vessel, can derive the pulse velocity of wave of radial artery, and then calculate pressure value.Ascending aorta-radial artery pulse wave passing time of take is below example, provides formula:
Pulse velocity of wave is determined by the density of arterial wall mechanical characteristic (viscosity and elasticity), geometric features (diameter and pipe thickness) and blood.Because elastic pipeline (tremulous pulse) inner blood is incompressible liquid, energy delivery is mainly conducted by blood vessel wall, so vascular function is the principal element that affects pulse velocity of wave.Their relation can be used Moens-Korteweg the Representation Equation, and obtains:
Can obtain thus pulse wave passing time in any vessels section is:
Wherein
for vessel segment numbering.Ascending aorta-radial artery pulse wave passing time
for pulse wave ascending aorta (
), aortic arch I(
), aortic arch II(
), left subclavian artery I(
), left subclavian artery II(
) and radial artery (
) passing time sum, and then we can obtain
the derivation of equation be:
further, formula is adjusted to known ascending aorta-radial artery pulse wave passing time
prerequisite under, we can calculate the passing time of pulse wave in radial artery and are:
now suppose the density of blood of different blood vessel in formula
, blood vessel characteristic parameter
and blood pressure
identical, so above-mentioned formula can be reduced to:
wherein
,
,
,
for blood vessel
blood vessel parameter ratio, by document Westerhof, N., et al., Analog studies of the human systemic arterial tree. Journal of biomechanics, 1969. 2 (2): p. 121-134, and Wang, J.J. and K.H. Parker, Wave propagation in a model of the arterial circulation. Journal of biomechanics, 2004. 37 (4): p. 457-470 can obtain.
A large use that obtains the proportionate relationship of these pulse velocities of wave is exactly that we can be by the pulse velocity of wave after the multistage blood vessel cascade recording, the pulse velocity of wave parameter of the concrete one section of blood vessel of deriving.Such as we use Electrocardiographic R ripple (or cardiac impedance waveform), pulse wave with radial artery end, measure pulse velocity of wave, it is the average pulse velocity of wave of center tremulous pulse, brachial artery, three sections of blood vessel cascades of radial artery, and the pulse velocity of wave of concrete every section of blood vessel is different, so directly use the blood pressure of this mean value calculation, be inappropriate.And passing through pulse velocity of wave in the proportionate relationship of these three sections of blood vessels, we just can specifically calculate the pulse velocity of wave of every section of blood vessel, and remove with it the pressure value of deriving.And use the derive pulse velocity of wave of a certain section of average pulse velocity of wave, than the pulse velocity of wave of this section of blood vessel of direct measurement, more easily implement, because the initial segment of most of blood vessel and end are often not easy to measure pulse wave or signal simultaneously.Such as, the end tremulous pulse of radial artery is easy to measure, and the interference bringing is also less, but the pulse wave of the initial segment of radial artery is not easy to measure.
, the transfer function based on arteries network model and center arterial pressure estimation
The transfer function of the blood pressure between the arbitrary node in human body artery blood vessel network model is designated as:
(wherein
represent in model
the blood pressure of number node).According to our network model, to its electric network equivalence, calculate its voltage transfering function and can obtain transfer function.Especially, can obtain blood pressure with the top of ascending aorta model (
) be input, with the blood pressure of the end of radial artery model (
) be the transfer function of output
.
Radial artery blood corrugating
with center arteriotony waveform
between relation can be in frequency domain transfer function
(
) represent.Its relational expression is expressed as follows:
Thereby center arteriotony estimation formulas is as follows:
5, the motion of human body and forearm and attitude detection
The human body center arteriotony continuous measurement equipment that noinvasive need not be inflated, in continuous measurement human upper limb blood pressure, obtains center arteriotony waveform continuously.Meanwhile, we also obtain electrocardiosignal, breath signal, and the motion of health and attitude information, comprise multidate information and the angle of pitch information of forearm.
In the type of sports that will classify at us, can be divided into three major types: lie, sit and stand as static type of sports, standing up, lie down, stand up and sit down as transient motion type, walking and run as dynamic motion type.For these three kinds of type of sports, adopted signal amplitude area, accelerometer axes orientation and three features of accumulated change amount foundation as classification.Signal amplitude area reflects the severe degree of current human motion according to the size of human motion acceleration fluctuation area, be defined as:
Accumulated change amount is for describing the feature of transient motion type, and the proposition of this feature is to make based on human body the variation that transient motion action brief acceleration has persistence, and the larger feature of amplitude changing.At human body, make in the process of transient motion action, attitude often changes, and because the transformation of attitude makes the accekeration after the decomposition of gravitational acceleration component on three axles of accelerometer present the trend that continues to change (increase or reduce) to some directions within certain persistent period.
For feature being corresponded to some concrete type of sports, first need data to carry out segmentation.The persistent period that human motion is the shortest is depended at split time interval, and human motion generally all can more than the time complete at 1 second, so split time window position 1 second, i.e. 100 sample points under the sample rate of 100Hz.After completing data sectional, will extract this three features to the acceleration information of each data segment.Follow-up classification is classified and is determined the kinestate of the human body that data segment was corresponding at that time according to this data segment characteristic of correspondence.
Because accelerometer can be measured acceleration of gravity, when human body attitude changes, by acceleration of gravity being decomposed to each axle of accelerometer and then can calculating the angle of each axle and gravity direction, according to the orientation of each axle, just can identify the attitude of human body.Will speed up the placement location of meter and three axles of the accelerometer when human body is stood towards as shown in Figure 7.During attitude at human body in standing, x axle points to the health back side, and it is contrary with gravity direction that y axle points to right side of body z axle, points to head.When human body attitude is different, for example to stand and lie low, while standing, z axle is almost contrary with gravity direction, that record is about 180 degree with angle gravity direction; While lying low, z axle is vertical with gravity direction, that record is about 90 degree with angle gravity direction.Because the orientation of three axles of different attitude accelerometers is also different, so accelerometer axes orientation can be used as the feature of distinguishing human body attitude.The orientation of accelerometer axes is often determined at the decomposed component of each axle according to acceleration of gravity, can measure thus the angle of pitch of body trunk and forearm, is also attitude.
, noinvasive arteriotony continuous measurement step
1) whole equipment is worn according to Fig. 2.Adjust radial artery pulse wave sensing station, make it aim at radial artery, obtain the rich waveform of stable radial artery.
2) brachial pulse wave sensor is placed in to radial artery initiating terminal (being also brachial artery end), obtains satisfied a string pulse wave signal.Meanwhile, measure the distance of radial artery initiating terminal and end, and measured value input signal is processed and analytic unit 130.
3) start the automatic pressure adjusting device on radial artery sensor or manually adjust, until Artery Vein is flattened, obtaining radial artery blood corrugating.Or use other blood pressure measuring method, obtain forearm pressure value, and input signal is processed and analytic unit 130.The pressure value that one of these two kinds of methods record, calculates and the calculating of radial artery continuous blood pressure for tremulous pulse network model parameter below.
4) complete after aforesaid operations, system will forward continuous measurement pattern to, automatically carry out following operation;
A) pulse wave and 131 pairs of pulse waves of electrocardiogram processing and ECG signal are carried out Filtering Processing, obtain brachial artery and radial artery pulse wave signal to sequence, and continuous electrocardiogram and radial artery waveshape signal, be sent to respectively the calculating 132 of tremulous pulse network model and pulse velocity of wave and blood pressure and calculate 133, and data are stored in local data base 136 simultaneously.
B) tremulous pulse network model calculates 132 according to being processed 131 brachial artery and radial artery pulse wave signal by pulse wave and electrocardiogram to sequence, use method in above-mentioned " vascular pattern based on mechanics of viscous fluids " and formula to calculate the model parameter of measured's left radial artery vascular pattern, comprise vascular compliance, blood flow inertia, peripheral vascular resistance and resistance of blood flow.And model parameter is delivered to pulse velocity of wave and blood pressure calculating 133.Vascular pattern parameter is deposited in local data base 136 simultaneously.
C) pulse velocity of wave and blood pressure calculate 133 and use pulse wave and electrocardiogram processing 131 continuous ECG of sending here and radial artery pulse wave waveshape signal pair, use method and formula in above-mentioned " pulse wave of every section of blood vessel speed proportionate relationship in blood vessel network " to calculate radial pulse velocity of wave.Further use tremulous pulse network model to calculate the 132 tremulous pulse network model parameters of sending here, with method and the formula in above-mentioned " monitoring of blood pressure based on radial artery blood tube model ", calculate radial artery blood pressure value and waveform, and further use method and the formula in above-mentioned " estimation of the transfer function based on arteries network model and center arterial pressure ", computer center's arteriotony and waveform.Result of calculation is sent to local data base 136.
D) if adopt the basic scheme pulse velocity of wave of the continuous arteriotony measuring method of noinvasive and equipment and blood pressure to calculate the 133 use pulse waves processing 131 continuous brachial artery of sending here and radial artery pulse wave waveshape signals pair, distance in use Fig. 6 between method and the radial artery sensor recording and brachial artery sensor, measuring and calculating radial artery pulse wave velocity of wave, is used method and formula in above-mentioned " pulse wave of every section of blood vessel speed proportionate relationship in blood vessel network " to calculate radial pulse velocity of wave.Further use tremulous pulse network model to calculate the 132 tremulous pulse network model parameters of sending here, with method and the formula in above-mentioned " monitoring of blood pressure based on radial artery blood tube model ", calculate radial artery blood pressure value and waveform, and further use method and the formula in above-mentioned " estimation of the transfer function based on arteries network model and center arterial pressure ", computer center's arteriotony and waveform.Result of calculation is sent to local data base 136.
E) motion and posture analysis 134 receive respectively forearm motion sensor (being mainly acceleration transducer) signal from pulse wave and motion collecting unit 110 and trunk motion sensor (the being mainly acceleration transducer) signal of electrocardio and motion collecting unit 120, according to the method in above-mentioned " motion of human body and forearm and attitude detection ", type of sports, intensity, attitude and the angle of pitch of classification trunk and forearm.Result is sent to local data base 136.
F) type of sports, intensity, attitude and the pitch angle data of tremulous pulse network model parameter, radial artery and center arteriotony and waveform, trunk and forearm are read in storage and report 135 from local data base 136.According to time tag, draw and show radial artery and center arteriotony in time, and the change curve of motion and attitude, calculating and demonstration atherogenic index, the health index of cardiorespiratory system, center arteriotony waveform parameter, etc.
5) each continuous arteriotony measurement device 100 can independent operating, also can connect with computer or server 200 by wireless or wired (as USB mouth), by the data in local data base 136, and the immediate status of continuous arteriotony measurement device 100, as duty and the self-detection result of battery levels, pulse wave and electrocardio sample rate, each unit, upload to computer or server 200.Computer or server 200 will provide system monitoring and further data analysis to continuous arteriotony measurement device 100, for wearer provides health consultation and service.
, daily life, work and centre of motion pulmonary system health index
Research and medical experiment prove, cardiorespiratory system is a dynamical system, and it is controlled by autonomic nerve, and its function is exactly the variation of health along with people, motion, external condition etc. and regulate adaptively its heart beating, blood supply, oxygen supply.Medical workers also find, many serious cardiovascular disease, as coronary heart disease, apoplexy, all have high correlation with heart rate variability degree, breathing, blood pressure etc.Crowd for specific age, sex, as by the state of cardiorespiratory system (normal, coronary heart disease, arrhythmia, myocardial ischemia ...) and electrocardio of measuring, breathing, blood pressure etc. with Bayesian network, represent, can obtain, in the situation of given factor and measured value, the rear of cardiorespiratory system state is directly proportional to the product of the likelihood ratio of electrocardio, breathing, three measurements of blood pressure because of probability.That is to say, if select different ages and the crowd of sex, when measuring electrocardio, breathing, blood pressure, measure its motion, and consider the division of day and night; After again the electrocardio recording, breathing, blood pressure and motor message being processed, obtain the likelihood ratio of some specified disease under all factor conditions.Had these likelihood ratios, one group of measurement for someone, just can calculate the probability that he suffers from certain disease.That is to say, these likelihood ratios can be used as the index of the health index of cardiorespiratory system and the early warning of some disease and diagnosis.The method of asking for the health index of cardiorespiratory system below:
Motion segmentation.The electrocardio obtaining, breathing and blood pressure data be through the first step after pretreatment, is to take the further processing that type of sports, intensity and attitude be sight condition, i.e. motion segmentation.The necessity of this processing is very obvious: cardiorespiratory system is subject to motion effects very large, and under different motions, heart rate, breathing rate and blood pressure are also different; The unexpected variation of people's attitude can cause the sudden change of measurement result, and this,, not only because the variation of attitude can cause the reaction of cardiorespiratory system, also produces and measure noise and error because of the variation of position between gauge and health; Moreover even all under static state, pressure transducer and heart relative position differ, its blood pressure measurement is also different.
As previously mentioned, the type of sports that we divided has: lie (lie low, left side, right side), sit, stand, walk (cadence), run (cadence); Motion change has: fall, sit up, stand up, sit down, lie down, accelerate, slow down; And pressure transducer is with respect to the height of heart.First, with type of sports and motion change, carry out electrocardio, breathing and the blood pressure data stream of divided ownership, obtain two large class data sequence: a class is the data sequence moving while changing, as the significant data source of disease that some abrupt motion causes.Another kind of is with stationary posture or with the data sequence of electrocardio, breathing and blood pressure under constant intensity motion sight.
Feature extraction.Electrocardio under special exercise and attitude, breathing and blood pressure data sequence also need to do further feature extraction, to obtain the characteristic measure with direct and obvious medical significance.For example, Electrocardiographic medical significance is not obvious, and we therefrom extract RR gap (heart rate) sequence and ST section sequence, and they characterize the dynamic characteristic of heart, and relevant with arrhythmia and myocardial ischemia respectively.
Because time series is driven by a plurality of factors, and be non-linear and non-stationary, especially individual in motion or when physically different, in order to propose different variation characteristics, sequence signal is done to seasonal effect in time series resolution process, be decomposed into three parts: trend (Trend), exceptional value (Outlier) and fluctuation (Fluctuation) component.
Physiological period.Cardiovascular system changed and represents a kind of physiological period with the division of day and night within one day.Typical example is that hyperpietic's blood pressure of a day is very valuable to diagnosis, medication.For this reason, we take is every two hours the method in a division of day and night, obtains 24 hours characteristic measure vector arrays:
[Fecg, Fresp, Fbp] (t, act), and t=1,2,3 ... 12, act=(attitude, motion) }
Feature in above formula in bracket is followed successively by electrocardio, breathing, blood pressure feature, comprises heart rate variability degree, ECG ST section, breathing rate degree of variation, blood pressure, Variation of Blood Pressure degree etc.To someone, these features at a time measured value under occasion, certain kinestate, certain quantity of motion have formed a character array, after obtaining the likelihood ratio of normal value and disease, become the index of judgement health cardiorespiratory system health, and the early warning of cardiorespiratory system disease, therapeutic effect monitoring, the important indicator of leaving hospital and observing and following up a case by regular visits to.
Claims (15)
1. noinvasive arteriotony method for continuous measuring and an equipment, comprising:
The radial artery that use synchronously records and brachial pulse wave train are calculated the method for Artery Vein model parameter, by radial pulse velocity of wave, calculated the method for mean blood pressure, systolic pressure and diastolic pressure, the pulse wave of every section of blood vessel speed proportionate relationship in blood vessel network, calculate ascending aorta to the method for the transfer function of radial artery, and by the method for radial artery blood pressure computer center arteriotony;
Pulse wave and motor message collecting unit, comprise the sensor, motion sensor, controller and the attachment device that gather radial artery and brachial pulse ripple, in various motions and attitude situation, gather the motor message of measured's radial artery, brachial pulse ripple signal and forearm, amplify and the measured signal of digitized;
Signal processing and analyzing unit, in wired or wireless mode, be connected with motor message collecting unit with pulse wave, real-time synchronization is controlled pulse wave and motor message collecting unit, real-time synchronization acquisition and processing radial artery and brachial pulse ripple signal, by the radial artery collecting and brachial pulse ripple signal, sequence is calculated to tremulous pulse network model parameter, every a pair of radial artery and brachial pulse by continuous acquisition involve corresponding two sensor distance calculating radial artery pulse wave velocity of wave, and and then calculating blood pressure value and waveform, calculate ascending aorta to the transfer function of radial artery also and then computer center's arteriotony and waveform, computer center's arteriotony waveform echo flex point and augmentation index (AIX), according to human body and forearm exercise data, the type of sports of classification trunk and forearm, intensity, attitude and the angle of pitch, process and analyze blood pressure and the electrocardiogram (ECG) data under different motion and attitude, to computer or server uploading data and Calculation results,
Computer or server, connect and manage a plurality of noinvasive arteriotony continuous measurement equipment, receive and analyze wearer under different motion state and attitude, the different division of day and night, electrocardio, blood pressure and breath data, calculate a series of indexs such as cardiovascular fitness index, according to wearer's age, sex, medical history, provide report and advisory opinion.
2. noinvasive arteriotony method for continuous measuring according to claim 1 and equipment, it is characterized in that: comprise its second embodiment, be that electrocardiosignal and radial artery pulse wave calculate radial artery pulse wave velocity of wave, noinvasive arteriotony method for continuous measuring and equipment under this second embodiment, comprising:
Pulse wave and motor message collecting unit, comprise the sensor, motion sensor, controller and the attachment device that gather radial artery and brachial pulse ripple, in various motions and attitude situation, gather measured's radial artery pulse wave signal and the motor message of forearm, measuring at first, synchro measure radial artery and brachial pulse wave train signal, amplify and the measured signal of digitized;
Electrocardio and motor message collecting unit, comprise and measure cardiac electrical electrode, motion sensor, controller and wearable device, gather, amplify electrocardiosignal and be converted to digital signal, this device embeds motion sensor simultaneously, measures motion and the attitude signal of trunk;
Signal processing and analyzing unit, in wired or wireless mode, be connected with motor message collecting unit with motor message collecting unit and electrocardio with pulse wave, real-time synchronization is controlled pulse wave and motor message collecting unit and electrocardio and motor message collecting unit, real-time synchronization acquisition and processing radial artery and brachial pulse ripple and electrocardio and motor message, by the radial artery collecting and brachial pulse ripple signal, sequence is calculated to tremulous pulse network model parameter, every a pair of radial artery pulse wave and electrocardiosignal waveform by continuous measurement, calculating radial pulse wave velocity goes forward side by side and calculating blood pressure and waveform, calculate ascending aorta to the transfer function of radial artery also and then computer center's arteriotony and waveform, computer center's arteriotony waveform echo flex point and augmentation index (AIX), according to human body and forearm exercise data, the type of sports of classification trunk and forearm, intensity, attitude and the angle of pitch, process and analyze blood pressure and the electrocardiogram (ECG) data under different motion and attitude, to computer or server uploading data and Calculation results,
Computer or server, connect and manage a plurality of noinvasive arteriotony continuous measurement equipment, receive and analyze wearer under different motion state and attitude, the different division of day and night, electrocardio, blood pressure and breath data, calculate a series of indexs such as cardiovascular fitness index, according to wearer's age, sex, medical history, provide report and advisory opinion.
3. noinvasive arteriotony method for continuous measuring according to claim 1 and equipment, it is characterized in that: pulse wave and motor message collecting unit are the micro embedded data collecting systems being worn in wrist, it comprises the sensor of measuring radial artery and brachial pulse ripple, motion sensor, preamplifier, analog digital conversion and controller, wherein radial artery sensor is stablized and is contacted by an attachment device assurance sensor and radial artery appearance, be not subject to or be seldom subject to motion and other factors to affect, so that stably measured radial artery pulse wave signal in long-time, synchronously, in the time of continuous measurement brachial pulse ripple, measure the distance between radial artery and the sensor of brachial pulse ripple, the pulse wave signal of surveying through preamplifier, amplify and be converted to digital signal, with this device in motion sensor signal together with, be sent to signal processing and analyzing unit.
4. noinvasive arteriotony method for continuous measuring according to claim 1 and equipment, it is characterized in that: forearm arteriotony reference value has two kinds of acquisition methods, on the radial artery sensor of the first in pulse wave and motor message collecting unit, pressue device is manually or automatically housed, radial pulse wave sensor is flattened Artery Vein, reach the pressure value that radial pulse wave sensor records and equate with pressure value in blood vessel, it two is with conventional sphygomanometer measurement forearm pressure value.
5. noinvasive arteriotony method for continuous measuring according to claim 2 and equipment, it is characterized in that: electrocardio and motor message harvester are the micro embedded systems of front that is worn on a pectoral girdle, in order to guarantee electrocardiosignal quality, one of them electrode should be placed in electrocardio breast and lead V3 or V4 position, after the premenstrual storing of electrocardiosignal gathering greatly, be converted to again digital signal, deliver to miniature signal processing apparatus with together with motion sensor signal in this device, motion sensor comprises 3 axis accelerometers, increase gyroscope and magnetometer and can increase trunk and forearm three-dimensional perspective estimated accuracy, brachial pulse wave sensor is only operated by operator or measured oneself when starting, synchro measure radial artery and brachial pulse wave train, for calculating tremulous pulse network parameter.
6. noinvasive arteriotony method for continuous measuring according to claim 2 and equipment, it is characterized in that: electrocardiogram signal acquisition device, further comprise based on breast impedance measurement method and measure respiratory wave, the modulation current source of constant amplitude is activated to human body, and measure the voltage that electric current produces, obtain the chest impedance of human body, this impedance changes along with human body respiration, thereby releases respiratory wave.
7. noinvasive arteriotony method for continuous measuring according to claim 1 and equipment, it is characterized in that: signal processing and analyzing unit is a microcomputer, mode with similar wrist-watch is worn on wrist, or wear in loins, it is connected with motor message collecting unit with electrocardio with motor message collecting unit with pulse wave in wired or wireless mode, real-time synchronization is controlled pulse wave signal collecting unit and electrocardio signal collecting unit, real-time synchronization acquisition and processing radial artery and brachial pulse ripple and electrocardio and motor message, calculate tremulous pulse network model parameter, calculate continuously radial artery blood pressure and center arteriotony, analyze motion and the attitude of trunk and forearm, storage data, report is provided, in wired or wireless mode to computer or server uploading data.
8. noinvasive arteriotony method for continuous measuring according to claim 1 and equipment, it is characterized in that: noinvasive arteriotony method for continuous measuring comprises: set up the arteries model based on mechanics of viscous fluids, use the radial artery and the brachial pulse wave train that synchronously record, calculate Artery Vein model parameter, it is the resistance of blood flow of radial artery, blood flow inertia and vascular compliance, set up this section of radial artery based on arteries model without blood pressure and the pulse velocity of wave relation of the even blood vessel of bifurcated, and calculate mean blood pressure by pulse velocity of wave, the formula of systolic pressure and diastolic pressure, set up the pulse wave speed proportionate relationship of every section of blood vessel in blood vessel network, thereby blood pressure and pulse velocity of wave relation are expanded to any vessels section in tremulous pulse network, comprise that center tremulous pulse is to radial artery, can go out pulse wave velocity from electrocardiogram and radial artery pulse wave waveshape, set up based on arteries network model and calculated ascending aorta to the method for the transfer function of radial artery, and by the formula of radial artery blood pressure computer center arteriotony.
9. the signal processing and analyzing unit in noinvasive arteriotony method for continuous measuring according to claim 7 and equipment, it is characterized in that: signal processing and analyzing unit obtains electrocardiogram (ECG) data and respiratory wave data from electrocardio and motor message collecting unit, it is carried out filtering, removes baseline drift, electrocardiosignal is extracted QRS ripple, ST section, detects anomalous ecg, calculated heart rate, heart rate variability degree.
10. the signal processing and analyzing unit in noinvasive arteriotony method for continuous measuring according to claim 7 and equipment, it is characterized in that: signal processing and analyzing unit obtains trunk motor message from electrocardio and motor message collecting unit, comprise accelerometer signal, gyroscope and magnetometer signals, according to one group of signal wherein, or merge to organize signals more, infer human body attitude and type of sports, comprise: lie, sit, stand, walk, run, fall, sit up, lie down, stand, sit down, and the cadence when walking and running, calculate the angle of pitch and the attitude of trunk, from the forearm exercise data of pulse wave and the acquisition of motor message collecting unit, analyze the motion and standstill state of forearm, calculate the angle of pitch and the attitude of forearm.
A kind of noinvasive arteriotony of 11. noinvasive according to claim 7 continuous measurement equipment
Signal processing and analyzing unit in arteriotony method for continuous measuring and equipment, it is characterized in that: the radial artery that processing collects and brachial pulse ripple signal are to sequence, find out suitable data point sequence pair, list parameter matrix and observing matrix, use least-squares algorithm, obtain tremulous pulse network model parameter, comprise radial artery blood flow resistance, blood flow inertia and vascular compliance.
Signal processing and analyzing unit in 12. noinvasive arteriotony method for continuous measuring according to claim 7 and equipment, it is characterized in that: every a pair of radial artery and brachial pulse by continuous measurement involve corresponding two sensor distance calculating radial pulse velocity of wave propagation, or by every a pair of radial artery pulse wave and the electrocardiosignal waveform of continuous measurement, computer center's tremulous pulse is to the pulse wave the mean propagation velocity of radial artery, again according to the proportionate relationship of the pulse wave velocity between tremulous pulse network medium vessels, obtain the pulse wave velocity of radial artery, according to the relation formula of pulse wave velocity and blood pressure, calculate radial artery blood pressure systolic pressure and diastolic pressure and waveform, according to human body artery blood vessel network model, calculate ascending aorta to the transfer function of radial artery, and and then computer center's arteriotony wave mode.
Signal processing and analyzing unit in 13. noinvasive arteriotony method for continuous measuring according to claim 7 and equipment, it is characterized in that: the tremulous pulse network model parameter going out according to measurements and calculations, radial artery and center tremulous pulse continuous blood pressure and waveform thereof, the type of sports of trunk and forearm, intensity, attitude and pitch angle data, and time tag, analyze and show radial artery and center arteriotony in time, and the variation of motion and attitude, calculate and demonstration atherogenic index, cardiorespiratory system health index, center arteriotony waveform echo flex point, augmentation index (AIX), diagnosis basis as hypertension.
14. noinvasive arteriotony method for continuous measuring according to claim 1 and equipment, it is characterized in that: according to human body and forearm motion and attitude type, merge blood pressure, electrocardio, breath signal and they with the variation of division of day and night and motion, calculate many organs variability parameter of wearer, as its cardiorespiratory system health index, characterize this wearer's health status, predict possible disease.
15. noinvasive arteriotony method for continuous measuring according to claim 1 and equipment, it is characterized in that: each continuous arteriotony measurement device can independent operating, also can connect with computer or server by wireless or wired (as USB), the data that measurements and calculations are gone out, and the immediate status of continuous arteriotony measurement device, as battery levels, pulse wave and electrocardio sample rate, the duty of each unit and self-detection result, upload to computer or server, computer or server connect and manage a plurality of noinvasive arteriotony continuous measurement equipment, accept and analyze wearer under different motion state and attitude, the different division of day and night, electrocardio, breathe and blood pressure data, according to wearer's age, sex, medical history, comprehensive report is provided, to unique individual, analyze and follow the tracks of health status and the state of an illness, to all personnel, research cardiorespiratory system health and the generation of disease to different crowd, development, control, rehabilitation is followed the tracks of and is furtherd investigate.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310172583.1A CN104138253B (en) | 2013-05-11 | 2013-05-11 | A kind of noinvasive arteriotony method for continuous measuring and equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310172583.1A CN104138253B (en) | 2013-05-11 | 2013-05-11 | A kind of noinvasive arteriotony method for continuous measuring and equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104138253A true CN104138253A (en) | 2014-11-12 |
| CN104138253B CN104138253B (en) | 2016-06-15 |
Family
ID=51847717
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201310172583.1A Active CN104138253B (en) | 2013-05-11 | 2013-05-11 | A kind of noinvasive arteriotony method for continuous measuring and equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104138253B (en) |
Cited By (58)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104545854A (en) * | 2015-01-30 | 2015-04-29 | 中国科学院电子学研究所 | Cuffless ambulatory blood pressure monitoring equipment based on electrocardio signals and impedance signals |
| CN104644151A (en) * | 2015-02-01 | 2015-05-27 | 北京工业大学 | Photoelectric volume pulse signal-based propagation prediction method for pulse pressure waveform |
| CN104706348A (en) * | 2015-03-20 | 2015-06-17 | 宁波市美灵思医疗科技有限公司 | Multi-mode continuous blood pressure measurement device and self-calibration method thereof |
| CN104720777A (en) * | 2015-03-10 | 2015-06-24 | 中国科学院电子学研究所 | Non-invasive continuous blood pressure physiological monitoring system |
| CN104799851A (en) * | 2015-04-23 | 2015-07-29 | 巩春智 | Intelligent anaesthesia system |
| CN104873186A (en) * | 2015-04-17 | 2015-09-02 | 中国科学院苏州生物医学工程技术研究所 | Wearable artery detection device and data processing method thereof |
| CN104921718A (en) * | 2015-01-30 | 2015-09-23 | 董云鹏 | Health monitoring and managing system |
| CN105147268A (en) * | 2015-06-15 | 2015-12-16 | 辛勤 | Method and device for monitoring health |
| CN105343977A (en) * | 2015-10-20 | 2016-02-24 | 山东大学齐鲁医院 | Control system of anesthesia vaporizer |
| CN106037696A (en) * | 2016-08-11 | 2016-10-26 | 深圳市埃微信息技术有限公司 | Continuous blood pressure measurement equipment based on photoplethysmographic sensors |
| CN106037695A (en) * | 2016-05-20 | 2016-10-26 | 深圳市玉成创新科技有限公司 | Blood pressure detection equipment, blood pressure monitoring system and method |
| CN106073732A (en) * | 2016-07-29 | 2016-11-09 | 刘琼 | Cardiovascular arteriosclerosis detecting device |
| CN106236050A (en) * | 2016-08-19 | 2016-12-21 | 黄广明 | A kind of safety monitoring device for old people |
| WO2017049624A1 (en) * | 2015-09-25 | 2017-03-30 | 华为技术有限公司 | Blood pressure measurement method, blood pressure measurement device and terminal |
| TWI578956B (en) * | 2016-11-10 | 2017-04-21 | Blood pressure measurement system based on body weight | |
| CN106618537A (en) * | 2016-12-21 | 2017-05-10 | 天津普仁万合信息技术有限公司 | Continuous dynamic blood pressure monitoring device and method based on pulse wave transit |
| CN106618540A (en) * | 2015-11-03 | 2017-05-10 | 深圳市维亿魄科技有限公司 | Non-invasive blood pressure detection method and device |
| CN107249435A (en) * | 2015-02-14 | 2017-10-13 | 体育企业有限公司 | The system and method that user's insight is provided based on real-time physiological parameter |
| CN107280762A (en) * | 2016-04-12 | 2017-10-24 | 西门子保健有限责任公司 | Method and system for carrying out individualized blood flow modeling based on wearable sensors network |
| CN107307857A (en) * | 2017-06-23 | 2017-11-03 | 成都市欣康兴泰科技有限公司 | A kind of pulse pressure optimum position Automatic-searching method and apparatus |
| CN107348952A (en) * | 2017-08-10 | 2017-11-17 | 上海理工大学 | Pulse Evolution Modes difference blood pressure monitor system |
| CN107348953A (en) * | 2017-08-10 | 2017-11-17 | 上海理工大学 | Pulse array mixed mode blood pressure monitor system |
| WO2017212120A1 (en) * | 2016-06-10 | 2017-12-14 | Polar Electro Oy | Multi-sensor system for estimating blood pulse wave characteristics |
| CN107669248A (en) * | 2017-09-29 | 2018-02-09 | 长春市万易科技有限公司 | Old man's dynamic pulse continuous detecting system and method |
| WO2018045499A1 (en) * | 2016-09-07 | 2018-03-15 | 中国科学院微电子研究所 | Pulse wave diagnostic system having respiratory wave collection function |
| CN107920763A (en) * | 2015-07-16 | 2018-04-17 | 普瑞温迪克斯有限责任公司 | Handle biological data |
| CN108236458A (en) * | 2016-12-26 | 2018-07-03 | 深圳先进技术研究院 | The method that brachial arterial pressure is rebuild based on double peripheral blood pressures |
| US10039455B2 (en) | 2014-05-19 | 2018-08-07 | Qualcomm Incorporated | Continuous calibration of a blood pressure measurement device |
| CN108523868A (en) * | 2018-06-15 | 2018-09-14 | 安徽中科智链信息科技有限公司 | Self-calibration system and method for blood pressure measurement |
| WO2018201857A1 (en) * | 2017-05-05 | 2018-11-08 | Jiangsu Huaben Health Life Science and Technology Co., Ltd. | Method and apparatus for human health evaluation |
| CN108882867A (en) * | 2016-04-15 | 2018-11-23 | 欧姆龙株式会社 | Biont information analytical equipment, system and program |
| CN109157201A (en) * | 2018-08-13 | 2019-01-08 | 广州喜梁门科技有限公司 | A kind of system and its control method of bracelet equipment |
| CN109222941A (en) * | 2018-11-09 | 2019-01-18 | 中科数字健康科学研究院（南京）有限公司 | A kind of measurement method and measuring device of pulse wave propagation time |
| CN109381170A (en) * | 2018-12-06 | 2019-02-26 | 王�琦 | Pressure sensor, noninvasive continuous monitoring blood pressure device and system |
| CN109602401A (en) * | 2019-01-28 | 2019-04-12 | 徐州市心血管病研究所 | A kind of microvascular blood flow kinetic parameter analyzer and analysis method |
| CN109862826A (en) * | 2016-08-18 | 2019-06-07 | 皇家飞利浦有限公司 | Blood pressure management |
| CN109893110A (en) * | 2019-03-06 | 2019-06-18 | 深圳市理邦精密仪器股份有限公司 | A kind of method and device for calibrating ambulatory blood pressure |
| CN110381822A (en) * | 2017-03-15 | 2019-10-25 | 欧姆龙株式会社 | Blood pressure measurement apparatus, blood pressure measuring method and program |
| CN110430807A (en) * | 2017-03-15 | 2019-11-08 | 欧姆龙株式会社 | Biological information measurement device, method and program |
| CN110584624A (en) * | 2019-09-18 | 2019-12-20 | 中国科学院微电子研究所 | Pulse wave feature point identification method based on included angle value |
| CN110710960A (en) * | 2019-09-12 | 2020-01-21 | 东莞市康助医疗科技有限公司 | Arterial blood vessel age estimation method and device |
| CN111387945A (en) * | 2015-04-28 | 2020-07-10 | 京瓷株式会社 | Electronic device and system |
| CN111481187A (en) * | 2020-05-27 | 2020-08-04 | 童心堂科技(深圳)有限公司 | Artificial intelligence arrhythmia detection method based on arterial pressure wave characteristics |
| CN111839717A (en) * | 2020-07-27 | 2020-10-30 | 哈尔滨医科大学 | System for real-time display of trans-aortic valve pressure in room interval ablation |
| CN111904404A (en) * | 2020-08-06 | 2020-11-10 | 苏州国科医工科技发展(集团)有限公司 | Blood pressure regulation and control equipment containing closed-loop monitoring and based on ear vagus nerve stimulation |
| CN112272534A (en) * | 2018-06-05 | 2021-01-26 | 皇家飞利浦有限公司 | Method and apparatus for estimating blood pressure surrogate trends |
| CN112739255A (en) * | 2018-05-25 | 2021-04-30 | 精准医电科技股份有限公司 | Blood pressure measuring device |
| CN112889118A (en) * | 2018-09-04 | 2021-06-01 | 阿克提雅有限公司 | System for determining blood pressure of one or more users |
| CN113069096A (en) * | 2015-03-31 | 2021-07-06 | 深圳市长桑技术有限公司 | System and method for monitoring blood pressure |
| CN113143230A (en) * | 2021-05-11 | 2021-07-23 | 重庆理工大学 | Peripheral arterial blood pressure waveform reconstruction system |
| US20220031183A1 (en) * | 2018-12-04 | 2022-02-03 | Myllylae Teemu | Biosignal measurement apparatus and method |
| CN114098660A (en) * | 2020-08-31 | 2022-03-01 | 逢甲大学 | Arteriosclerosis risk assessment system |
| US11337615B2 (en) | 2020-03-06 | 2022-05-24 | The Access Technologies | Smart wristband for multiparameter physiological monitoring |
| WO2022246987A1 (en) * | 2021-05-26 | 2022-12-01 | 南京大学 | Construction method and application of hemodynamics-based digital human cardiovascular system |
| CN115581444A (en) * | 2022-09-29 | 2023-01-10 | 汉王科技股份有限公司 | Blood pressure detection method, device, sphygmomanometer and medium |
| CN116746896A (en) * | 2023-08-21 | 2023-09-15 | 深圳大学 | Continuous blood pressure estimation method and device, electronic equipment and storage medium |
| CN116807426A (en) * | 2023-07-24 | 2023-09-29 | 山东山科智心科技有限公司 | System based on photoelectric sensor vital sign signal acquisition and analysis |
| CN117017249A (en) * | 2023-10-07 | 2023-11-10 | 深圳市爱保护科技有限公司 | Blood pressure detection method, device, electronic equipment and storage medium |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1925785A (en) * | 2003-12-05 | 2007-03-07 | 爱德华兹生命科学公司 | Arterial pressure-based, automatic determination of a cardiovascular parameter |
| US20090131804A1 (en) * | 2006-03-15 | 2009-05-21 | Ramakrishna Mukkamala | Method And Apparatus For Determining Central Aortic Pressure Waveform |
| US20100016736A1 (en) * | 2008-07-16 | 2010-01-21 | Massachusetts Institute Of Technology | Estimating Aortic Blood Pressure from Non-Invasive Extremity Blood Pressure |
| CN101686806A (en) * | 2007-03-30 | 2010-03-31 | 欧姆龙健康医疗株式会社 | Blood vessel state evaluating device, blood vessel state evaluating method, and computer-readable recording medium storing blood vessel state evaluating program |
| CN102026576A (en) * | 2008-05-15 | 2011-04-20 | 帕尔斯科尔有限公司 | Method for estimating a central pressure waveform obtained with a blood pressure cuff |
| US20110275944A1 (en) * | 2010-05-07 | 2011-11-10 | Atcor Medical Pty Ltd. | Brachial Cuff |
| CN102499658A (en) * | 2011-11-08 | 2012-06-20 | 中国科学院深圳先进技术研究院 | Central blood pressure waveform reconstruction module and reconstruction method |
-
2013
- 2013-05-11 CN CN201310172583.1A patent/CN104138253B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1925785A (en) * | 2003-12-05 | 2007-03-07 | 爱德华兹生命科学公司 | Arterial pressure-based, automatic determination of a cardiovascular parameter |
| US20090131804A1 (en) * | 2006-03-15 | 2009-05-21 | Ramakrishna Mukkamala | Method And Apparatus For Determining Central Aortic Pressure Waveform |
| CN101686806A (en) * | 2007-03-30 | 2010-03-31 | 欧姆龙健康医疗株式会社 | Blood vessel state evaluating device, blood vessel state evaluating method, and computer-readable recording medium storing blood vessel state evaluating program |
| CN102026576A (en) * | 2008-05-15 | 2011-04-20 | 帕尔斯科尔有限公司 | Method for estimating a central pressure waveform obtained with a blood pressure cuff |
| US20100016736A1 (en) * | 2008-07-16 | 2010-01-21 | Massachusetts Institute Of Technology | Estimating Aortic Blood Pressure from Non-Invasive Extremity Blood Pressure |
| US20110275944A1 (en) * | 2010-05-07 | 2011-11-10 | Atcor Medical Pty Ltd. | Brachial Cuff |
| CN102499658A (en) * | 2011-11-08 | 2012-06-20 | 中国科学院深圳先进技术研究院 | Central blood pressure waveform reconstruction module and reconstruction method |
Cited By (86)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10052036B2 (en) | 2014-05-19 | 2018-08-21 | Qualcomm Incorporated | Non-interfering blood pressure measuring |
| US10039455B2 (en) | 2014-05-19 | 2018-08-07 | Qualcomm Incorporated | Continuous calibration of a blood pressure measurement device |
| CN104921718A (en) * | 2015-01-30 | 2015-09-23 | 董云鹏 | Health monitoring and managing system |
| CN104545854A (en) * | 2015-01-30 | 2015-04-29 | 中国科学院电子学研究所 | Cuffless ambulatory blood pressure monitoring equipment based on electrocardio signals and impedance signals |
| CN104644151B (en) * | 2015-02-01 | 2017-07-07 | 北京工业大学 | A kind of pressure pulse wave wave travel Forecasting Methodology based on photoelectricity volume pulse signal |
| CN104644151A (en) * | 2015-02-01 | 2015-05-27 | 北京工业大学 | Photoelectric volume pulse signal-based propagation prediction method for pulse pressure waveform |
| CN107249435A (en) * | 2015-02-14 | 2017-10-13 | 体育企业有限公司 | The system and method that user's insight is provided based on real-time physiological parameter |
| CN104720777A (en) * | 2015-03-10 | 2015-06-24 | 中国科学院电子学研究所 | Non-invasive continuous blood pressure physiological monitoring system |
| CN104706348A (en) * | 2015-03-20 | 2015-06-17 | 宁波市美灵思医疗科技有限公司 | Multi-mode continuous blood pressure measurement device and self-calibration method thereof |
| CN113069096A (en) * | 2015-03-31 | 2021-07-06 | 深圳市长桑技术有限公司 | System and method for monitoring blood pressure |
| CN104873186A (en) * | 2015-04-17 | 2015-09-02 | 中国科学院苏州生物医学工程技术研究所 | Wearable artery detection device and data processing method thereof |
| CN104799851A (en) * | 2015-04-23 | 2015-07-29 | 巩春智 | Intelligent anaesthesia system |
| CN111387945B (en) * | 2015-04-28 | 2023-11-14 | 京瓷株式会社 | Electronic equipment and system |
| CN111387945A (en) * | 2015-04-28 | 2020-07-10 | 京瓷株式会社 | Electronic device and system |
| CN105147268A (en) * | 2015-06-15 | 2015-12-16 | 辛勤 | Method and device for monitoring health |
| CN107920763A (en) * | 2015-07-16 | 2018-04-17 | 普瑞温迪克斯有限责任公司 | Handle biological data |
| US11564640B2 (en) | 2015-09-25 | 2023-01-31 | Huawei Technologies Co., Ltd. | Blood pressure measurement method, blood pressure measurement apparatus, and terminal |
| WO2017049624A1 (en) * | 2015-09-25 | 2017-03-30 | 华为技术有限公司 | Blood pressure measurement method, blood pressure measurement device and terminal |
| CN105343977A (en) * | 2015-10-20 | 2016-02-24 | 山东大学齐鲁医院 | Control system of anesthesia vaporizer |
| CN106618540A (en) * | 2015-11-03 | 2017-05-10 | 深圳市维亿魄科技有限公司 | Non-invasive blood pressure detection method and device |
| CN106618540B (en) * | 2015-11-03 | 2020-01-17 | 深圳市维亿魄科技有限公司 | Non-invasive blood pressure detection method and non-invasive blood pressure detection device |
| CN107280762A (en) * | 2016-04-12 | 2017-10-24 | 西门子保健有限责任公司 | Method and system for carrying out individualized blood flow modeling based on wearable sensors network |
| US10971271B2 (en) | 2016-04-12 | 2021-04-06 | Siemens Healthcare Gmbh | Method and system for personalized blood flow modeling based on wearable sensor networks |
| US11617516B2 (en) | 2016-04-15 | 2023-04-04 | Omron Corporation | Biological information analysis device, biological information analysis system, program, and biological information analysis method |
| US11246501B2 (en) | 2016-04-15 | 2022-02-15 | Omron Corporation | Biological information analysis device, system, and program |
| CN108882867A (en) * | 2016-04-15 | 2018-11-23 | 欧姆龙株式会社 | Biont information analytical equipment, system and program |
| CN108882867B (en) * | 2016-04-15 | 2021-12-07 | 欧姆龙株式会社 | Biological information analysis device, system, and program |
| CN106037695A (en) * | 2016-05-20 | 2016-10-26 | 深圳市玉成创新科技有限公司 | Blood pressure detection equipment, blood pressure monitoring system and method |
| CN109310369B (en) * | 2016-06-10 | 2021-10-19 | 博能电子公司 | Multi-sensor system for estimating blood pulse wave characteristics |
| US11160453B2 (en) | 2016-06-10 | 2021-11-02 | Polar Electro Oy | Multi-sensor system for estimating blood pulse wave characteristics |
| WO2017212120A1 (en) * | 2016-06-10 | 2017-12-14 | Polar Electro Oy | Multi-sensor system for estimating blood pulse wave characteristics |
| CN109310369A (en) * | 2016-06-10 | 2019-02-05 | 博能电子公司 | For estimating the multisensor syste of blood pulse wave characteristic |
| CN106073732A (en) * | 2016-07-29 | 2016-11-09 | 刘琼 | Cardiovascular arteriosclerosis detecting device |
| CN106037696A (en) * | 2016-08-11 | 2016-10-26 | 深圳市埃微信息技术有限公司 | Continuous blood pressure measurement equipment based on photoplethysmographic sensors |
| CN109862826A (en) * | 2016-08-18 | 2019-06-07 | 皇家飞利浦有限公司 | Blood pressure management |
| CN106236050A (en) * | 2016-08-19 | 2016-12-21 | 黄广明 | A kind of safety monitoring device for old people |
| WO2018045499A1 (en) * | 2016-09-07 | 2018-03-15 | 中国科学院微电子研究所 | Pulse wave diagnostic system having respiratory wave collection function |
| TWI578956B (en) * | 2016-11-10 | 2017-04-21 | Blood pressure measurement system based on body weight | |
| WO2018113442A1 (en) * | 2016-12-21 | 2018-06-28 | 天津普仁万合信息技术有限公司 | Continuous ambulatory blood pressure monitoring device and method based on pulse wave transit |
| CN106618537A (en) * | 2016-12-21 | 2017-05-10 | 天津普仁万合信息技术有限公司 | Continuous dynamic blood pressure monitoring device and method based on pulse wave transit |
| CN108236458A (en) * | 2016-12-26 | 2018-07-03 | 深圳先进技术研究院 | The method that brachial arterial pressure is rebuild based on double peripheral blood pressures |
| CN110430807A (en) * | 2017-03-15 | 2019-11-08 | 欧姆龙株式会社 | Biological information measurement device, method and program |
| US11564570B2 (en) | 2017-03-15 | 2023-01-31 | Omron Corporation | Biological information measuring apparatus, method and program |
| CN110381822A (en) * | 2017-03-15 | 2019-10-25 | 欧姆龙株式会社 | Blood pressure measurement apparatus, blood pressure measuring method and program |
| WO2018201857A1 (en) * | 2017-05-05 | 2018-11-08 | Jiangsu Huaben Health Life Science and Technology Co., Ltd. | Method and apparatus for human health evaluation |
| CN107307857A (en) * | 2017-06-23 | 2017-11-03 | 成都市欣康兴泰科技有限公司 | A kind of pulse pressure optimum position Automatic-searching method and apparatus |
| CN107348952A (en) * | 2017-08-10 | 2017-11-17 | 上海理工大学 | Pulse Evolution Modes difference blood pressure monitor system |
| CN107348953A (en) * | 2017-08-10 | 2017-11-17 | 上海理工大学 | Pulse array mixed mode blood pressure monitor system |
| CN107669248A (en) * | 2017-09-29 | 2018-02-09 | 长春市万易科技有限公司 | Old man's dynamic pulse continuous detecting system and method |
| CN107669248B (en) * | 2017-09-29 | 2024-02-02 | 长春市万易科技有限公司 | Dynamic pulse continuous detection system and method for old people |
| JP2021524792A (en) * | 2018-05-25 | 2021-09-16 | アキュレイト メディテック インコーポレイテッド | A device for measuring blood pressure |
| CN112739255A (en) * | 2018-05-25 | 2021-04-30 | 精准医电科技股份有限公司 | Blood pressure measuring device |
| US11969236B2 (en) | 2018-05-25 | 2024-04-30 | Accurate Meditech Inc | Device for measuring blood pressure |
| JP7247444B2 (en) | 2018-05-25 | 2023-03-29 | アキュレイト メディテック インコーポレイテッド | device for measuring blood pressure |
| CN112272534A (en) * | 2018-06-05 | 2021-01-26 | 皇家飞利浦有限公司 | Method and apparatus for estimating blood pressure surrogate trends |
| CN112272534B (en) * | 2018-06-05 | 2024-04-05 | 皇家飞利浦有限公司 | Method and apparatus for estimating trend of blood pressure surrogate |
| CN108523868A (en) * | 2018-06-15 | 2018-09-14 | 安徽中科智链信息科技有限公司 | Self-calibration system and method for blood pressure measurement |
| CN109157201A (en) * | 2018-08-13 | 2019-01-08 | 广州喜梁门科技有限公司 | A kind of system and its control method of bracelet equipment |
| CN112889118A (en) * | 2018-09-04 | 2021-06-01 | 阿克提雅有限公司 | System for determining blood pressure of one or more users |
| CN109222941A (en) * | 2018-11-09 | 2019-01-18 | 中科数字健康科学研究院（南京）有限公司 | A kind of measurement method and measuring device of pulse wave propagation time |
| US20220031183A1 (en) * | 2018-12-04 | 2022-02-03 | Myllylae Teemu | Biosignal measurement apparatus and method |
| CN109381170A (en) * | 2018-12-06 | 2019-02-26 | 王�琦 | Pressure sensor, noninvasive continuous monitoring blood pressure device and system |
| CN109602401A (en) * | 2019-01-28 | 2019-04-12 | 徐州市心血管病研究所 | A kind of microvascular blood flow kinetic parameter analyzer and analysis method |
| CN109602401B (en) * | 2019-01-28 | 2021-08-27 | 徐州市心血管病研究所 | Microvascular hemodynamic parameter analyzer and analysis method |
| CN109893110A (en) * | 2019-03-06 | 2019-06-18 | 深圳市理邦精密仪器股份有限公司 | A kind of method and device for calibrating ambulatory blood pressure |
| CN109893110B (en) * | 2019-03-06 | 2022-06-07 | 深圳市理邦精密仪器股份有限公司 | Method and device for calibrating dynamic blood pressure |
| CN110710960A (en) * | 2019-09-12 | 2020-01-21 | 东莞市康助医疗科技有限公司 | Arterial blood vessel age estimation method and device |
| CN110710960B (en) * | 2019-09-12 | 2022-12-09 | 东莞市康助医疗科技有限公司 | Arterial blood vessel age estimation method and device |
| CN110584624A (en) * | 2019-09-18 | 2019-12-20 | 中国科学院微电子研究所 | Pulse wave feature point identification method based on included angle value |
| CN110584624B (en) * | 2019-09-18 | 2022-04-01 | 中国科学院微电子研究所 | Pulse wave feature point identification method based on included angle value |
| US11337615B2 (en) | 2020-03-06 | 2022-05-24 | The Access Technologies | Smart wristband for multiparameter physiological monitoring |
| CN111481187A (en) * | 2020-05-27 | 2020-08-04 | 童心堂科技(深圳)有限公司 | Artificial intelligence arrhythmia detection method based on arterial pressure wave characteristics |
| CN111839717A (en) * | 2020-07-27 | 2020-10-30 | 哈尔滨医科大学 | System for real-time display of trans-aortic valve pressure in room interval ablation |
| CN111839717B (en) * | 2020-07-27 | 2021-06-18 | 哈尔滨医科大学 | System for real-time display of trans-aortic valve pressure in room interval ablation |
| CN111904404B (en) * | 2020-08-06 | 2021-06-18 | 苏州国科医工科技发展(集团)有限公司 | Blood pressure regulation and control equipment containing closed-loop monitoring and based on ear vagus nerve stimulation |
| CN111904404A (en) * | 2020-08-06 | 2020-11-10 | 苏州国科医工科技发展(集团)有限公司 | Blood pressure regulation and control equipment containing closed-loop monitoring and based on ear vagus nerve stimulation |
| CN114098660A (en) * | 2020-08-31 | 2022-03-01 | 逢甲大学 | Arteriosclerosis risk assessment system |
| CN113143230A (en) * | 2021-05-11 | 2021-07-23 | 重庆理工大学 | Peripheral arterial blood pressure waveform reconstruction system |
| WO2022246987A1 (en) * | 2021-05-26 | 2022-12-01 | 南京大学 | Construction method and application of hemodynamics-based digital human cardiovascular system |
| CN115581444B (en) * | 2022-09-29 | 2023-12-12 | 汉王科技股份有限公司 | Blood pressure detection device |
| CN115581444A (en) * | 2022-09-29 | 2023-01-10 | 汉王科技股份有限公司 | Blood pressure detection method, device, sphygmomanometer and medium |
| CN116807426A (en) * | 2023-07-24 | 2023-09-29 | 山东山科智心科技有限公司 | System based on photoelectric sensor vital sign signal acquisition and analysis |
| CN116746896B (en) * | 2023-08-21 | 2023-11-07 | 深圳大学 | Continuous blood pressure estimation method and device, electronic equipment and storage medium |
| CN116746896A (en) * | 2023-08-21 | 2023-09-15 | 深圳大学 | Continuous blood pressure estimation method and device, electronic equipment and storage medium |
| CN117017249A (en) * | 2023-10-07 | 2023-11-10 | 深圳市爱保护科技有限公司 | Blood pressure detection method, device, electronic equipment and storage medium |
| CN117017249B (en) * | 2023-10-07 | 2024-01-12 | 深圳市爱保护科技有限公司 | Blood pressure detecting device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104138253B (en) | 2016-06-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104138253B (en) | A kind of noinvasive arteriotony method for continuous measuring and equipment | |
| JP5984088B2 (en) | Noninvasive continuous blood pressure monitoring method and apparatus | |
| CN108471987B (en) | Improvements in or relating to cardiac monitoring | |
| JP2021142349A (en) | Observational heart failure monitoring system | |
| CN103491868B (en) | For cardiac output, stroke output, mental and physical efforts and blood pressure continuously, the body worn formula system of non-invasive measurement | |
| McCarthy et al. | An investigation of pulse transit time as a non-invasive blood pressure measurement method | |
| CN103892818B (en) | A kind of non-invasive central arterial blood pressure measuring method and equipment | |
| CN107233087A (en) | A kind of Woundless blood pressure measuring device based on photoplethysmographic feature | |
| CN108366749A (en) | Ambulatory blood pressure and life physical sign monitoring device, system and method | |
| Murali et al. | A wearable device for physical and emotional health monitoring | |
| CN106028918A (en) | Body-worn system for continuous, noninvasive measurement of vital signs | |
| EP3551060B1 (en) | Pulse wave velocity determination, for example for blood pressure monitoring | |
| WO2022246987A1 (en) | Construction method and application of hemodynamics-based digital human cardiovascular system | |
| CN111631698A (en) | Wearable blood pressure monitoring and correcting method based on motion mode cascade constraint | |
| CN109730663A (en) | Assessment of blood pressure method based on pulse wave conduction speed nonlinear analysis | |
| WO2013128364A1 (en) | A method of processing a signal representing a physiological rhythm | |
| CN104921718A (en) | Health monitoring and managing system | |
| CN105455797A (en) | Method and device for measuring autonomic nerve heart regulation and control function | |
| Marques et al. | A real time, wearable ECG and blood pressure monitoring system | |
| Zhang et al. | Assessment of pre-ejection period in ambulatory subjects using seismocardiogram in a wearable blood pressure monitor | |
| CN110881967A (en) | Non-invasive multi-segment peripheral arterial vessel elastic function detection method and instrument thereof | |
| Shao et al. | An optimization study of estimating blood pressure models based on pulse arrival time for continuous monitoring | |
| Shokouhmand et al. | Fingertip Strain Plethysmography: Representation of Pulse Information based on Vascular Vibration | |
| Bhattacharjee | Continuous blood pressure monitoring method based on multiple photoplethysmography features | |
| Koay et al. | Cuffless Blood Pressure Meter with Mobile Application for Home-Care Service |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20180402 Address after: Yao Chong Street Road in Qixia District of Nanjing city in Jiangsu province 210046 No. 1 building 04 room 705 Patentee after: Nanjing Maosen Electronics Technology Co. Ltd. Address before: 100049 Yuquanlu Road Yuquan new town, Shijingshan District, Beijing, 19-3-502 Patentee before: Wu Jiankang |