CN108931463B - Blood cell pulse recognition method and device based on sheath flow impedance principle - Google Patents
Blood cell pulse recognition method and device based on sheath flow impedance principle Download PDFInfo
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- 239000006285 cell suspension Substances 0.000 description 3
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
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Abstract
The invention relates to a blood cell pulse identification method based on a sheath flow impedance principle, which comprises the following steps: 1) determining a gradient edge of the pulse signal; 2) finding out a trough and a peak, recording an abscissa a corresponding to the trough and an abscissa b corresponding to the peak, and recording the relative height delta h of the pulse signal, which is f (b) -f (a); 3) finding out an abscissa c corresponding to the pulse end point, wherein the height of the pulse end point is f (c); 4) acquiring the number N of intermediate troughs between the wave crest and the pulse end point, and recording a second signal characteristic of the pulse signal if N is 0; if N is more than or equal to 1, entering the step 5); 5) and recording the intermediate trough with the nearest wave crest as a starting point along the positive direction of the horizontal axis, acquiring the horizontal axis d of the intermediate trough, recording the third signal characteristic of the pulse signal, and returning to the step 1). The method is simpler and faster, and the statistical result is more accurate and reliable. The invention also discloses a blood cell pulse recognition device based on the sheath flow impedance principle.
Description
Technical Field
The invention relates to the technical field of detection, in particular to a blood cell pulse identification method and device based on a sheath flow impedance principle, which are used in the field of medical detection.
Background
Most of the present blood cell analyzers detect cells by using the Coulter principle, specifically, the Coulter principle refers to the electrical impedance principle, which is that cells suspended in an electrolyte pass through a small hole, two electrodes are respectively immersed at two sides of the small hole, when the cells pass through the small hole, the resistance changes to generate voltage pulses, the amplitude of the pulses is generally in direct proportion to the volume of cell particles, and the pulses can be used for measuring the distribution and the quantity of the cell volume after being amplified and identified.
According to the principle, only the pulse signal amplitude generated when a single cell passes through the axis region of the small hole in a straight line can express the volume of the cell, however, in the actual detection process, abnormal signals are very easy to appear, and the abnormal signals are mainly divided into two types: one type is a pulse signal generated by multiple cells through a small hole in a coincidence manner, the pulse signal is called M wave, and the signal easily influences the counting of the cells; the other type is a pulse signal generated by a single cell through a small hole by deviating from the axis of the small hole, the pulse signal is called m-wave, and the amplitude of the pulse signal cannot accurately express the volume of the cell due to the influence of the electric field distribution gradient.
Chinese patent application No. 201611250438.0 discloses a method for processing the above abnormal signals, which comprises extracting characteristic values of blood cell pulse signals, classifying and identifying the pulse signals in a buffer according to the characteristic values, screening abnormal signals of blood cell pulses, and processing the abnormal signals. Although the method reduces the influence of M waves to a certain extent, the efficiency of the whole statistical process is very low because abnormal pulses are screened after data characteristics need to be extracted; in addition, various experience-related threshold values need to be added when the M-wave and the M-wave are classified in the method, and the selection of the threshold values greatly affects the result, so that the accuracy of signal processing by the method cannot be guaranteed.
Disclosure of Invention
In order to solve the technical problems, the invention discloses a blood cell pulse identification method based on a sheath flow impedance principle, so that the influence of M waves and M waves can be eliminated, and the accuracy of each result in blood cell detection is effectively improved while the detection efficiency is ensured.
The invention discloses a blood cell pulse recognition method based on sheath flow impedance principle, which comprises the following steps:
1) determining a gradient edge of the pulse signal from the starting point along the identification direction of the pulse signal;
2) finding out a trough and a peak connected with the slope edge, recording an abscissa a corresponding to the trough and an abscissa b corresponding to the peak, and recording a first signal characteristic of the pulse signal, wherein the first signal characteristic at least comprises a relative height Δ h of the pulse signal, and Δ h ═ f (b) - (f) (a);
3) finding out an abscissa c corresponding to a pulse terminal after the peak is crossed, wherein the height of the pulse terminal is f (c), and delta h/10 is more than or equal to f (c) and less than or equal to delta h/5;
4) acquiring the number N of intermediate troughs between the peak and the pulse end point, and recording a second signal characteristic of the pulse signal if N is 0; if N is more than or equal to 1, entering the step 5);
5) recording the intermediate trough with the nearest wave crest as the starting point of the next pulse signal, acquiring the abscissa d of the starting point, recording the third signal characteristic of the pulse signal, and returning to the step 1).
Preferably, the second signal is characterized by a pulse width Δ w | -c-a |, and the third signal is characterized by a pulse width Δ w | -d-a |.
Preferably, in step 2), an actual height h of the pulse signal is also recorded, where h ═ f (b).
Preferably, the height f (c) of the pulse end point is Δ h/5.
Preferably, the slope edge is a rising edge of the pulse signal, the identification direction of the pulse signal is a positive direction of a horizontal axis, and the step 1) specifically includes:
selecting a characteristic point on the pulse signal along a horizontal axis from a starting point, calculating the slope k of the pulse signal at the characteristic point, wherein the slope k is more than or equal to a first preset slope k0And if so, determining that the characteristic point is positioned in the rising edge of the pulse signal.
Preferably, the interval between two adjacent feature points on the horizontal axis is the sampling interval of the pulse signal.
Preferably, the first predetermined slope k0Satisfies the following conditions: k is not less than 50≤15。
Preferably, the step 2) is specifically:
finding out the characteristic point P with the maximum slope in the pulse signal in the rising edge of the pulse signal0From P0Initially, finding out a wave trough connected with the rising edge along the negative direction of the transverse shaft; and finding out the wave crest connected with the rising edge along the positive direction of the horizontal axis.
Preferably, the slope edge is a rising edge of the pulse signal, the identification direction of the pulse signal is a positive direction of a horizontal axis, and the step 4) specifically includes:
41) selecting any two values i and x between the intervals (b and c), wherein i is larger than x, and if f (i) -f (x) is less than or equal to 0 all the time, judging that N is 0; if f (i) -f (x) > 0, go to step 42);
42) recording the number m of the operation of the step, recording the intermediate trough with the nearest wave crest as a starting point, and finding out the rising edge of the pulse signal along the positive direction of the horizontal axis from the starting pointFinding out the wave crest connected with the rising edge, and recording the abscissa b of the wave crest1Finding out the abscissa c corresponding to the pulse end point after crossing the peak along the positive direction of the abscissa1Wherein Δ h/10. ltoreq. f (c)1) Delta h/5 or less, and entering the step 43).
43) Selecting interval (b)1，c1) Any two values in between i1And x1And i is1＞x1If f (i) is always satisfied1)-f(x1) And if not, assigning N to m, otherwise, returning to the step 42).
Preferably, the gradient edge is a falling edge of the pulse signal, the identification direction of the pulse signal is a negative direction of a horizontal axis, and the step 1) specifically includes:
selecting a characteristic point on the pulse signal along a horizontal axis from a starting point, calculating the slope k of the pulse signal at the characteristic point, and calculating a second preset slope k when the slope k is less than or equal to1And if so, determining that the characteristic point is positioned in the falling edge of the pulse signal.
Preferably, the step 2) is specifically:
finding out the characteristic point P with the minimum slope in the pulse signal in the falling edge of the pulse signal0From P0Initially, finding out a trough connected with the falling edge along the positive direction of a transverse shaft; and finding out the peak connected with the falling edge along the negative direction of the horizontal axis.
The blood cell pulse recognition device based on the sheath flow impedance principle disclosed by the invention comprises:
the gradient edge determining module is used for determining the gradient edge of the pulse signal from the starting point along the identification direction of the pulse signal;
the wave crest/wave trough determining module is used for finding out the wave trough and the wave crest connected with the gradient edge, and recording an abscissa a corresponding to the wave trough and an abscissa b corresponding to the wave crest;
a first processing module, configured to calculate and record a first signal characteristic of the pulse signal, where the first signal characteristic at least includes a relative height Δ h of the pulse signal, where Δ h ═ f (b) -f (a);
the pulse end point determining module is used for finding out an abscissa c corresponding to a pulse end point after the peak is crossed, wherein the height of the pulse end point is f (c), and delta h/10 is less than or equal to f (c) and less than or equal to delta h/5;
the middle trough number acquisition module is used for acquiring the middle trough number N between the peak and the pulse end point;
the second processing module is used for calculating and recording a second signal characteristic of the pulse signal when N is equal to 0;
the middle trough determining module is used for acquiring the abscissa d of the middle trough closest to the wave peak when N is larger than or equal to 1;
the third processing module is used for calculating and recording a third signal characteristic of the pulse signal when N is larger than or equal to 1;
and the starting point resetting module is used for resetting the intermediate wave trough closest to the wave crest to the starting point of the next pulse signal when N is larger than or equal to 1.
Preferably, the slope edge determination module includes a slope calculation module, a comparison module, and a determination module, wherein,
the slope calculation module is used for calculating the slope k of the characteristic point on the pulse signal along the identification direction of the pulse signal;
the comparison module is used for comparing the slope k with the first preset slope k0And said second predetermined slope k1The size of (d);
the determining module is used for determining whether the slope k is a positive number and not less than the first preset slope k0Then, judging that the characteristic point is positioned in the rising edge of the pulse signal; when the slope k is negative and the slope k is not more than the second preset slope k1And then, judging that the characteristic point is positioned in the falling edge of the pulse signal.
The skilled in the art can understand that the sheath flow impedance technology can ensure that the cells directionally flow along the center of the small hole, so that the blood cell pulse identification method based on the sheath flow impedance principle can effectively avoid the cells from deviating from the center of the small hole, thereby reducing or even avoiding the influence of m-wave on the blood cell counting and the particle size statistics; in addition, in the blood cell pulse recognition method disclosed by the invention, aiming at the phenomenon that pulse signals are overlapped due to M waves, single pulses capable of reflecting the characteristics of single cells in the pulse signals are respectively subjected to characteristic extraction, so that the influence of the M waves on the cell number statistics and the amplitude and width of the pulse signals is eliminated. Compared with signal correction in the prior art, the blood cell pulse identification method is simpler and faster, and the statistical result is more accurate and reliable.
Drawings
FIG. 1 is a schematic diagram of a normal pulse signal disclosed in an embodiment of the present invention;
FIG. 2 is a schematic diagram of "M-wave" disclosed in the embodiments of the present invention;
FIG. 3 is a schematic flow chart of a blood cell pulse recognition method according to an embodiment of the present invention;
FIG. 4 is a flow chart illustrating a blood cell pulse recognition method according to another embodiment of the present invention.
Detailed Description
In the field of blood cell detection, sheath flow techniques have emerged to avoid the flow of blood cells from the edges of the small pores during counting and to avoid the effects of turbulence and turbulence. The sheath flow technology is realized by aligning a capillary tube with a small-hole tube, ejecting the cell suspension from the capillary tube, and simultaneously flowing the cell suspension and sheath liquid flowing out from the periphery of the capillary tube through a sensitive area together to ensure that the cell suspension forms a single-arranged cell flow in the middle and the periphery of the cell flow is surrounded by the sheath liquid. The particle size and the number of the cells can be counted according to the change of the resistance when the cells flow through the small holes by utilizing the sheath flow impedance principle.
The blood cell pulse identification method disclosed by the invention is used for identifying pulse signals formed based on the sheath flow impedance principle, and recording the relative height, pulse width and the like of the pulse signals so as to obtain and count various blood cell parameters such as the number of cells, the particle size and the like.
Referring to fig. 1 and 2, fig. 1 is a schematic diagram of a pulse signal obtained according to the principle of sheath flow impedance when a single blood cell passes through a pore, the pulse signal is a normal pulse signal, fig. 2 is a schematic diagram of a pulse signal obtained according to the principle of sheath flow impedance when a blood cell passes through a pore, but the pulse signal is actually two blood cells overlapping and passing through a pore, so that the pulse signal is abnormal, and a so-called "M wave" is formed.
The invention discloses a blood cell pulse recognition method, which comprises the following steps:
1) determining a gradient edge of the pulse signal from the starting point along the identification direction of the pulse signal;
2) finding out a trough and a peak connected with the slope edge, recording an abscissa a corresponding to the trough and an abscissa b corresponding to the peak, and recording a first signal characteristic of the pulse signal, wherein the first signal characteristic at least comprises a relative height Δ h of the pulse signal, and Δ h ═ f (b) - (f) (a);
3) finding out an abscissa c corresponding to a pulse terminal after the peak is crossed, wherein the height of the pulse terminal is f (c), and delta h/10 is more than or equal to f (c) and less than or equal to delta h/5;
4) acquiring the number N of intermediate troughs between the peak and the pulse end point, and recording a second signal characteristic of the pulse signal if N is 0; if N is more than or equal to 1, entering the step 5);
5) recording the intermediate trough with the nearest wave crest as the starting point of the next pulse signal, acquiring the abscissa d of the starting point, recording the third signal characteristic of the pulse signal, and returning to the step 1).
As is well known, the rising edge and the falling edge of the pulse signal are respectively located on two sides of the peak of the pulse signal, and in this case, the rising edge and the falling edge on two sides of the pulse signal are collectively referred to as the slope edge.
The first signal characteristic in the above embodiment may include, but is not limited to, the actual height h of the pulse signal, and the area of the pulse signal, in addition to the relative height of the pulse, where h ═ f (b); the second signal characteristic may be a pulse width Δ w | -c-a |, and the third signal characteristic may be a pulse width Δ w | -d-a |, but the second signal characteristic and the third signal characteristic may also be other pulse information that needs to be calculated and recorded, and the pulse information may be adapted according to the experimentally expected purpose.
Hereinafter, the present invention will be described in detail with reference to two specific embodiments, in which the slope edge is a rising edge and the slope edge is a falling edge.
Example 1
The present embodiment is described with respect to a case where a slope edge is a rising edge and an identification direction of a pulse signal is a positive direction of a horizontal axis, and is understood with reference to fig. 1 to 3.
Referring to fig. 3, after acquiring a pulse signal, the blood cell pulse recognition method sequentially performs the following steps:
s1) finding the rising edge of the pulse signal along the positive direction of the horizontal axis from the starting point;
s2), finding out the wave trough and the wave crest connected with the rising edge, recording the abscissa a corresponding to the wave trough, recording the abscissa b corresponding to the wave crest, and recording the relative height Δ h of the pulse signal, wherein Δ h ═ f (b) - (f) (a);
s3) finding out an abscissa c corresponding to a pulse end point after the abscissa crosses a peak along the positive direction of the abscissa, wherein the height of the pulse end point is f (c), and delta h/10 is more than or equal to f (c) and less than or equal to delta h/5;
s4) acquiring the number N of intermediate troughs between the peak and the pulse end point, wherein if N is 0, the pulse is formed by a single cell, and the pulse width Δ w is directly recorded as c-a; if N is equal to or greater than 1, it indicates that the pulse is formed by overlapping a plurality of cells through the aperture, and then the process proceeds to step S5);
s5) recording the intermediate valley closest to the peak as the starting point of the next pulse signal in the positive direction along the horizontal axis, and acquiring the horizontal axis d thereof, recording the pulse width Δ w-d-a, and returning to step S1), by which the overlapped pulse waves can be separated, and returning to step S1), the features of the separated individual pulses can be individually extracted.
If necessary, in step S2), the actual pulse height h of the pulse signal may be recorded, where h is f (b).
The function f (x) in the above step specifically refers to a functional relation corresponding to the pulse signal. The skilled in the art can understand that the sheath flow impedance technology can ensure that the cells flow directionally along the center of the small hole, so that the blood cell pulse identification method based on the sheath flow impedance principle can effectively avoid the cells from deviating from the center of the small hole, thereby reducing or even avoiding the influence of m-wave on the blood cell count and the particle size statistics; in addition, in the blood cell pulse recognition method disclosed in the above embodiment, in order to solve the phenomenon that the pulse signal is superimposed due to the "M wave", the feature extraction is performed on the individual pulses in the pulse signal, which can reflect the features of the individual cells, respectively, so as to eliminate the influence of the "M wave" on the statistics of the number of cells and the particle size, as well as on the amplitude and the width of the pulse signal. Compared with a signal correction mode in the prior art, the blood cell pulse identification method is simpler and faster, and the statistical result is more accurate and reliable.
As shown in fig. 1 and 2, actually, the pulse signal is represented in a two-dimensional rectangular coordinate system, the abscissa indicates the abscissa in the two-dimensional rectangular coordinate system, and according to mathematical interpretation, the positive direction of the abscissa is a direction toward the right (increasing numerical value) and the negative direction is a direction toward the left (decreasing numerical value).
In general, the starting point in step S1) is the left end point of the acquired pulse signal, and there should be at least one complete pulse in the acquired pulse signal; of course, the starting point may be a starting point set manually.
The method for finding the rising edge of the pulse signal is not limited to one, and in fig. 3, the step labeled S1 discloses a method for finding the rising edge of the pulse signal, specifically, a characteristic point on the pulse signal can be selected along the horizontal axis from the starting point, and then the pulse signal at the characteristic point can be calculatedThe slope k of the sign is greater than or equal to the first predetermined slope k0And then, determining that the characteristic point is located in the rising edge of the pulse signal, so that the rising edge of the pulse signal is found, and easily understanding that the slope k in the rising edge is not less than 0, and once the slope k at the characteristic point is less than 0, proving that the characteristic point exceeds the rising edge.
First predetermined slope k0Is an artificial set value, k0The arrangement of (1) is mainly to eliminate the influence of noise in the pulse signal and avoid determining the disturbance caused by the noise as the rising edge of the pulse signal, and if the reasonable k is not set, the noise is actually in the area defined by the broken line of the part A in FIG. 10It is easy to determine the rising edge as the false rising edge of the pulse signal, and practical studies show that the slope value of the rising edge caused by noise is generally not more than 5, and the slope value of the rising edge of the actual pulse signal generated when the cell passes through the small hole is much more than 5, so the first predetermined slope k is set to be the first predetermined slope k0Is set to the interval [5, 15]The influence of noise on the judgment of the rising edge of the pulse signal can be effectively eliminated by the numerical value between the two.
Besides, those skilled in the art can also find the rising edge of the pulse signal from the starting point along the positive direction of the transverse axis by using an image recognition method, and since the image recognition method is widely used in scientific research and daily life, the image recognition method will not be described in detail in the embodiment of the present invention.
Step S2), finding out the wave trough and the wave crest connected to the rising edge can also be performed by using an image recognition method, in addition, the embodiment of the present invention further discloses a method for finding out the wave crest and the wave trough by slope assistance, specifically, finding out the characteristic point P with the maximum slope in the pulse signal in the rising edge of the pulse signal0From P0Initially, finding out a trough (a point with the minimum ordinate) connected with the rising edge along the negative direction of the horizontal axis; the peak (the point with the largest ordinate) connected to the rising edge is found along the positive direction of the horizontal axis.
The interval of the feature point selection can be changed according to needs, and for convenience of selection, the interval of two adjacent feature points on the horizontal axis is the sampling interval of the pulse signal.
In order to obtain the pulse end point of the pulse signal within a reasonable pulse width range, the height of the pulse end point may be set to 10% to 20% of the relative height Δ h, that is, the height Δ h/10 ≦ f (c) ≦ Δ h/5, preferably, f (c) ≦ Δ h/5.
In step S4), it can be directly determined whether the pulse signal is formed by a single cell through a pinhole or by overlapping multiple cells through a pinhole by obtaining the intermediate number N of valleys between the peak and the pulse end point, if N is 0, it is verified that no valley appears again between the peak and the valley of the current pulse signal, the pulse signal is a normal signal, the pulse width Δ w is recorded as required as c-a, and if N is greater than or equal to 1, it is verified that at least one valley appears between the peak and the valley of the current pulse signal, the pulse signal is actually an "M wave", and then the process proceeds to step S5);
in step S5), the intermediate trough closest to the peak is recorded as a starting point along the horizontal axis in the forward direction, and the horizontal axis d of the trough is obtained, and the trough is actually the end point of the previous pulse signal, at this time, the previous pulse width Δ w is recorded as d-a; then, the trough is reset to the start point of the next pulse signal, and the process returns to step S1) again until the condition that N is 0 in step S4) is satisfied. As can be seen, the multiple pulse signals overlapped together are separated one by one in step S5) to extract the features such as the relative height and pulse width of the pulse signals, so as to record the number of cells passing through the small holes and the particle size information truly and accurately.
In this embodiment, the specific manner of obtaining the number N of intermediate troughs between the peak and the pulse end point in step S4) is as follows:
41) selecting any two values i and x in the interval (b, c), wherein i is larger than x, if f (i) -f (x) is always satisfied to be less than or equal to 0, indicating that the pulse signal is in a continuous descending state in the interval (b, c), and judging that N is equal to 0 if no wave trough appears in the interval; if f (i) -f (x) is greater than 0, the pulse signal is in the interval (b, c) and jumps in the descending process, and the step 42 is carried out, so as to record the number of the middle wave troughs in the interval;
42) recording the number m of the operation of the step, recording the intermediate trough closest to the peak as the starting point of the next pulse signal, finding out the rising edge of the pulse signal along the positive direction of the transverse axis from the starting point, finding out the peak connected with the rising edge, and recording the abscissa b of the peak1Finding out the abscissa c corresponding to the pulse end point after crossing the peak along the positive direction of the abscissa1The height of the pulse end point is f (c)1) Wherein Δ h/10. ltoreq. f (c)1) Delta h/5 or less, and entering the step 43).
43) Selecting interval (b)1，c1) Any two values in between i1And x1And i is1＞x1If f (i) is always satisfied1)-f(x1) And if not, assigning N to m, otherwise, returning to the step 42).
In addition, of course, a person skilled in the art can also obtain the number N of intermediate troughs between the peak and the pulse end point by means of image recognition, which is not described in the present invention again.
The method disclosed in the above embodiment is to find the rising edge of the pulse signal first, and then find the parameters such as the peak and the trough of the pulse signal according to the rising edge, and those skilled in the art can also find the falling edge of the pulse signal first, and then find the parameters such as the peak and the trough of the pulse signal through the falling edge.
Example 2
The present embodiment is described with respect to the case where the gradient edge is a falling edge and the identification direction of the pulse signal is a negative direction of the horizontal axis, and is understood with reference to fig. 1, 2 and 4.
Specifically, in the blood cell pulse recognition method disclosed in this embodiment, after acquiring a segment of pulse signal, the blood cell pulse recognition method sequentially performs the following steps:
s I) finding out the falling edge of the pulse signal from the starting point along the negative direction of the transverse shaft;
s II) finding out a trough and a peak connected with the falling edge, recording an abscissa a corresponding to the trough and an abscissa b corresponding to the peak, and recording the relative height delta h of the pulse signal, wherein the delta h is f (b) -f (a);
s III) finding out a horizontal coordinate c corresponding to a pulse end point after crossing the peak along the negative direction of the horizontal axis, wherein the height of the pulse end point is f (c), and delta h/10 is less than or equal to f (c) and less than or equal to delta h/5;
s IV) acquiring the number N of intermediate troughs between the peak and the pulse end point, and if N is 0, recording the pulse width delta w as a-c; if N is more than or equal to 1, entering step S V);
and S V) recording the intermediate trough with the nearest wave crest as the starting point of the next pulse signal along the negative direction of the horizontal axis, acquiring the horizontal axis d of the intermediate trough, recording the current pulse width delta w as a-d, and returning to the step S I).
If necessary, in step S ii), the actual pulse height h of the pulse signal may also be recorded, where h is f (b).
Similar to the first embodiment, finding the falling edge of the pulse signal can select the characteristic point on the pulse signal along the horizontal axis from the starting point, and then calculate the slope k of the pulse signal at the characteristic point, since the slopes in the falling edge are all negative values, the slope k is less than or equal to the second predetermined slope k1And then, determining that the characteristic point is located in the falling of the pulse signal, so that the falling edge of the pulse signal is found, wherein it is easy to understand that the slope k in the falling edge is not greater than 0, and once the slope k at the characteristic point is greater than 0, the characteristic point is proved to exceed the falling edge.
Second predetermined slope k1Is set to the interval [ -15, -5 [)]So as to effectively eliminate the influence of noise on the judgment of the falling edge of the pulse signal.
In this embodiment, the peak and the trough can be found in a slope-assisted manner, and specifically, the characteristic point P with the minimum slope in the pulse signal is found in the falling edge of the pulse signal0From P0Initially, finding out a trough (a point with the smallest ordinate) connected with the falling edge along the positive direction of the horizontal axis; the peak (the point with the largest ordinate) connected to the falling edge is found along the negative direction of the horizontal axis.
The determination of the number N of intermediate troughs in step S iv) may be performed with reference to the first embodiment, which is not described herein again.
Compared with the signal correction mode in the prior art, the blood cell pulse recognition method disclosed by the embodiment of the invention is simpler and faster, and the statistical result is more accurate and reliable.
In addition, the present invention also discloses a blood cell pulse recognition device based on the sheath flow impedance principle, which comprises:
the gradient edge determining module is used for determining the gradient edge of the pulse signal from the starting point along the identification direction of the pulse signal;
the wave crest/wave trough determining module is used for finding out the wave trough and the wave crest connected with the gradient edge, and recording an abscissa a corresponding to the wave trough and an abscissa b corresponding to the wave crest;
a first processing module, configured to calculate and record a first signal characteristic of the pulse signal, where the first signal characteristic at least includes a relative height Δ h of the pulse signal, where Δ h ═ f (b) -f (a);
the pulse end point determining module is used for finding out an abscissa c corresponding to a pulse end point after the peak is crossed, wherein the height of the pulse end point is f (c), and delta h/10 is less than or equal to f (c) and less than or equal to delta h/5;
the middle trough number acquisition module is used for acquiring the middle trough number N between the peak and the pulse end point;
the second processing module is used for calculating and recording a second signal characteristic of the pulse signal when N is equal to 0;
the middle trough determining module is used for acquiring the abscissa d of the middle trough closest to the wave peak when N is larger than or equal to 1;
the third processing module is used for calculating and recording a third signal characteristic of the pulse signal when N is larger than or equal to 1;
and the starting point resetting module is used for resetting the intermediate wave trough closest to the wave crest to the starting point of the next pulse signal when N is larger than or equal to 1.
Likewise, the first signal characteristic may include, but is not limited to, the actual height h of the pulse signal, and the area of the pulse signal, in addition to the relative height of the pulse, where h ═ f (b); the second signal characteristic may be a pulse width Δ w | -c-a |, and the third signal characteristic may be a pulse width Δ w | -d-a |, but the second signal characteristic and the third signal characteristic may also be other pulse information that needs to be calculated and recorded, and the pulse information may be adapted according to the experimentally expected purpose.
More specifically, the slope edge determination module includes a slope calculation module, a comparison module, and a determination module, wherein,
the slope calculation module is used for calculating the slope k of the characteristic point on the pulse signal along the identification direction of the pulse signal;
the comparison module is used for comparing the slope k with a first preset slope k0And said second predetermined slope k1The size of (d);
the determination module is used for determining that the slope k is a positive number and is not less than the first preset slope k0Then, judging that the characteristic point is positioned in the rising edge of the pulse signal; when the slope k is negative and the slope k is not more than the second preset slope k1And then, judging that the characteristic point is positioned in the falling edge of the pulse signal.
It should be noted that the interval between feature points may be changed as needed, and for convenience of selection, in the embodiment of the present invention, the interval between two adjacent feature points on the horizontal axis is the sampling interval of the pulse signal.
The blood cell pulse recognition method and device based on the sheath flow impedance principle disclosed in the present invention are described in detail above. The principles and embodiments of the present invention are explained herein using specific examples, which are presented only to assist in understanding the method and its core concepts. It should be noted that, for those skilled in the art, it is possible to make various improvements and modifications to the present invention without departing from the principle of the present invention, and those improvements and modifications also fall within the scope of the claims of the present invention.
Claims (12)
1. A blood cell pulse recognition method based on sheath flow impedance principle is characterized by comprising the following steps:
1) determining a gradient edge of the pulse signal from the starting point along the identification direction of the pulse signal;
2) finding out a trough and a peak connected with the slope edge, recording an abscissa a corresponding to the trough and an abscissa b corresponding to the peak, and recording a first signal characteristic of the pulse signal, wherein the first signal characteristic at least comprises a relative height Δ h of the pulse signal, and Δ h = f (b) - (f) (a);
3) finding out an abscissa c corresponding to a pulse terminal after the peak is crossed, wherein the height of the pulse terminal is f (c), and delta h/10 is more than or equal to f (c) and less than or equal to delta h/5;
4) acquiring the number N of intermediate troughs between the wave crest and the pulse end point, and recording a second signal characteristic of the pulse signal if N = 0; if N is more than or equal to 1, entering the step 5);
5) recording the intermediate trough with the nearest wave crest as the starting point of the next pulse signal, acquiring the abscissa d of the starting point, recording the third signal characteristic of the pulse signal, and returning to the step 1).
2. The method of claim 1 wherein the second signal characteristic is pulse width Δ w = | c-a |, and the third signal characteristic is pulse width Δ w = | d-a |.
3. The method of identifying a pulse of blood cells according to claim 1, wherein the height f (c) = Δ h/5 at the pulse end point.
4. The method according to claim 1, wherein the gradient edge is a rising edge of the pulse signal, and the identification direction of the pulse signal is a positive direction of a horizontal axis, and the step 1) is specifically as follows:
selecting a characteristic point on the pulse signal along a horizontal axis from a starting point, calculating the slope k of the pulse signal at the characteristic point, wherein the slope k is more than or equal to a first preset slope k0And if so, determining that the characteristic point is positioned in the rising edge of the pulse signal.
5. The method according to claim 4, wherein the interval between two adjacent feature points on the horizontal axis is a sampling interval of the pulse signal.
6. The method according to claim 4, wherein the first predetermined slope k is0Satisfies the following conditions: k is not less than 50≤15。
7. The blood cell pulse recognition method according to claim 4, wherein the step 2) is specifically:
finding out the characteristic point P with the maximum slope in the pulse signal in the rising edge of the pulse signal0From P0Initially, finding out a wave trough connected with the rising edge along the negative direction of the transverse shaft; and finding out the wave crest connected with the rising edge along the positive direction of the horizontal axis.
8. The method according to claim 1, wherein the gradient edge is a rising edge of the pulse signal, the identification direction of the pulse signal is a positive direction of a horizontal axis, and the step 4) is specifically as follows:
41) selecting any two values i and x in the interval (b, c), wherein i is larger than x, and if f (i) -f (x) is less than or equal to 0 all the time, judging that N = 0; if f (i) -f (x) > 0, go to step 42);
42) recording the number m of the operation of the step, recording the intermediate trough closest to the peak as a starting point, finding out the rising edge of the pulse signal along the positive direction of the transverse axis from the starting point, finding out the peak connected with the rising edge, and recording the abscissa b of the peak1Along the horizontal axisFinding out the abscissa c corresponding to the pulse end point after the peak is crossed1The height of the pulse end point is f (c)1) Wherein Δ h/10. ltoreq. f (c)1) Delta h/5 or less, entering the step 43);
43) selecting interval (b)1，c1) Any two values in between i1And x1And i is1＞x1If f (i) is always satisfied1）-f（x1) And if not more than 0, assigning N = m, otherwise, returning to the step 42).
9. The method according to claim 1, wherein the gradient edge is a falling edge of the pulse signal, and the identification direction of the pulse signal is a negative direction of a horizontal axis, and the step 1) is specifically:
selecting a characteristic point on the pulse signal along a horizontal axis from a starting point, calculating the slope k of the pulse signal at the characteristic point, and calculating a second preset slope k when the slope k is less than or equal to1And if so, determining that the characteristic point is positioned in the falling edge of the pulse signal.
10. The method for identifying blood cell pulses according to claim 9, wherein the step 2) is specifically:
in the falling edge of the pulse signal, finding out the characteristic point P with the minimum slope in the pulse signal0From P0Initially, finding out a trough connected with the falling edge along the positive direction of a transverse shaft; and finding out the peak connected with the falling edge along the negative direction of the horizontal axis.
11. A blood cell pulse recognition device based on the sheath flow impedance principle is characterized by comprising:
the gradient edge determining module is used for determining the gradient edge of the pulse signal from the starting point along the identification direction of the pulse signal;
the wave crest/wave trough determining module is used for finding out the wave trough and the wave crest connected with the gradient edge, and recording an abscissa a corresponding to the wave trough and an abscissa b corresponding to the wave crest;
a first processing module, configured to calculate and record a first signal characteristic of the pulse signal, where the first signal characteristic at least includes a relative height Δ h of the pulse signal, where Δ h = f (b) -f (a);
the pulse end point determining module is used for finding out an abscissa c corresponding to a pulse end point after the peak is crossed, wherein the height of the pulse end point is f (c), and delta h/10 is less than or equal to f (c) and less than or equal to delta h/5;
the middle trough number acquisition module is used for acquiring the middle trough number N between the peak and the pulse end point;
the second processing module is used for calculating and recording a second signal characteristic of the pulse signal when N = 0;
the middle trough determining module is used for acquiring the abscissa d of the middle trough closest to the wave peak when N is larger than or equal to 1;
the third processing module is used for calculating and recording a third signal characteristic of the pulse signal when N is larger than or equal to 1;
and the starting point resetting module is used for resetting the intermediate wave trough closest to the wave crest to the starting point of the next pulse signal when N is larger than or equal to 1.
12. The apparatus according to claim 11, wherein the slope edge determination module includes a slope calculation module, a comparison module, and a determination module, wherein,
the slope calculation module is used for calculating the slope k of the characteristic point on the pulse signal along the identification direction of the pulse signal;
the comparison module is used for comparing the slope k with a first preset slope k0And a second predetermined slope k1The size of (d);
the determining module is used for determining whether the slope k is a positive number and not less than the first preset slope k0Then, judging that the characteristic point is positioned in the rising edge of the pulse signal; when the slope k is negative and the slope k is not more than the second preset slope k1And then, judging that the characteristic point is positioned in the falling edge of the pulse signal.
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