CN110495863B - Method and device for identifying characteristic points of radial artery pressure waveform central isthmus - Google Patents
Method and device for identifying characteristic points of radial artery pressure waveform central isthmus Download PDFInfo
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- CN110495863B CN110495863B CN201811168957.1A CN201811168957A CN110495863B CN 110495863 B CN110495863 B CN 110495863B CN 201811168957 A CN201811168957 A CN 201811168957A CN 110495863 B CN110495863 B CN 110495863B
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/021—Measuring pressure in heart or blood vessels
- A61B5/02108—Measuring pressure in heart or blood vessels from analysis of pulse wave characteristics
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7225—Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/725—Details of waveform analysis using specific filters therefor, e.g. Kalman or adaptive filters
Abstract
The application discloses a method and a device for identifying characteristic points of a radial artery pressure waveform central isthmus. The method comprises the following steps: filtering the radial pulse waveform; generating a differential signal of the radial pulse waveform, and determining a maximum value of the differential signal; determining a starting point of the radial pulse waveform based on a maximum of the differential signal; determining a period of the radial pulse waveform based on the starting point; performing baseline wandering processing on the radial pulse waveform based on the starting point and calibrating the waveform; and identifying the identified clipping feature points of the waveform. The method reduces the processing process of the pulse waveform data to a certain extent, reduces the consumption of computing resources, is easier to extract the waveform characteristic points, and makes the subsequent analysis processing process by using the pulse waveform more convenient.
Description
Technical Field
The application relates to the field of waveform detection, in particular to a method and a device for identifying characteristic points of a radial artery pressure waveform central isthmus.
Background
In the current society, with the continuous development of the times, the living standard of people is continuously improved, and more people pay more attention to the self health condition. Non-infectious chronic diseases in China become the first problem of hindering health, cardiovascular diseases are ranked first, and the morbidity and mortality of the cardiovascular diseases become the first causes of common diseases and fatalities of urban and rural people in China. Therefore, how to detect and prevent cardiovascular diseases becomes a problem of great concern.
People in daily life generally know their health by measuring blood pressure. There are two common measurement methods, direct and indirect, in which direct measurement is an invasive continuous measurement method, and is commonly used in the implementation of hospital surgery. The indirect measurement is to measure the blood pressure indirectly through parameters such as artery blood vessel wall fluctuation, blood volume change and the like, generally adopts an auscultation method or an oscillography, has mature technology and is widely applied in clinical environment. The pulse wave of the upper arm, wrist, brachial artery or radial artery of the human body is measured by using a related instrument, and the blood pressure value is obtained by analyzing and calculating the pulse wave.
The method comprises the steps of collecting human body radial artery pulse wave signals through a photoelectric sensor, carrying out filtering amplification and AD conversion on the signals by using a microprocessor to reduce noise, then carrying out frequency domain transformation, wavelet processing and second-order difference to determine characteristic points of human body radial artery pulse wave waveforms, calculating accurate numerical values of human body radial artery pulse wave conduction time, establishing a regression equation for measuring blood pressure, and finally obtaining blood pressure values. The processing method adopted when the waveform characteristics are obtained by the method is complex and tedious, and more hardware resources are consumed, so that a method which can be used for extracting the characteristic point parameters more easily is needed, and the subsequent analysis and processing process is facilitated.
Disclosure of Invention
It is an object of the present application to overcome the above problems or to at least partially solve or mitigate the above problems.
According to one aspect of the present application, there is provided a method of identifying a characteristic point of a radial artery pressure waveform depression central isthmus, comprising:
a filtering step: filtering the radial pulse waveform;
a differential signal generation step: generating a differential signal of the radial pulse waveform, and determining a maximum value of the differential signal;
a starting point searching step: determining a starting point of the radial pulse waveform based on a maximum of the differential signal;
a period determining step: determining a period of the radial pulse waveform based on the starting point;
waveform calibration: performing baseline wandering processing on the radial pulse waveform based on the starting point and calibrating the waveform;
a characteristic point identification step: and identifying the characteristic points of the central isthmus of the calibrated waveform.
The method solves the problem of great limitation existing in the existing measurement method, namely the method needs to perform frequency domain transformation, wavelet processing and second-order difference on the obtained human body radial artery pulse wave data to determine the characteristic points of the human body radial artery pulse wave waveform, the data processing process is complex, and more hardware computing resources are occupied. The method provided by the application utilizes a specific two-dimensional group to carry out convolution filtering processing on the pulse waveform; then, a first-order difference method is adopted to obtain a maximum value point; after baseline drift of the radial pulse waveform is removed and the waveform is calibrated, finally, searching is carried out in a corresponding waveform period area according to different pulse periods, and therefore the central isthmus F point is determined. The data processing method reduces the processing process of the pulse waveform data to a certain extent, reduces the consumption of computing resources, is easier to extract the waveform characteristic points, and makes the subsequent analysis processing process by using the pulse waveform more convenient.
Optionally, the smoothing filtering step includes: and performing convolution filtering processing on the radial pulse waveform and a preset two-dimensional array.
Optionally, in the differential signal generating step, the calculation formula for generating the differential signal is:
vtCpDifSig[i]＝vtSmoothedData[i+1]-vtSmoothedData[i-1]+2*(vtSmoothedData[i+2]-vtSmoothedData[i-2])
wherein vtCpDifSig represents a differential signal; vtsmootheneddata represents the filtered radial pulse waveform; i is an outer loop variable representing the ith bit signal value.
The method adopts a mathematical calculation mode to calculate the differential signal, can realize operation without adopting hardware of a differential circuit, and is convenient, quick, simple and realizable.
Optionally, in the differential signal generating step, the method for determining the waveform maximum value includes:
and (3) a step of segmented searching: dividing the differential signal waveform into eight sections, and respectively searching a maximum value point of each section of waveform;
and an average value calculation step: calculating an average value AvgSegmentMax of maximum values of the eight sections of waveforms; and
a maximum value determining step: and searching a maximum value point in the whole differential signal waveform, and determining the value of the maximum value point as the maximum value point of the differential signal under the condition that the amplitude of the maximum value point is greater than 0.6 AvgSegmentMax.
By adopting the method, the maximum value is searched in a segmented mode, the operation speed can be improved in a parallel processing mode, the obtained average value of the maximum value can be used as a threshold value to judge the maximum value of the whole waveform, and the judgment accuracy is improved.
Optionally, the starting point searching step includes: determining a search area based on the maximum value point of the differential signal, searching a forward zero crossing point in the search area, and taking the zero crossing point as a waveform starting point under the condition that the forward zero crossing point exists; otherwise, the minimum value point is used as the starting point of the waveform.
Optionally, in the period determining step, the waveform period is determined by calculating a distance difference between two starting points, and the waveform period is calculated by:
m_vtPeriod[i]＝m_vtFootPos[i]-m_vtFootPos[i-1]
wherein m _ vtPeriod is a waveform period; m _ vtFootPos is used as a starting point; i is an outer loop variable representing the ith bit signal value.
Due to the adoption of the technical scheme, compared with the prior art, the method and the device reduce the processing process of pulse waveform data to a certain extent, reduce the consumption of computing resources, and are easier to extract waveform characteristic points, so that the subsequent analysis processing process of utilizing pulse waveforms is more convenient.
Optionally, in the waveform calibration step, a baseline wander process is performed according to a slope of the waveform start point value and a waveform offset, where the slope is calculated by:
the waveform offset calculation formula is as follows:
ΔvtSlope＝vtSlope[i]*(j-m_vtFootPos[i])
the waveform after baseline wander removal processing is:
Normalization[j]＝vtSmoothedData[j]-vtSmoothedData[m_vtFootPos[i]]-ΔvtSlope
wherein vtSlope represents the slope; Δ vtSlope represents the waveform offset; vtsmootheneddata represents the filtered radial pulse waveform; m _ vtFootPos is used as a starting point; i is an outer loop variable and represents the ith signal value; j is an inner loop variable.
Due to the adoption of the technical scheme, compared with the prior art, the method and the device reduce the processing process of pulse waveform data to a certain extent, reduce the consumption of computing resources, and are easier to extract waveform characteristic points, so that the subsequent analysis processing process of utilizing pulse waveforms is more convenient.
Optionally, the feature point identifying step includes: determining a region for searching for the characteristic point of the central isthmus according to the waveform period, and taking the minimum value point near the zero crossing point as the characteristic point of the central isthmus under the condition that the positive zero crossing point of the differential signal exists in the region; and under the condition that no zero crossing point exists, taking the maximum value point of the curvature signal in the region as the characteristic point of the central notch.
Optionally, the calculation formula of the curvature signal is:
wherein vtsmootheneddata represents the filtered radial pulse waveform; vtSecDrtSig represents the second order differential signal of the radial pulse waveform, and i represents the ith signal value.
Another aspect of the present application provides an apparatus for identifying a radial artery pressure waveform centromere feature point, comprising:
a filtering module configured to perform filtering processing on a radial artery pulse waveform;
a differential signal generation module configured to generate a differential signal of the radial pulse waveform, determine a maximum of the differential signal;
a starting point search module configured to determine a starting point of the radial pulse waveform based on a maximum value of the differential signal;
a period determination module configured to determine a period of the radial pulse waveform based on the starting point;
a waveform calibration module configured to perform de-baseline wander processing on the radial pulse waveform and calibrate a waveform based on the starting point;
a feature point identification module configured to identify a isthmus feature point of the calibrated waveform.
The device reduces the processing process of pulse waveform data to a certain extent, reduces the consumption of computing resources, is easier to extract waveform characteristic points, and makes the subsequent analysis processing process of utilizing pulse waveforms more convenient.
The above and other objects, advantages and features of the present application will become more apparent to those skilled in the art from the following detailed description of specific embodiments thereof, taken in conjunction with the accompanying drawings.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. Some specific embodiments of the present application will be described in detail hereinafter by way of illustration and not limitation with reference to the accompanying drawings. The same reference numbers in the drawings identify the same or similar elements or components. Those skilled in the art will appreciate that the drawings are not necessarily drawn to scale. In the drawings:
FIG. 1 is a schematic diagram of a hardware configuration of a computer device for performing a method for identifying isthmus feature points in a radial artery pressure waveform drop according to an embodiment of the present application;
FIG. 2 is a schematic flow chart diagram of a method of identifying a radial artery pressure waveform drop isthmus feature point according to one embodiment of the present application;
FIG. 3 is a schematic flow chart diagram of a method of identifying isthmus feature points in a radial artery pressure waveform drop according to another embodiment of the present application;
FIG. 4 is a schematic flow chart diagram of a method of identifying isthmus feature points in a radial artery pressure waveform drop according to another embodiment of the present application;
FIG. 5 is a schematic diagram of the location of the isthmus F-point on the radial pulse waveform in an embodiment of the present application;
FIG. 6 is a schematic block diagram of an apparatus for identifying isthmus feature points in a radial artery pressure waveform drop according to an embodiment of the present application;
FIG. 7 is a block diagram of one embodiment of a computing device of the present application;
FIG. 8 is a block diagram of one embodiment of a computer-readable storage medium of the present application.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
There is also provided, in accordance with an embodiment of the present application, an embodiment of a method of identifying isthmus feature points in a radial artery pressure waveform drop, it should be noted that the steps illustrated in the flowchart of the accompanying drawings may be performed in a computer system such as a set of computer-executable instructions and that, although a logical ordering is illustrated in the flowchart, in some cases, the steps illustrated or described may be performed in an order different than here.
The method provided by the first embodiment of the present application may be executed in a mobile terminal, a computer terminal, or a similar computing device. Fig. 1 is a schematic diagram of a hardware configuration of a computer device for executing a method for identifying a characteristic point of a central notch in a radial artery pressure waveform drop according to an embodiment of the application. As shown in fig. 1, computer apparatus 10 (or mobile device 10) may include one or more processors (shown as 102a, 102b, … …, 102n, which may include, but are not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data, and a transmission module for communication functions. Besides, the method can also comprise the following steps: a display, an input/output interface (I/O interface), a Universal Serial Bus (USB) port (which may be included as one of the ports of the I/O interface), a network interface, a power source, and/or a camera. It will be understood by those skilled in the art that the structure shown in fig. 1 is only an illustration and is not intended to limit the structure of the electronic device. For example, computer device 10 may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.
It should be noted that the one or more processors and/or other data processing circuitry described above may be referred to generally herein as "data processing circuitry". The data processing circuitry may be embodied in whole or in part in software, hardware, firmware, or any combination thereof. Further, the data processing circuit may be a single stand-alone processing module, or incorporated in whole or in part into any of the other elements in the computer apparatus 10 (or mobile device). As referred to in the embodiments of the application, the data processing circuit acts as a processor control (e.g. selection of a variable resistance termination path connected to the interface).
The memory 104 can be used for storing software programs and modules of application software, such as program instructions/data storage devices corresponding to the methods in the embodiments of the present application, and the processor executes various functional applications and data processing by executing the software programs and modules stored in the memory 104, that is, implementing the methods of the application programs described above. The memory 104 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, memory 104 may further include memory located remotely from the processor, which may be connected to computer device 10 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of computer device 10. In one example, the transmission device includes a Network adapter (NIC) that can be connected to other Network devices through a base station to communicate with the internet. In one example, the transmission device may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.
The display may be, for example, a touch screen type Liquid Crystal Display (LCD) that may enable a user to interact with a user interface of the computer device 10 (or mobile device).
Under the operating environment, the application provides a method for identifying characteristic points of a radial artery pressure waveform, in particular to F points of isthmus characteristic points. Fig. 2 is a schematic flow chart of a method of identifying isthmus feature points in a radial artery pressure waveform drop according to an embodiment of the present application. The method may comprise the steps of:
s100, a filtering step: filtering the radial pulse waveform;
s200 differential signal generation step: generating a differential signal of the radial pulse waveform, and determining a maximum value of the differential signal;
s300, a starting point searching step: determining a starting point of the radial pulse waveform based on a maximum of the differential signal;
s400, period determination: determining a period of the radial pulse waveform based on the starting point;
s500, waveform calibration: performing baseline wandering processing on the radial pulse waveform based on the starting point and calibrating the waveform;
s600, feature point identification: and identifying the characteristic points of the central isthmus of the calibrated waveform.
The method solves the problem of great limitation in the existing measurement method, namely the method needs to perform frequency domain transformation, wavelet processing and second-order difference on the obtained human body radial artery pulse wave data to determine the characteristic points of the human body radial artery pulse wave waveform, the data processing process is complex, and more hardware computing resources are occupied. The method provided by the application utilizes a specific two-dimensional group to carry out convolution filtering processing on the pulse waveform; then, a first-order difference method is adopted to obtain a maximum value point; after baseline drift of the radial pulse waveform is removed and the waveform is calibrated, finally, searching is carried out in a corresponding waveform period area according to different pulse periods, and therefore the central isthmus F point is determined. The data processing method reduces the processing process of the pulse waveform data to a certain extent, reduces the consumption of computing resources, is easier to extract the waveform characteristic points, and makes the subsequent analysis processing process by using the pulse waveform more convenient.
Fig. 3 is a schematic flow chart diagram of a method of identifying isthmus feature points in a radial artery pressure waveform drop according to another embodiment of the present application. Optionally, the smoothing filtering step includes: and performing convolution filtering processing on the radial pulse waveform and a preset two-dimensional array. For example, the array may be an 11 x 14 two dimensional array: QG [11] [14 ]. And performing convolution filtering processing on the pulse waveform and the filter coefficient to obtain a filtered pulse waveform.
Wherein, each element in the specific two-dimensional array QG [11] [14] can be a specific numerical value as shown in the following table one:
watch 1
| 35 | 17 | 12 | -3 | ||||||||||
| 21 | 7 | 6 | 3 | -2 | |||||||||
| 231 | 59 | 54 | 39 | 14 | -21 | ||||||||
| 429 | 89 | 84 | 69 | 44 | 9 | -21 | |||||||
| 143 | 25 | 24 | 21 | 16 | 9 | 0 | -11 | ||||||
| 1105 | 167 | 162 | 147 | 122 | 87 | 42 | -13 | -78 | |||||
| 323 | 43 | 42 | 39 | 34 | 27 | 18 | 7 | -6 | 21 | ||||
| 2261 | 269 | 264 | 249 | 224 | 189 | 144 | 89 | 24 | -51 | -136 | |||
| 3059 | 329 | 324 | 309 | 284 | 249 | 204 | 149 | 84 | 9 | -76 | -171 | ||
| 8059 | 79 | 78 | 75 | 70 | 63 | 54 | 43 | 30 | 15 | -2 | -21 | -42 | |
| 5175 | 467 | 462 | 447 | 422 | 387 | 322 | 287 | 222 | 147 | 62 | -33 | -138 | -253 |
Referring to fig. 2 and 3, optionally, in the differential signal generating step, the calculation formula for generating the differential signal is as follows:
vtCpDifSig[i]＝vtSmoothedData[i+1]-vtSmoothedData[i-1]+2*(vtSmoothedData[i+2]-vtSmoothedData[i-2])
wherein vtCpDifSig represents a differential signal; vtsmootheneddata represents the filtered radial pulse waveform; i is an outer loop variable representing the ith bit signal value.
The method adopts a mathematical calculation mode to calculate the differential signal, can realize operation without adopting hardware of a differential circuit, and is convenient, quick, simple and realizable.
Optionally, in the differential signal generating step, the method for determining the waveform maximum value includes:
and (3) a step of segmented searching: dividing the differential signal waveform into eight sections, and respectively searching a maximum value point of each section of waveform;
and an average value calculation step: calculating an average value AvgSegmentMax of maximum values of the eight sections of waveforms; and
a maximum value determining step: and searching a maximum value point in the whole differential signal waveform, and determining the value of the maximum value point as the maximum value point of the differential signal under the condition that the amplitude of the maximum value point is greater than 0.6 AvgSegmentMax.
By adopting the method, the maximum value is searched in a segmented mode, the operation speed can be improved in a parallel processing mode, the obtained average value of the maximum value can be used as a threshold value to judge the maximum value of the whole waveform, and the judgment accuracy is improved.
Optionally, the starting point searching step includes: determining a search area based on the maximum value point of the differential signal, searching a forward zero crossing point in the search area, and taking the zero crossing point as a waveform starting point under the condition that the forward zero crossing point exists; otherwise, the minimum value point is used as the starting point of the waveform. The minimum value point calculation method comprises the following steps: and finding the point with the minimum amplitude value in the search area as the minimum value point. The process of determining the starting point by the difference signal maximum value point is as follows: searching forward for 200ms through a maximum value point (generally occurring after the starting point) of the differential signal to determine a search area, wherein the search area is used as a waveform starting point when a forward zero crossing point of the differential signal occurs; when there is no forward zero crossing point, the minimum point of the search area is taken as a starting point.
Referring to fig. 2 and 3, optionally, in the period determining step, the waveform period is determined by calculating a distance difference between two starting points, and the waveform period is calculated by:
m_vtPeriod[i]＝m_vtFootPos[i]-m_vtFootPos[i-1]
wherein m _ vtPeriod is a waveform period; m _ vtFootPos is used as a starting point; i is an outer loop variable representing the ith bit signal value.
Due to the adoption of the technical scheme, compared with the prior art, the method and the device reduce the processing process of pulse waveform data to a certain extent, reduce the consumption of computing resources, and are easier to extract waveform characteristic points, so that the subsequent analysis processing process of utilizing pulse waveforms is more convenient.
Optionally, after the period determining step, the method further includes the peak point determining step, which includes searching for a waveform maximum point in an interval from the starting point to 2/3 of the period, and using the waveform maximum point as the peak point.
The method searches the maximum point of the waveform in the interval from the starting point to 2/3 of the period, so that the number of data processing can be reduced, and the calculation speed can be improved.
Optionally, in the waveform calibration step, a baseline wander process is performed according to a slope of the waveform start point value and a waveform offset, where the slope is calculated by:
the waveform offset calculation formula is as follows:
ΔvtSlope＝vtSlope[i]*(j-m_vtFootPos[i])
the waveform after baseline wander removal processing is:
Normalization[j]＝vtSmoothedData[j]-vtSmoothedData[m_vtFootPos[i]]-ΔvtSlope
wherein vtSlope represents the slope; Δ vtSlope represents the waveform offset; vtsmootheneddata represents the filtered radial pulse waveform; m _ vtFootPos is used as a starting point; i is an outer loop variable and represents the ith signal value; j is an inner loop variable.
Due to the adoption of the technical scheme, compared with the prior art, the method and the device reduce the processing process of pulse waveform data to a certain extent, reduce the consumption of computing resources, and are easier to extract waveform characteristic points, so that the subsequent analysis processing process of utilizing pulse waveforms is more convenient.
Optionally, in one embodiment, the waveform scaling is scaling the amplitude of the radial artery waveform to have blood pressure units based on the systolic and diastolic pressures of the brachial artery.
Optionally, the feature point identifying step includes: determining a region for searching for the characteristic point of the central isthmus according to the waveform period, and taking the minimum value point near the zero crossing point as the characteristic point of the central isthmus under the condition that the positive zero crossing point of the differential signal exists in the region; and under the condition that no zero crossing point exists, taking the maximum value point of the curvature signal in the region as the characteristic point of the central notch.
Fig. 4 is a schematic flow chart diagram of a method of identifying isthmus feature points in a radial artery pressure waveform drop according to another embodiment of the present application. For example, the pulse periods can be divided into three cases according to different sizes, and the search area in each case is different; the isthmus F-point is then determined based on whether there is a differential signal positive zero crossing: if the minimum value point exists, searching a region 15ms before and after the zero crossing point as an F point, and if the minimum value point does not exist, searching a curvature signal maximum value point in the region according to a related calculation formula as the F point. And finally obtaining the fj point of the central isthmus of the waveform.
(1) When the waveform period is between 625ms and 925ms, searching an F point in a region from 0.32 waveform period to 0.5 waveform period; when a positive zero crossing point of the differential signal exists, searching a minimum value point in a region 15ms before and after the zero crossing point as an F point; if no zero crossing point exists, searching a curvature signal maximum value point as an F point;
(2) when the waveform period is more than 925ms, searching an F point in a region from 0.28 waveform periods to 0.45 waveform periods; when a positive zero crossing point of the differential signal exists, searching a minimum value point of a region in the front 15ms and the back 15ms of the zero crossing point as an F point; if no zero crossing point exists, searching a curvature signal maximum value point as an F point;
(3) when the waveform period is less than 625ms, searching an F point in a region from 0.36 waveform periods to 0.52 waveform periods; when a positive zero crossing point of the differential signal exists, searching a minimum value point in the front and rear 15ms areas as an F point by using the zero crossing point; when there is no positive zero crossing of the differential signal, the curvature signal maximum point is searched for as the F point.
The calculation formula of the curvature signal is as follows:
wherein vtsmootheneddata represents the filtered radial pulse waveform; vtSecDrtSig represents the second order differential signal of the radial pulse waveform, and i represents the ith signal value.
FIG. 5 is a schematic diagram of the location of the isthmus F-point on the radial pulse waveform in an embodiment of the present application. The figure contains a complete single cycle radial pulse waveform consisting primarily of ascending and descending branches. Ascending branches and descending branches form a main wave 1, an incision on the descending branches is called as the descending isthmus 3, and a severe pre-pulsation wave 2, also called as an tidal wave, often appears between the main wave 1 and the descending isthmus 3. The severe beat wave 4, also called the descending central wave, appears next to the descending central isthmus 3. Both the above-mentioned waves and isthmus are the main components constituting the pulse wave.
Specifically, the point B of the dominant wave 1 trough is an aortic opening point, which represents a pressure turning point at which the aortic valve begins to open and marks the beginning of the rapid ejection period of the heart; point C is the peak of the main wave 1, which is the highest point of the aortic pressure and represents the highest point of the systolic arterial pressure; the F point is the descending isthmus 3 valley point, which represents the left ventricular diastolic starting point, and is a downward apodization wave formed by the descending branch of the main wave 1 and the ascending branch of the dicrotic wave 4. When the smooth muscle of the arterial wall of the human body is less and the elastic fiber is more, the main wave C of the formed pulse wave is high and sharp, and the wave trough F of the dicrotic wave 4 is obvious because of the high blood reflux impact strength. On the contrary, the smooth muscle of the artery wall is increased, the elastic fiber of the artery wall is less, the wave velocity of the reflected wave is increased, the wave trough F of the dicrotic wave 4 is gradually increased and close to the wave crest C of the main wave 1, and finally fusion in different degrees is presented. Therefore, the fluctuation change of the pulse wave characteristic points can reflect the change of the resistance of the blood vessels and the elasticity of the blood vessel walls of the human body.
Example 2
According to the embodiment of the application, a device for identifying characteristic points of the central isthmus in radial artery pressure waveform reduction is further provided, and the device corresponds to the method in embodiment 1. Fig. 6 is a schematic block diagram of an apparatus for identifying isthmus feature points in a radial artery pressure waveform drop according to an embodiment of the present application. The apparatus may include:
a filtering module 100 configured to perform filtering processing on a radial artery pulse waveform;
a differential signal generation module 200 configured to generate a differential signal of the radial pulse waveform, determine a maximum of the differential signal;
a starting point search module 300 configured to determine a starting point of the radial pulse waveform based on a maximum value of the differential signal;
a period determination module 400 configured to determine a period of the radial pulse waveform based on the starting point;
a waveform calibration module 500 configured for de-baseline wander processing and waveform calibration of the radial pulse waveform based on the starting point;
a feature point identification module 600 configured to identify a isthmus feature point of the calibrated waveform.
The device uses a specific two-dimensional group to carry out convolution filtering processing on the pulse waveform; then, a first-order difference method is adopted to obtain a maximum value point; after baseline drift of the radial pulse waveform is removed and the waveform is calibrated, finally, searching is carried out in a corresponding waveform period area according to different pulse periods, and therefore the central isthmus F point is determined. The data processing method reduces the processing process of the pulse waveform data to a certain extent, reduces the consumption of computing resources, is easier to extract the waveform characteristic points, and makes the subsequent analysis processing process by using the pulse waveform more convenient.
Optionally, in the differential signal generating module, the calculation formula for generating the differential signal is:
vtCpDifSig[i]＝vtSmoothedData[i+1]-vtSmoothedData[i-1]+2*(vtSmoothedData[i+2]-vtSmoothedData[i-2])
wherein vtCpDifSig represents a differential signal; vtsmootheneddata represents the filtered radial pulse waveform; i is an outer loop variable representing the ith bit signal value.
The device adopts the mode of mathematical computation to calculate the differential signal, and can realize the operation without adopting the hardware of a differential circuit, thereby being convenient, rapid and simple to realize.
Optionally, the differential signal generating module includes:
a segment searching module configured to divide the differential signal waveform into eight segments, and search for a maximum value point of each segment waveform respectively;
an average value calculating module configured to calculate an average value AvgSegmentMax of maxima of the eight-segment waveform;
a maximum determination module configured to search for a maximum point within the entire differential signal waveform, determine a value of the maximum point as the maximum point of the differential signal waveform if the magnitude of the maximum point is greater than 0.6 at AvgSegmentMax.
By adopting the device, the maximum value is searched in a segmented mode, the operation speed can be improved in a parallel processing mode, the obtained average value of the maximum value can be used as a threshold value to judge the maximum value of the whole waveform, and the judgment accuracy is improved.
Optionally, the starting point searching module is further configured to: determining a forward zero-crossing point search area based on the maximum value point of the differential signal, searching in the search area, and taking the zero-crossing point as a waveform starting point under the condition that the forward zero-crossing point exists; otherwise, the minimum value point is used as the starting point of the waveform.
Optionally, in the period determining module, the waveform period is determined by calculating a distance difference between two starting points, and the waveform period is calculated by:
m_vtPeriod[i]＝m_vtFootPos[i]-m_vtFootPos[i-1]
wherein m _ vtPeriod is a waveform period; m _ vtFootPos is used as a starting point; i is an outer loop variable representing the ith bit signal value.
Due to the adoption of the technical scheme, compared with the prior art, the method and the device reduce the processing process of pulse waveform data to a certain extent, reduce the consumption of computing resources, and are easier to extract waveform characteristic points, so that the subsequent analysis processing process of utilizing pulse waveforms is more convenient.
Optionally, after the period determining module, the apparatus may further include the peak point determining module further configured to search for a waveform maximum point in an interval from the starting point to 2/3 of the period, and use the waveform maximum point as the peak point.
The device can reduce the number of data processing and improve the calculation speed by searching the maximum value point of the waveform in the interval from the starting point to 2/3 of the period.
Optionally, in the waveform calibration module, the baseline wander is removed according to a slope of the waveform start point value and a waveform offset, where the slope is calculated by:
the waveform offset calculation formula is as follows:
ΔvtSlope＝vtSlope[i]*(j-m_vtFootPos[i])
the waveform after baseline wander removal processing is:
Normalization[j]＝vtSmoothedData[j]-vtSmoothedData[m_vtFootPos[i]]-ΔvtSlope
wherein vtSlope represents the slope; Δ vtSlope represents the waveform offset; vtsmootheneddata represents the filtered radial pulse waveform; m _ vtFootPos is used as a starting point; i is an outer loop variable and represents the ith signal value; j is an inner loop variable.
Optionally, in one embodiment, the waveform scaling is scaling the amplitude of the radial artery waveform to have blood pressure units based on the systolic and diastolic pressures of the brachial artery.
Optionally, the feature point identification module is configured to: determining a region for searching for the characteristic point of the central isthmus according to the waveform period, and taking the minimum value point near the zero crossing point as the characteristic point of the central isthmus under the condition that the positive zero crossing point of the differential signal exists in the region; and under the condition that no zero crossing point exists, taking the maximum value point of the curvature signal as the characteristic point of the central notch.
The calculation formula of the curvature signal is as follows:
wherein vtsmootheneddata represents the filtered radial pulse waveform; vtSecDrtSig represents the second order differential signal of the radial pulse waveform, and i represents the ith signal value.
Due to the adoption of the technical scheme, compared with the prior art, the method and the device reduce the processing process of pulse waveform data to a certain extent, reduce the consumption of computing resources, and are easier to extract waveform characteristic points, so that the subsequent analysis processing process of utilizing pulse waveforms is more convenient.
The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present application, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one type of division of logical functions, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Example 3
An aspect of an embodiment of the present application provides a computing device. Referring to fig. 7, the computing device comprises a memory 1120, a processor 1110 and a computer program stored in said memory 1120 and executable by said processor 1110, the computer program being stored in a space 1130 for program code in the memory 1120, the computer program, when executed by the processor 1110, realizing means for performing any one of the above-mentioned method steps 1131 according to the present application.
An aspect of embodiments of the present application also provides a computer-readable storage medium. Referring to fig. 8, the computer readable storage medium comprises a storage unit for program code provided with a program 1131' for performing one of the above-mentioned method steps according to the present application, which program is executed by a processor.
An aspect of an embodiment of the present application also provides a computer program product containing instructions, including computer readable code, which when executed by a computing device, causes the computing device to perform the method as described above.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed by a computer, cause the computer to perform, in whole or in part, the procedures or functions described in accordance with the embodiments of the application. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk (ssd)), among others.
Those of skill would further appreciate that the various illustrative components and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It will be understood by those skilled in the art that all or part of the steps in the method for implementing the above embodiments may be implemented by a program which may be stored in a computer-readable storage medium, where the storage medium is a non-transitory medium, such as a random access memory, a read only memory, a flash memory, a hard disk, a solid state disk, a magnetic tape, a floppy disk, an optical disk, and any combination thereof.
The above description is only for the preferred embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (7)
1. A method of identifying a radial artery pressure waveform centromere feature point, comprising:
a filtering step: filtering the radial pulse waveform;
a differential signal generation step: generating a differential signal of the radial pulse waveform, and determining a maximum value of the differential signal;
a starting point searching step: determining a starting point of the radial pulse waveform based on a maximum of the differential signal;
a period determining step: determining a period of the radial pulse waveform based on the starting point;
waveform calibration: performing baseline-removing drift processing on the radial pulse waveform based on the starting point and calibrating the waveform; and
a characteristic point identification step: identifying the central isthmus-reducing characteristic points of the calibrated waveform;
wherein, in the differential signal generating step, the method of determining the waveform maximum value includes:
and (3) a step of segmented searching: dividing the differential signal waveform into eight sections, and respectively searching a maximum value point of each section of waveform;
and an average value calculation step: calculating an average value AvgSegmentMax of maximum values of the eight sections of waveforms; and
a maximum value determining step: searching a maximum value point in the whole differential signal waveform, and determining the value of the maximum value point as the maximum value point of the differential signal under the condition that the amplitude of the maximum value point is greater than 0.6 × AvgSegmentMax;
in the differential signal generating step, a calculation formula of the differential signal generation is:
vtCpDifSig[i]＝vtSmoothedData[i+1]-vtSmoothedData[i-1]+2*(vtSmoothedData[i+2]-vtSmoothedData[i-2])
wherein vtCpDifSig represents a differential signal; vtsmootheneddata represents the filtered radial pulse waveform; i is an outer loop variable and represents the ith signal value;
wherein the feature point identifying step includes: determining a region for searching for the characteristic point of the central isthmus according to the waveform period, and taking the minimum value point near the zero crossing point as the characteristic point of the central isthmus under the condition that the positive zero crossing point of the differential signal exists in the region; under the condition that no zero crossing point exists, taking the maximum value point of the curvature signal in the region as a characteristic point of the central notch;
when the waveform period is between 625ms and 925ms, searching for isthmus characteristic points in a region from 0.32 waveform period to 0.5 waveform period; when a positive zero crossing point of the differential signal exists, searching a minimum value point in a region 15ms before and after the zero crossing point as an isthmus characteristic point; if no zero crossing point exists, searching a curvature signal maximum value point as an isthmus characteristic point;
when the waveform period is more than 925ms, searching isthmus characteristic points in a region from 0.28 waveform period to 0.45 waveform period; when a positive zero crossing point of the differential signal exists, searching a minimum value point of a region in the front 15ms and the back 15ms of the zero crossing point as an isthmus characteristic point; if no zero crossing point exists, searching a curvature signal maximum value point as an isthmus characteristic point;
when the waveform period is less than 625ms, searching isthmus characteristic points in a region from 0.36 waveform period to 0.52 waveform period; when a positive zero crossing point of the differential signal exists, searching a minimum value point in the front and rear 15ms regions by using the zero crossing point as an isthmus characteristic point; and when the positive zero crossing point of the differential signal does not exist, searching the maximum point of the curvature signal as the feature point of the isthmus.
2. The method of claim 1, wherein the filtering step is a smoothing filtering step, the smoothing filtering step comprising: and performing convolution filtering processing on the radial pulse waveform and a preset two-dimensional array.
3. The method of claim 1, wherein the starting point searching step comprises: determining a search area based on the maximum value point of the differential signal, searching a forward zero crossing point in the search area, and taking the zero crossing point as a waveform starting point under the condition that the forward zero crossing point exists; otherwise, the minimum value point is used as the starting point of the waveform.
4. The method according to claim 1, wherein in the period determining step, the waveform period is determined by calculating a distance difference between two starting points, and the waveform period is calculated by:
m_vtPeriod[i]＝m_vtFootPos[i]-m_vtFootPos[i-1]
wherein m _ vtPeriod is a waveform period; m _ vtFootPos is used as a starting point; i is an outer loop variable representing the ith bit signal value.
5. The method according to claim 1, wherein in the waveform calibration step, the baseline wander processing is performed according to a slope of the waveform start point value and a waveform offset, wherein the slope is calculated by:
the waveform offset calculation formula is as follows:
ΔvtSlope＝vtSlope[i]*(j-m_vtFootPos[i])
the waveform after baseline wander removal processing is:
Normalization[j]＝vtSmoothedData[j]-vtSmoothedData[m_vtFootPos[i]]-ΔvtSlope
wherein vtSlope represents the slope; Δ vtSlope represents the waveform offset; vtsmootheneddata represents the filtered radial pulse waveform; m _ vtFootPos is used as a starting point; m _ vtPeriod is a waveform period; i is an outer loop variable and represents the ith signal value; j is an inner loop variable.
6. The method of claim 1, wherein the curvature signal is calculated by the formula:
wherein vtsmootheneddata represents the filtered radial pulse waveform; vtSecDrtSig represents the second order differential signal of the radial pulse waveform, and i represents the ith signal value.
7. An apparatus for identifying a radial artery pressure waveform isthmus feature point, comprising:
a filtering module configured to perform filtering processing on a radial artery pulse waveform;
a differential signal generation module configured to generate a differential signal of the radial pulse waveform, determine a maximum of the differential signal;
a starting point search module configured to determine a starting point of the radial pulse waveform based on a maximum value of the differential signal;
a period determination module configured to determine a period of the radial pulse waveform based on the starting point;
a waveform calibration module configured to perform de-baseline wander processing on the radial pulse waveform based on the starting point and calibrate the waveform; and
a feature point identification module configured to identify a isthmus feature point of the calibrated waveform;
the method for determining the waveform maximum value comprises the following steps:
and (3) a step of segmented searching: dividing the differential signal waveform into eight sections, and respectively searching a maximum value point of each section of waveform;
and an average value calculation step: calculating an average value AvgSegmentMax of maximum values of the eight sections of waveforms; and
a maximum value determining step: searching a maximum value point in the whole differential signal waveform, and determining the value of the maximum value point as the maximum value point of the differential signal under the condition that the amplitude of the maximum value point is greater than 0.6 × AvgSegmentMax;
in the differential signal generating step, a calculation formula of the differential signal generation is:
vtCpDifSig[i]＝vtSmoothedData[i+1]-vtSmoothedData[i-1]+2*(vtSmoothedData[i+2]-vtSmoothedData[i-2])
wherein vtCpDifSig represents a differential signal; vtsmootheneddata represents the filtered radial pulse waveform; i is an outer loop variable and represents the ith signal value;
wherein the step of feature point identification comprises: determining a region for searching for the characteristic point of the central isthmus according to the waveform period, and taking the minimum value point near the zero crossing point as the characteristic point of the central isthmus under the condition that the positive zero crossing point of the differential signal exists in the region; under the condition that no zero crossing point exists, taking the maximum value point of the curvature signal in the region as a characteristic point of the central notch;
when the waveform period is between 625ms and 925ms, searching for isthmus characteristic points in a region from 0.32 waveform period to 0.5 waveform period; when a positive zero crossing point of the differential signal exists, searching a minimum value point in a region 15ms before and after the zero crossing point as an isthmus characteristic point; if no zero crossing point exists, searching a curvature signal maximum value point as an isthmus characteristic point;
when the waveform period is more than 925ms, searching isthmus characteristic points in a region from 0.28 waveform period to 0.45 waveform period; when a positive zero crossing point of the differential signal exists, searching a minimum value point of a region in the front 15ms and the back 15ms of the zero crossing point as an isthmus characteristic point; if no zero crossing point exists, searching a curvature signal maximum value point as an isthmus characteristic point;
when the waveform period is less than 625ms, searching isthmus characteristic points in a region from 0.36 waveform period to 0.52 waveform period; when a positive zero crossing point of the differential signal exists, searching a minimum value point in the front and rear 15ms regions by using the zero crossing point as an isthmus characteristic point; and when the positive zero crossing point of the differential signal does not exist, searching the maximum point of the curvature signal as the feature point of the isthmus.
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