CN113907727A - Beat-to-beat blood pressure measuring system and method based on photoplethysmography - Google Patents
Beat-to-beat blood pressure measuring system and method based on photoplethysmography Download PDFInfo
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Abstract
The invention belongs to the technical field of medical equipment, and provides a beat-by-beat blood pressure measuring system, method and device based on photoplethysmography, wherein the system comprises: the signal acquisition module is used for acquiring pulse wave signals; the blood pressure calculation module is used for extracting three characteristics related to blood pressure from the pulse wave signals and calculating a blood pressure value according to the characteristics; and the application interaction module is used for measuring the motion state of the user, calculating the blood pressure variability and interacting with the user. The invention analyzes the flow of blood in blood vessels by an elastohydrodynamic method, measures pulse waves by a photoplethysmography, extracts three characteristics with high correlation degree with blood pressure from the pulse waves to calculate the blood pressure value, realizes beat-by-beat blood pressure measurement, improves the precision of the blood pressure measurement, can also judge the motion state of a measured user, calculates the blood pressure variability according to the motion state, and is an important index for evaluating risk coefficients of patients with cardiovascular diseases, diabetes and the like.
Description
Technical Field
The invention belongs to the technical field of medical equipment, and particularly relates to a beat-to-beat blood pressure measuring system, method and device based on photoplethysmography and a computer readable medium.
Background
Blood pressure is the most important risk factor for cardiovascular diseases. Blood pressure measurement and monitoring are important in medical and health practices such as physical examination, diagnosis and surgery. Blood pressure changes with heartbeat beats, and beat-to-beat blood pressure measurement is naturally required for medical treatment. The current gold standard for beat-to-beat blood pressure measurement in the medical community is invasive, inserting a pressure sensor into the arterial vessel, an invasive method that is only used in certain critical cases, and not in general patients and normal persons.
The existing noninvasive beat-by-beat blood pressure measurement products have two types: tensiometry, also known as the flatting method. The complex mechanical device is needed to enable the blood vessel to be in a state that the internal pressure and the external pressure are equal, the operation is complex, the position and the movement are sensitive, and the measurement result is unstable. The volume compensation method adopts a servo system to compensate the change of the arterial volume caused by the change of the arterial internal pressure, so that the internal pressure of the cuff is equal to the arterial internal pressure. This method also requires a complicated mechanical device, and the measurement for a long time is uncomfortable for the subject.
The relationship between blood pressure and pulse wave velocity (PTT) is derived by Thomas Young, a well-known physicist in the united kingdom, who models the flow of blood in blood vessels as elastohydrodynamic intravascular wave propagation. This has led to a great deal of research work to measure PTT to estimate blood pressure.
However, due to technical limitations, pulse transit time cannot be directly detected. Thus, there is a class of methods that use simultaneous measurement of the ECG and PPG pulse waves to calculate the Pulse Arrival Time (PAT) instead of PTT. Chinese patent CN110251105A, "a method, apparatus, device and system for non-invasive blood pressure measurement". Synchronously measuring the electrocardiosignals and the pulse wave signals, and analyzing and extracting characteristic values; and inputting the personal sign data and the extracted characteristic value into a pre-established blood pressure measurement model to calculate and obtain the blood pressure measurement information of the user. However, this PAT-based approach has natural drawbacks, the pulse arrival time PAT including PTT and pre-ejection period, i.e. left ventricular electromechanical delay time and isovolumetric contraction period. The uncertainty in this part of the time seriously affects the measurement accuracy.
The pulse wave is a dynamic representation of blood flowing in a blood vessel, and has all features related to blood pressure. Therefore, it has been proposed to replace PTT with the PPG signal characteristic, Slope Transit Time (STT), of the photoplethysmographic pulse wave. Chinese patent CN107233087A, "a non-invasive blood pressure measuring device based on photoplethysmography characteristics", proposes an average slope transmission time MSTT, which realizes the estimation of blood pressure by a single physiological signal photoplethysmography pulse wave. The mean slope transmission time MSTT proposed in this patent, although reducing noise interference by averaging, loses the advantages of beat-to-beat blood pressure measurement and response to blood pressure changes, and the corresponding clinical application value.
Disclosure of Invention
Technical problem to be solved
The invention aims to solve the technical problems of non-invasive and inflation-free cuff measurement of accurate beat-to-beat blood pressure.
(II) technical scheme
In order to solve the above technical problem, an aspect of the present invention provides a beat-to-beat blood pressure measuring system based on photoplethysmography, including: a signal acquisition module, a blood pressure calculation module and an application interaction module, wherein,
the signal acquisition module is used for acquiring a photoplethysmography signal and an acceleration signal;
the blood pressure calculation module is configured to receive the photoplethysmography signal and extract a plurality of features associated with blood pressure from the photoplethysmography signal, the features including: the normalized slope transmission time, the minimum point of the descending derivative and the normalized tidal wave peak value are also used for acquiring personalized blood pressure calculation parameters according to the personal information of the user to be detected; calculating a beat-to-beat blood pressure value according to the personalized blood pressure calculation parameters and the three characteristics;
the application interaction module is used for judging the motion state of the detected user according to the three-dimensional acceleration signal, marking the motion state of the beat-by-beat blood pressure and calculating the blood pressure variability of the beat-by-beat blood pressure value sequence in the rest state reaching or exceeding a preset time period.
According to a preferred embodiment of the present invention, the signal acquisition module acquires the photoplethysmography signal and the acceleration signal from a fingertip or a wrist of a user to be tested.
According to a preferred embodiment of the present invention, the normalized slope transit time calculation formula is:
wherein NSTT is normalized slope transmission time, m is the maximum slope of the rising part of the photoplethysmography pulse wave, H is the amplitude of the photoplethysmography pulse wave, A is a constant arbitrary amplitude related to the amplitude of the photoplethysmography pulse wave, and t is time;
the normalized tidal wave peak value calculation formula is as follows:
wherein NPTW is the normalized tidal wave Peak value, hBAnd hFThe height of the point B and the height of the point F of the photoplethysmography signal are respectively shown, and H is the amplitude of the photoplethysmography signal;
the calculation formula of the minimum point of the descending branch derivative is as follows: PMDD ═ tD-tFWhere PMDD is the minimum point of the reduced derivative, tDAnd tFRespectively, the time of the minimum point D and the time of the point F of the falling-band derivative of the photoplethysmographic pulse wave.
According to a preferred embodiment of the invention, the indicator of blood pressure variability comprises: mean blood pressure, standard deviation, coefficient of variation, actual mean of variation, mean-independent variation, rate of change, dynamic arteriosclerosis index, and sample entropy.
According to a preferred embodiment of the invention, the beat-by-beat blood pressure values comprise a systolic pressure value and a diastolic pressure value.
The invention provides a beat-to-beat blood pressure measuring method based on photoplethysmography in a second aspect, which comprises the following steps:
acquiring photoplethysmography data and three-dimensional acceleration signals of the pulse waves;
extracting preset characteristics related to blood pressure from the pulse wave signals, and calculating to obtain beat-to-beat blood pressure values according to the preset characteristics, wherein the preset characteristics comprise: normalized slope transmission time, minimum point of the descending derivative and normalized tidal wave peak value;
and judging the motion state of the detected user according to the three-dimensional acceleration signal, labeling the beat-by-beat blood pressure values, and calculating the blood pressure variability of a beat-by-beat blood pressure value sequence in a rest state reaching or exceeding a preset time period.
The invention provides a photoplethysmography-based beat-by-beat blood pressure measuring device, which is a wearable device and comprises the blood pressure measuring system, wherein the signal acquisition module is arranged in a fingertip sleeve or a smart watch of the wearable device; the blood pressure calculation module and the application interaction module are arranged in embedded software of the wearable device, and are used for measuring and monitoring beat-to-beat blood pressure, analyzing the measured blood pressure and the variation index thereof, issuing a measurement and monitoring report, and uploading data to a server to-be-measured user.
The fourth aspect of the present invention also provides a computer-readable medium storing a computer-executable program, which when executed, implements the above-mentioned method.
(III) advantageous effects
The invention analyzes the flow of blood in blood vessels by an elastohydrodynamic method, measures pulse waves by a photoplethysmography, extracts three characteristics with high correlation degree with blood pressure from the pulse waves to calculate the blood pressure value, realizes beat-by-beat blood pressure measurement, improves the precision of the blood pressure measurement, can also judge the motion state of a measured user, calculates the blood pressure variability according to the motion state, and is an important index for evaluating risk coefficients of patients with cardiovascular diseases, diabetes and the like.
Drawings
FIG. 1 is a schematic diagram of a photoplethysmography-based beat-to-beat blood pressure measurement system according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an embodiment of the present invention of extracting a Normalized Slope Transit Time (NSTT) from a photoplethysmograph signal;
FIG. 3 is a schematic diagram of an extracted minimum point of the descending derivative (PMDD) and Normalized Peak Tidal Wave (NPTW) of a photoplethysmograph signal in accordance with one embodiment of the present invention;
FIG. 4 is a flow chart of a method for measuring blood pressure beat by beat based on photoplethysmography according to an embodiment of the present invention;
fig. 5 is a schematic diagram of a computer-readable recording medium of an embodiment of the present invention.
Detailed Description
In describing particular embodiments, specific details of structures, properties, effects, or other features are set forth in order to provide a thorough understanding of the embodiments by one skilled in the art. However, it is not excluded that a person skilled in the art may implement the invention in a specific case without the above-described structures, performances, effects or other features.
The flow chart in the drawings is only an exemplary flow demonstration, and does not represent that all the contents, operations and steps in the flow chart are necessarily included in the scheme of the invention, nor does it represent that the execution is necessarily performed in the order shown in the drawings. For example, some operations/steps in the flowcharts may be divided, some operations/steps may be combined or partially combined, and the like, and the execution order shown in the flowcharts may be changed according to actual situations without departing from the gist of the present invention.
The block diagrams in the figures generally represent functional entities and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different network and/or processing unit devices and/or microcontroller devices.
The same reference numerals denote the same or similar elements, components, or parts throughout the drawings, and thus, a repetitive description thereof may be omitted hereinafter. It will be further understood that, although the terms first, second, third, etc. may be used herein to describe various elements, components, or sections, these elements, components, or sections should not be limited by these terms. That is, these phrases are used only to distinguish one from another. For example, a first device may also be referred to as a second device without departing from the spirit of the present invention. Furthermore, the term "and/or", "and/or" is intended to include all combinations of any one or more of the listed items.
In order that the objects, technical solutions and advantages of the present invention will become more apparent, the present invention will be further described in detail with reference to the accompanying drawings in conjunction with the following specific embodiments.
FIG. 1 is a schematic diagram of a beat-to-beat blood pressure measurement system based on photoplethysmography according to an embodiment of the present invention.
As shown in fig. 1, the present system includes:
a signal collecting module 100 for collecting pulse wave signals;
a blood pressure calculating module 200, configured to extract a preset feature related to blood pressure from the pulse wave signal, and calculate blood pressure according to the preset feature;
and the application interaction module 300 is used for displaying the blood pressure measurement result and interacting with the user.
In some embodiments, signal acquisition module 100 may be a miniature wearable device, including a photoplethysmography (PPG) signal acquisition unit 110 that acquires photoplethysmography data using a photosensor; the acceleration signal acquisition unit 120 is used for acquiring a three-dimensional acceleration signal of the pulse wave; the module management unit 130 is further included to provide power management, signal storage and transmission, and possible processing and display functions for the signal acquisition module 100, and to wirelessly transmit the acquired signals to the blood pressure calculation module 200 by means of bluetooth or the like.
As a miniature wearable device, the signal acquisition module 100 can be made as a stand-alone measurement device that is worn around a fingertip or a wrist.
The blood pressure calculation module 200 includes a feature extraction unit 210, a blood pressure calculation unit 220, and a parameter calculation unit 230, where the feature extraction unit 210 receives the PPG signal sent from the signal acquisition module 100, and extracts the following three features from the PPG signal: (1) normalized Slope Transit Time (NSTT), (2) minimum point of the descending derivative (PMDD), and (3) normalized tidal wave Peak (NPTW).
The feature extraction unit 210 first extracts the above three features. Fig. 2 is a diagram of the Normalized Slope Transit Time (NSTT) extracted from the photoplethysmograph signal of an embodiment of the present invention, as shown in fig. 2, the initial rising slope of the pulse wave is proportional to the transit time, and the slope is not affected by the heart rate and the ejection time, which is the physiological and elastohydrodynamic basis for calculating blood pressure by using the Slope Transit Time (STT) instead of PTT. The definition of STT is as follows:
where m is the maximum slope of the rising portion of the PPG and a is a constant arbitrary amplitude related to the PPG signal amplitude.
Because the amplitude of the PPG signal can be influenced by the sensitivity of the sensor, the wearing position, the wearing mode and the like, in order to improve the invariance of PPG characteristic measurement and slope transmission time STT, normalization processing is carried out:
where m is the maximum slope of the ascending portion of the PPG and H is the amplitude of the PPG. Δ a is proportional to H, so NSTT has invariance to PPG signal amplitude changes, greatly reducing the effect of sensor sensitivity and interference in other measurement processes.
In order to further improve the blood pressure estimation precision, the invention also provides two new PPG characteristic measures: a minimum point of the descending derivative (PMDD) and a normalized tidal wave Peak value (NPTW). The pulse wave is a superposition of a shock wave and a reflected wave of the blood flow pulse flowing in the blood vessel. The shock wave is formed by a straight-line increase in arterial blood flow caused by rapid pumping of blood after depolarization of the heart. The reflected wave contains two components, a tidal wave, which reflects the reflection of the blood pumped by the heart as it encounters the smaller branches of the arterial vessel, and a dicrotic wave, which is the reflected shockwave generated by the blood striking the arterial valve through the aorta.
Assuming that the other arterial parameters remain constant, the blood pressure increases and the Pulse Wave Velocity (PWV) will increase, resulting in faster pulse wave transmission and faster reflected waves encountering the shock wave, resulting in a tighter fusion of the two waves. The tidal wave will be closer to the peak and its amplitude will rise, i.e. the characteristic measure tidal wave peak value PTW increases. And for the dicrotic wave, it is also closer to the shockwave, resulting in a more advanced location of the falling edge of the dicrotic wave throughout the heart cycle, resulting in a decrease in the minimum point PMDD of the characteristic metric derivative.
Fig. 3 is a schematic diagram of an embodiment of the invention of extracting the minimum point of the descending derivative (PMDD) and the Normalized Peak Tidal Wave (NPTW) from the photoplethysmograph signal, as shown in fig. 3,
NPTW is defined as the height difference between the tidal wave (point B) and point F of PPG and the pulse wave height (H ═ H)A-hF) The ratio of (c) can be calculated by equation (3):
PMDD, defined as the time interval between the minimum point of the derivative of the falling band (point D) and the point F of the PPG, can be calculated as equation (4):
PMDD＝tD-tF (4)
after the three characteristics are extracted, the systolic pressure value and the diastolic pressure value of the blood pressure are calculated according to the characteristics, and parameters required by the systolic pressure value and the diastolic pressure value are calculated firstly before the systolic pressure value and the diastolic pressure value are calculated.
The personalized parameter calculating unit 230 in the blood pressure calculating module 200 firstly uses the standard beat-by-beat sphygmomanometer or invasive blood pressure measurement as the true value of the beat-by-beat blood pressure for the tested person, and simultaneously measures the PPG signal, processes and analyzes the PPG signal to obtain three feature metrics. Based on three characteristic metrics of 'true value' of beat-by-beat blood pressure and PPG, 8 personalized blood pressure calculation parameter values suitable for the measured person are learned by using a least square method.
The parameters in equations (5) (6) (7) and (8) are initialized using the least squares method.
θ＝(XTX)-1XTY (7)
Where the value with n subscripts represents the corresponding value in the nth initialization sample, θ is defined as equation (8). In general, n may be 4 to 10.
After completing the learning of the personalized blood pressure calculation parameters for enough tested persons, the parameter θ and the identity information of the corresponding tested user can be associated and stored in the data storage module, where the identity information is, for example: and the sex, age, height, weight, heart rate, blood pressure, diseases and other information of the detected user. With the storage module, for a certain tested user, when the personal information is input, the corresponding parameter θ can be found, and the blood pressure value can be calculated by sending the parameter to the blood pressure calculating unit 220.
Having obtained the required parameter θ, the blood pressure calculation unit 220 calculates the systolic pressure value and the diastolic pressure value according to the parameter and the extracted three features:
SBP＝a0HSTT+a1PMDD+a2PTW+a3 (9)
DBP＝b0HSTT+b1PMDD+b2PTW+b3 (10)
wherein SBP is systolic pressure, DBP is diastolic pressure, a0,a1,a2,a3,b0,b1,b2And b3Are parameters calculated by the parameter calculation unit 230.
Preferably, the parameter θ may be associated with identity information of the corresponding user to be tested, such as sex, age, height, weight, heart rate, blood pressure, disease, etc. of the user to be tested, and stored in the data storage module. Thus, for a certain tested user, the corresponding parameter θ can be found by inputting the personal information of the user, and the blood pressure value can be calculated by sending the parameter to the blood pressure calculating unit 220.
The application interaction module 300 includes an interaction unit 310, a blood pressure variability calculation unit 320, and a motion state analysis unit 330, wherein the motion state analysis unit 330 receives the three-dimensional acceleration signal sent by the acceleration signal acquisition unit 120, and determines whether the user to be tested is currently in a "motion" state or a "rest" state according to data in the signal, and labels the beat-by-beat blood pressure value sent by the blood pressure calculation unit 220 in the two states.
The blood pressure variability calculation unit 320 receives beat-by-beat blood pressure sequences labeled with { exercise, rest } labels from the exercise state analysis unit 330, and calculates the following blood pressure variability indexes in units of 5-minute length for blood pressure sequences with rest of 5 minutes and more continuously:
mean blood pressure (mean BP):
standard Deviation (SD):
coefficient of Variation (CV):
mean of actual variation (ARV):
mean independent Variation (VIM):
rate of change (ROC):
dynamic arteriosclerosis index (AASI):
and a nonlinear sample entropy index, which is calculated by the following steps:
(1) for the original blood pressure sequence y1,y2,…,yNDefine an m-dimensional vector: y ism(j)＝{yj,yj+1,…,yj+m-1Therein of
(2) Memory vector Ym(i) And Ym(j) A distance d betweenijIf the Chebyshev distance is used to quantify this distance, then there is dij＝maxk|yi+k,yj+k|,0≤k≤m-1。
(3) If a similar tolerance r is given, the distance d is counted accordinglyijThe number of the threshold r is less than or equal to the middle value and is marked as Pm(i) If this threshold condition is met, then the two vectors are considered similar (matching is successful).
(4) Definition of
The probability that two vectors match under the similarity threshold is represented by the probability mean of the number of successful matches.
(5) The number of dimensions is increased by 1, and the matching probability C in the m +1 dimension is obtained by the same method as abovem+1(r)。
(6) Finally, the sample entropy of this blood pressure sequence is:
the value of the sample entropy is mainly influenced by its parameters m, r and N. The general dimension m takes 1 or 2; and the similarity threshold r is 0.1 SD-0.25 SD to obtain better results.
The blood pressure variability is an important index for evaluating risk factors of patients with cardiovascular diseases and diabetes mellitus.
After calculating the blood pressure variability, the interaction unit 310 provides the measured user and the doctor with measurement and monitoring data, including: the blood pressure value sequence is shot by shot, the blood pressure sequence marked by { movement and rest }, the blood pressure variability index and corresponding measurement and monitoring reports are obtained, and meanwhile, a tested user can view related blood pressure data and analyze the reports by clicking a function button on the interaction unit.
The invention analyzes the flow of blood in blood vessels by an elastohydrodynamic method, measures pulse waves by a photoplethysmography, extracts three characteristics with high correlation degree with blood pressure from the pulse waves to calculate the blood pressure value, realizes beat-by-beat blood pressure measurement, improves the precision of the blood pressure measurement, can also judge the motion state of a measured user, calculates the blood pressure variability according to the motion state, and is an important index for evaluating risk coefficients of patients with cardiovascular diseases, diabetes and the like.
Fig. 4 is a schematic flow chart of a method for measuring beat-to-beat blood pressure based on photoplethysmography according to an embodiment of the present invention, as shown in fig. 4, the method includes:
s101, collecting photoplethysmography data and three-dimensional acceleration signals of pulse waves.
In some embodiments, photoplethysmography data and three-dimensional acceleration data of pulse waves are acquired and stored and displayed for blood pressure measurement.
S102, extracting preset characteristics related to blood pressure from the pulse wave signals, and calculating to obtain beat-to-beat blood pressure values according to the preset characteristics, wherein the preset characteristics comprise: normalized slope transit time, minimum point of the descending derivative and normalized tidal wave peak.
In some embodiments, three features of (1) Normalized Slope Transit Time (NSTT), (2) descending derivative minimum Point (PMDD), and (3) normalized tidal wave peak (NPTW) are extracted from acquired photoplethysmographic data, where the initial rising slope of the pulse wave is proportional to transit time, which is independent of heart rate and ejection time, which is the physiological and elastohydrodynamic basis for calculating blood pressure with Slope Transit Time (STT) instead of PTT. The definition of STT is as follows:
where m is the maximum slope of the rising portion of the PPG and a is a constant arbitrary amplitude related to the PPG signal amplitude.
Because the amplitude of the PPG signal can be influenced by the sensitivity of the sensor, the wearing position, the wearing mode and the like, in order to improve the invariance of PPG characteristic measurement and slope transmission time STT, normalization processing is carried out:
where m is the maximum slope of the ascending portion of the PPG and H is the amplitude of the PPG. Δ a is proportional to H, so NSTT has invariance to PPG signal amplitude changes, greatly reducing the effect of sensor sensitivity and interference in other measurement processes.
In order to further improve the blood pressure estimation precision, the invention also provides two new PPG characteristic measures: a minimum point of the descending derivative (PMDD) and a normalized tidal wave Peak value (NPTW). The pulse wave is a superposition of a shock wave and a reflected wave of the blood flow pulse flowing in the blood vessel. The shock wave is formed by a straight-line increase in arterial blood flow caused by rapid pumping of blood after depolarization of the heart. The reflected wave contains two components, a tidal wave, which reflects the reflection of the blood pumped by the heart as it encounters the smaller branches of the arterial vessel, and a dicrotic wave, which is the reflected shockwave generated by the blood striking the arterial valve through the aorta.
Assuming that the other arterial parameters remain constant, the blood pressure increases and the Pulse Wave Velocity (PWV) will increase, resulting in faster pulse wave transmission and faster reflected waves encountering the shock wave, resulting in a tighter fusion of the two waves. The tidal wave will be closer to the peak and its amplitude will rise, i.e. the characteristic measure tidal wave peak value PTW increases. And for the dicrotic wave, it is also closer to the shockwave, resulting in a more advanced location of the falling edge of the dicrotic wave throughout the heart cycle, resulting in a decrease in the minimum point PMDD of the characteristic metric derivative.
NPTW is defined as the height difference between the tidal wave (point B) and point F of PPG and the pulse wave height (H ═ H)A-hF) The ratio of (c) can be calculated by equation (3):
PMDD, defined as the time interval between the minimum point of the derivative of the falling band (point D) and the point F of the PPG, can be calculated as equation (4):
PMDD＝tD-tF (4)
after the three characteristics are extracted, the systolic pressure value and the diastolic pressure value of the blood pressure are calculated according to the characteristics, and parameters required by the systolic pressure value and the diastolic pressure value are calculated firstly before the systolic pressure value and the diastolic pressure value are calculated.
The desired parameters are learned by using a segment of known beat-to-beat blood pressure and corresponding PPG signal.
The parameters in equations (5) (6) (7) and (8) are initialized using the least squares method.
θ＝(XTX)-1XTY (7)
Where the value with n subscripts represents the corresponding value in the nth initialization sample, θ is defined as equation (8). In general, n may be 4 to 10.
Obtaining a required parameter theta, and calculating a systolic pressure value and a diastolic pressure value according to the parameter and the extracted features:
SBP＝a0HSTT+a1PMDD+a2PTW+a3 (9)
DBP＝b0HSTT+b1PMDD+b2PTW+b3 (10)
wherein SBP is systolic pressure, DBP is diastolic pressure, a0,a1,a2,a3,b0,b1,b2And b3Are the parameters calculated above.
S103, judging the motion state of the user to be detected according to the three-dimensional acceleration signal, labeling the beat-to-beat blood pressure values, and calculating the blood pressure variability of a beat-to-beat blood pressure value sequence in a resting state reaching or exceeding a preset time period.
In some embodiments, the acceleration signal is three-dimensional, and whether the detected user is currently in a "moving" state or a "resting" state is determined according to data in the signal, and the beat-to-beat blood pressure value calculated in the above embodiments is labeled in the two states. For beat-to-beat blood pressure sequences with a "rest" status label labeled therein and resting continuously for 5 minutes and above, the following blood pressure variability indices were calculated in units of 5 minutes length:
mean blood pressure (mean BP):
standard Deviation (SD):
coefficient of Variation (CV):
mean of actual variation (ARV):
mean independent Variation (VIM):
rate of change (ROC):
dynamic arteriosclerosis index (AASI):
and a non-linear sample entropy indicator. The calculation steps are as follows:
(1) for the original blood pressure sequence y1,y2,…,yNDefine an m-dimensional vector: y ism(j)＝{yj,yj+1,…,yj+m-1Therein of
(2) Memory vector Ym(i) And Ym(j) A distance d betweenijIf the Chebyshev distance is used to quantify this distance, then there is dij＝maxk|yi+k,yj+k|,0≤k≤m-1。
(3) If a similar tolerance r is given, the distance d is counted accordinglyijThe number of the threshold r is less than or equal to the middle value and is marked as Pm(i) If this threshold condition is met, then the two vectors are considered similar (matching is successful).
(4) Definition of
The probability that two vectors match under the similarity threshold is represented by the probability mean of the number of successful matches.
(5) Increasing the number of dimensions by 1, and obtaining the sameMatch probability C in m +1 dimensionm+1(r)。
(6) Finally, the sample entropy of this blood pressure sequence is:
the value of the sample entropy is mainly influenced by its parameters m, r and N. The general dimension m takes 1 or 2; and the similarity threshold r is 0.1 SD-0.25 SD to obtain better results.
The blood pressure variability is an important index for evaluating risk factors of patients with cardiovascular diseases and diabetes mellitus.
After calculating the blood pressure variability, providing the measured user and the doctor with measurement and monitoring data, including: the blood pressure value sequence is shot by shot, the blood pressure sequence marked by { movement and rest }, the blood pressure variability index and corresponding measurement and monitoring reports are obtained, and meanwhile, a tested user can view related blood pressure data and analyze the reports by clicking a function button on the interaction unit.
Those skilled in the art will appreciate that all or part of the steps to implement the above-described embodiments are implemented as programs (computer programs) executed by a computer data processing apparatus. When the computer program is executed, the method provided by the invention can be realized. Furthermore, the computer program may be stored in a computer readable storage medium, which may be a readable storage medium such as a magnetic disk, an optical disk, a ROM, a RAM, or a storage array composed of a plurality of storage media, such as a magnetic disk or a magnetic tape storage array. The storage medium is not limited to centralized storage, but may be distributed storage, such as cloud storage based on cloud computing.
The invention also provides a photoplethysmography-based beat-by-beat blood pressure measuring device, which is a wearable device and comprises the blood pressure measuring system in the embodiment, a signal acquisition module 100 of the device is a photoplethysmography pulse wave PPG and acceleration signal acquisition and transmission hardware device similar to a smart watch and is fixed at the finger or wrist of a user, and a blood pressure calculation module 200 and an application interaction module 300 serving as intelligent APP software are simplified into a personal-oriented beat-by-beat sphygmomanometer and are embedded into the smart watch.
Fig. 5 is a schematic diagram of a computer-readable recording medium of an embodiment of the present invention. As shown in fig. 5, the computer-readable recording medium stores therein a computer-executable program, which when executed, implements the photoplethysmography-based beat-to-beat blood pressure measurement method of the present invention as described above. The computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
The computer readable medium carries one or more programs which, when executed by a device, cause the computer readable medium to perform the functions of: collecting pulse wave signals; extracting preset characteristics related to blood pressure from the pulse wave signals, and calculating the blood pressure according to the preset characteristics; the blood pressure measurement is displayed and interacted with by the user.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
From the above description of the embodiments, those skilled in the art will readily appreciate that the present invention can be implemented by hardware capable of executing a specific computer program, such as the system of the present invention, and electronic processing units, servers, clients, mobile phones, control units, processors, etc. included in the system. The invention may also be implemented by computer software for performing the method of the invention. It should be noted, however, that the computer software for executing the method of the present invention is not limited to be executed by one or a specific hardware entity, but may also be implemented in a distributed manner by hardware entities without specific details, for example, some method steps executed by a computer program may be executed by a mobile client, and another part may be executed by a smart meter, a smart pen, or the like. For computer software, the software product may be stored in a computer readable storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or may be distributed over a network, as long as it enables the electronic device to perform the method according to the present invention.
In summary, the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that some or all of the functionality of some or all of the components in embodiments in accordance with the invention may be implemented in practice using a general purpose data processing device such as a microprocessor or a Digital Signal Processor (DSP). The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
While the foregoing embodiments have described the objects, aspects and advantages of the present invention in further detail, it should be understood that the present invention is not inherently related to any particular computer, virtual machine or electronic device, and various general-purpose machines may be used to implement the present invention. The invention is not to be considered as limited to the specific embodiments thereof, but is to be understood as being modified in all respects, all changes and equivalents that come within the spirit and scope of the invention.
Claims (8)
1. A beat-to-beat blood pressure measurement system based on photoplethysmography, comprising: a signal acquisition module, a blood pressure calculation module and an application interaction module, wherein,
the signal acquisition module is used for acquiring a photoplethysmography signal and an acceleration signal;
the blood pressure calculation module is configured to receive the photoplethysmography signal and extract a plurality of features associated with blood pressure from the photoplethysmography signal, the features including: the normalized slope transmission time, the minimum point of the descending derivative and the normalized tidal wave peak value are also used for acquiring personalized blood pressure calculation parameters according to the personal information of the user to be detected; calculating a beat-to-beat blood pressure value according to the personalized blood pressure calculation parameters and the three characteristics;
the application interaction module is used for judging the motion state of the detected user according to the three-dimensional acceleration signal, marking the motion state of the beat-by-beat blood pressure and calculating the blood pressure variability of the beat-by-beat blood pressure value sequence in the rest state reaching or exceeding a preset time period.
2. A photoplethysmography-based beat-to-beat blood pressure measurement system according to claim 1, characterized in that the signal acquisition module acquires the photoplethysmography signals and acceleration signals from a fingertip or a wrist of a tested user.
3. A photoplethysmography based beat-to-beat blood pressure measurement system according to claim 1,
the normalized slope transmission time calculation formula is as follows:
wherein NSTT is normalized slope transmission time, m is the maximum slope of the rising part of the photoplethysmography pulse wave, H is the amplitude of the photoplethysmography pulse wave, A is a constant arbitrary amplitude related to the amplitude of the photoplethysmography pulse wave, and t is time;
the normalized tidal wave peak value calculation formula is as follows:
wherein NPYW is normalized tidal wave crest value hBAnd hFThe height of the point B and the height of the point F of the photoplethysmography signal are respectively shown, and H is the amplitude of the photoplethysmography signal;
the calculation formula of the minimum point of the descending branch derivative is as follows: PMDD ═ tD-tFWhere PMDD is the minimum point of the reduced derivative, tDAnd tFRespectively, the time of the minimum point D and the time of the point F of the falling-band derivative of the photoplethysmographic pulse wave.
4. The photoplethysmography-based beat-to-beat blood pressure measurement system of claim 1, wherein the indicator of blood pressure variability comprises: mean blood pressure, standard deviation, coefficient of variation, actual mean of variation, mean-independent variation, rate of change, dynamic arteriosclerosis index, and sample entropy.
5. Photoplethysmography-based beat-by-beat blood pressure measurement system according to claim 1, characterized in that the beat-by-beat blood pressure values comprise systolic and diastolic pressure values.
6. A beat-to-beat blood pressure measurement method based on photoplethysmography is characterized by comprising the following steps:
acquiring photoplethysmography data and three-dimensional acceleration signals of the pulse waves;
extracting preset characteristics related to blood pressure from the pulse wave signals, and calculating to obtain beat-to-beat blood pressure values according to the preset characteristics, wherein the preset characteristics comprise: normalized slope transmission time, minimum point of the descending derivative and normalized tidal wave peak value;
and judging the motion state of the detected user according to the three-dimensional acceleration signal, labeling the beat-by-beat blood pressure values, and calculating the blood pressure variability of a beat-by-beat blood pressure value sequence in a rest state reaching or exceeding a preset time period.
7. A beat-to-beat blood pressure measuring device based on photoplethysmography is characterized in that,
the device is a smart wearable device comprising the blood pressure measurement system of any one of claims 1-5, wherein the signal acquisition module is disposed in a fingertip sleeve or a smart watch of the wearable device; the blood pressure calculation module and the application interaction module are arranged in embedded software of the wearable device, and are used for measuring and monitoring beat-to-beat blood pressure, analyzing the measured blood pressure and the variation index thereof, issuing a measurement and monitoring report, and uploading data to a server to-be-measured user.
8. A computer-readable medium storing a computer-executable program, wherein the computer-executable program, when executed, implements the method of claim 6.
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