CN113109630B - Pulse data processing method and device and blood cell analyzer - Google Patents
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Abstract
The embodiment of the invention discloses a pulse data processing method and device and a blood cell analyzer. The method comprises the following steps: acquiring original pulse data; determining a first mean value of the original pulse data based on the size of a first window, and determining a second mean value of the original pulse data based on the size of a second window, wherein the size of the first window is smaller than that of the second window, and the size of the first window and the size of the second window are both larger than the data width of single pulse data in the original pulse data; determining whether the original pulse data has baseline lifting according to the magnitude relation of the first average value and the second average value, and determining a lifting starting point of the baseline according to the first average value and the second average value when the original pulse data has baseline lifting; determining a baseline according to the first mean value and the lifting starting point; target pulse data is determined from the raw pulse data and the baseline. According to the embodiment of the invention, the lifting baseline in the pulse data can be accurately and efficiently removed.
Description
Technical Field
The invention relates to the technical field of pulse data, in particular to a pulse data processing method and device and a blood cell analyzer.
Background
In the pulse detection process, due to the influence of external factors such as poor contact of the sensor, low-frequency interference and the like, effective signals of pulse data are superposed on an unstable baseline voltage level, namely fundamental frequency signals. In some particle detection systems, a particle produces a pulse signal whose amplitude is proportional to the volume of the particle as it passes through a microwell, for example, in a blood cell analyzer, a pulse signal whose amplitude is proportional to the volume of a blood cell as it passes through a diamond well.
As shown in fig. 1, when a fluctuating baseline is superimposed on the pulse data signal, the amplitude of the pulse data signal is raised or lowered, that is, the baseline is raised, which causes distortion of amplitude measurement and affects accurate identification of pulse data, and fig. 2 is a result of superimposing an ac fundamental frequency signal in fig. 1, and compared with fig. 1, there is significant fundamental frequency signal raising. In order to remove the baseline lifting and obtain effective pulse data, a signal baseline is usually obtained by using a median filtering method, or an estimation of the baseline is performed by using a reference value.
However, although the signal baseline is obtained by using the median filtering method, the baseline obtaining result is accurate, and the problem of baseline lifting can be effectively solved, the median filtering is mainly performed by sorting and median solving, the sorting process is long in time consumption, and is not suitable for the case of high system frequency, and the median solving process still needs to be optimized. However, the baseline estimation by the reference value can only roughly obtain the signal baseline, and although the running time is fast, the problem of partial baseline lifting cannot be effectively solved.
Disclosure of Invention
In view of the above, it is necessary to provide a pulse data processing method, a pulse data processing apparatus, and a blood cell analyzer.
In a first aspect, an embodiment of the present invention provides a method for processing pulse data, where the method includes:
acquiring original pulse data;
determining a first mean value of the original pulse data based on a first window size, and determining a second mean value of the original pulse data based on a second window size, wherein the first window size is smaller than the second window size, and the first window size and the second window size are both larger than the data width of single pulse data in the original pulse data;
determining whether the original pulse data has baseline lifting according to the magnitude relation of the first mean value and the second mean value, and determining a lifting starting point of the baseline according to the first mean value and the second mean value when the original pulse data has baseline lifting;
determining the baseline according to the first mean and the lifting starting point;
target pulse data is determined from the raw pulse data and a baseline.
In a second aspect, an embodiment of the present invention provides a pulse data processing apparatus, where the apparatus includes:
the sampling module is used for acquiring original pulse data;
the mean filtering module comprises a first mean filtering unit and a second mean filtering unit, wherein the first mean filtering unit is used for determining a first mean value of the original pulse data based on a first window size, the second mean filtering unit is used for determining a second mean value of the original pulse data based on a second window size, the first window size is smaller than the second window size, and the first window size and the second window size are both larger than the data width of single pulse data in the original pulse data;
the first comparison module is used for comparing the first mean value with the second mean value to determine whether the original pulse data has baseline lifting, and when the original pulse data has baseline lifting, the first comparison module is further used for determining a lifting starting point of the baseline according to the first mean value and the second mean value;
the base line acquisition module is used for determining the base line according to the first mean value and the lifting starting point;
and the subtractor module is used for determining target pulse data according to the original pulse data and the baseline.
In a third aspect, an embodiment of the present invention provides a blood cell analyzer, including the pulse data processing apparatus provided in any embodiment of the present invention, and the sampling module is specifically configured to perform pulse detection on target blood cells to obtain raw pulse data of the target blood cells.
According to the embodiment of the invention, two mean values of the original pulse data are obtained based on different window sizes, the base line is determined after the lifting starting point is solved according to the two mean values, and the target pulse data is determined according to the base line and the original pulse data, so that the problem that the lifting of the base line in the pulse data is not efficient enough or accurate enough is solved, and the beneficial effect of accurately and efficiently removing the lifting of the base line in the pulse data is obtained.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Wherein:
FIG. 1 is a diagram of raw pulse data;
FIG. 2 is a diagram of raw pulse data superimposed with an AC base frequency signal;
FIG. 3 is a flow diagram of a method for pulse data processing in one embodiment;
FIG. 4 is a diagram illustrating raw pulse data in one embodiment;
FIG. 5 is a diagram illustrating the last output target pulse data in one embodiment;
FIG. 6 is a flowchart illustrating the detailed operation of step S140 in the pulse data processing method according to an embodiment;
FIG. 7 is a block diagram showing the structure of a pulse data processing apparatus according to an embodiment;
FIG. 8 is a block diagram showing the structure of a pulse data processing apparatus according to an embodiment;
FIG. 9 is a block diagram showing the structure of a blood cell analyzer according to an embodiment.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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 invention.
In one embodiment, as shown in FIG. 3, a method of pulse data processing is provided. The method can be applied to both the terminal and the server, and this embodiment is exemplified by being applied to the terminal. The pulse data processing method specifically comprises the following steps:
and S110, acquiring original pulse data.
In this embodiment, when the pulse data is processed, the counting signal may be sampled by the a/D converter of the single chip, and referring to fig. 4 together, the original pulse data is obtained, and it can be seen that many small glitches exist in the original pulse data, which are non-effective signals, and an obvious baseline lifting exists.
S120, determining a first mean value of the original pulse data based on the size of a first window, and determining a second mean value of the original pulse data based on the size of a second window, wherein the size of the first window is smaller than that of the second window, and the size of the first window and the size of the second window are both larger than the data width of single pulse data in the original pulse data.
In this embodiment, after the original pulse data is obtained, a first average value of the original pulse data may be determined based on a first window size, and a second average value of the original pulse data may be determined based on a second window size, so as to perform average filtering of different window sizes, where the first window size is N, the second window size is M, M is greater than N, as preferred, M is far greater than N, and M and N are both far greater than a data width of a single pulse data in the original pulse data, thereby ensuring that a filtering effect of the first average value and the second average value is obtained. The data width of the single pulse data is determined by hardware such as an A/D converter of the single chip microcomputer, and generally consists of dozens of data points, and the value of each data point is an AD value corresponding to the current particle number. The first mean value is obtained by accumulating and summing the AD value of each data point by the AD values of N adjacent data points, and the second mean value is obtained by accumulating and summing the AD value of each data point by the AD values of M adjacent data points.
S130, determining whether the original pulse data has baseline lifting according to the size relation between the first average value and the second average value, and determining a lifting starting point of the baseline according to the first average value and the second average value when the original pulse data has baseline lifting.
And S140, determining a baseline according to the first mean value and the lifting starting point.
And S150, determining target pulse data according to the original pulse data and the base line.
S160, outputting the target pulse data greater than the first threshold value as an original value, and outputting the target pulse data less than or equal to the first threshold value as the first threshold value.
In this embodiment, after the first mean value and the second mean value are obtained, whether the baseline lifting exists in the original pulse data may be determined according to a size relationship between the first mean value and the second mean value, wherein if the baseline lifting exists in the original pulse data, the first mean value may be larger than the second mean value, a lifting start point of the baseline is determined according to the first mean value and the second mean value, specifically, when the first mean value and the second mean value satisfy a preset threshold condition, a data point corresponding to the current first mean value and the second mean value is determined as the lifting start point, then the baseline is determined according to the first mean value and the lifting start point, and finally the target pulse data is determined according to the original pulse data and the baseline, i.e., the target pulse data may be obtained by subtracting the baseline from the original pulse data. Preferably, since there are many small glitches in the original pulse data, subtracting a data point where the baseline may exist as a negative number, so that the target pulse data greater than the first threshold is output as the original value, and the target pulse data less than or equal to the first threshold is output as the first threshold, where the first threshold is 0, and the final result is also referred to fig. 5, thereby quickly and accurately completing the process of removing the lifted baseline from the original pulse data.
According to the embodiment of the invention, two mean values of the original pulse data are obtained based on different window sizes, the base line is determined after the lifting starting point is solved according to the two mean values, and the target pulse data is determined according to the base line and the original pulse data, so that the problems that the lifting of the base line in the pulse data is not high enough or accurate are solved, and the beneficial effect of accurately and efficiently removing the lifting of the base line in the pulse data is obtained.
In one embodiment, as shown in fig. 6, step S140 specifically includes:
s210, obtaining the maximum value between the lifting starting point and the lifting end point from the first average value, wherein the distance between the lifting end point and the lifting starting point is the size of the second window.
And S220, determining a baseline according to the maximum value and the first mean value.
In this embodiment, because the first average value is obtained based on a smaller first window size, and the second average value is obtained based on a larger second window size, the maximum value in the first average value is substantially consistent with the baseline lifting height, and the maximum value in the second average value is smaller than the baseline lifting height, the maximum value between the lifting start point and the lifting end point is obtained from the first average value, and then the baseline is determined according to the maximum value and the first average value, where the distance between the lifting end point and the lifting start point is the second window size, that is, the lifting end point is the mth data point after the lifting start point, specifically, the values of the data points of the first average value between the lifting start point and the lifting end point are all replaced with the maximum value, that is, the values of the lifting start point and the M-1 data points after the lifting start point are all replaced with the maximum value, and then the new first average value obtained by replacing the maximum value is the obtained baseline result.
According to the embodiment of the invention, the baseline is accurately found through the characteristics of the first average value and the second average value, so that the accuracy of removing the lifting baseline in the pulse data is improved.
As shown in fig. 7, in an embodiment, a pulse data processing apparatus is provided, and the pulse data processing apparatus provided in this embodiment can execute the pulse data processing method provided in any embodiment of the present invention, and has corresponding functional modules and beneficial effects of the execution method. The pulse data processing apparatus includes a sampling module 100, a mean filtering module 200, a first comparison module 300, a baseline acquisition module 400, a subtractor module 500, and a second comparison module 600.
Specifically, the sampling module 100 is configured to obtain original pulse data; the mean filtering module 200 includes a first mean filtering unit 210 and a second mean filtering unit 220, the first mean filtering unit 210 is configured to determine a first mean value of the original pulse data based on a first window size, the second mean filtering unit 220 is configured to determine a second mean value of the original pulse data based on a second window size, the first window size is smaller than the second window size, and both the first window size and the second window size are larger than a data width of a single pulse data in the original pulse data; the first comparison module 300 is configured to compare magnitudes of the first mean value and the second mean value to determine whether the original pulse data has a baseline lift, and when the original pulse data has a baseline lift, the first comparison module 300 is further configured to determine a lift start point of the baseline according to the first mean value and the second mean value; the baseline acquisition module 400 is configured to determine a baseline according to the first mean value and the lifting start point; the subtractor module 500 is configured to determine target pulse data from the raw pulse data and the baseline. The baseline acquisition module 400 is specifically configured to acquire a maximum value between the lifting start point and the lifting end point from the first average value, and determine a baseline according to the maximum value and the first average value, where a distance between the lifting end point and the lifting start point is a size of the second window. The second comparing module 600 is configured to output the target pulse data greater than the first threshold as an original value, and output the target pulse data less than or equal to the first threshold as the first threshold.
In this embodiment, the pulse data processing apparatus has no requirement on real-time performance, data in the pulse data processing apparatus may be automatically cached, and may be programmed by using a scripting language such as C + +, or the like, so as to execute the pulse data processing method. The first mean filtering unit 210 and the second mean filtering unit 220 are both connected to the sampling module 100 to receive original pulse data, the first mean filtering unit 210 and the second mean filtering unit 220 are both connected to the first comparing module 300 to output a first mean value and a second mean value to the first comparing module 300, the first comparing module 300 is connected to the baseline obtaining module 400, the baseline obtaining module 400 is configured to obtain the first mean value and a lifting start point determined by the first comparing module 300, and determine a baseline according to the first mean value and the lifting start point, the subtractor module 500 is connected to the baseline obtaining module 400 to receive the baseline and the original pulse data sent by the sampling module 100, thereby determining target pulse data, and finally selectively outputting the target pulse data through the second comparing module 600.
According to the embodiment of the invention, the problems that the lifting baseline in the pulse data is not high enough to be removed or is not accurate enough are solved through the sampling module 100, the mean filtering module 200, the first comparing module 300, the baseline acquiring module 400, the subtracter module 500 and the second comparing module 600, and the beneficial effects of accurately and efficiently removing the lifting baseline in the pulse data are obtained.
As shown in fig. 8, in an embodiment, on the basis of the previous embodiment, there is further provided a pulse data processing apparatus, which further includes a first delay module 10, a second delay module 20, a third delay module 30, and a fourth delay module 40.
Specifically, the first delay module 10 and the first mean value filtering unit 210 have the same window width and simultaneously acquire the original pulse data, the first delay module 10 is configured to output first segment data, and the first mean value filtering unit 210 is configured to discard the first segment data to continuously acquire the original pulse data after acquiring the original pulse data of the size of the first window; the second delay module 20 and the second average filtering unit 220 have the same data width and simultaneously acquire the original pulse data, the second delay module 20 is configured to output second segment data, and the second average filtering unit 220 is configured to discard the second segment data after acquiring the original pulse data of the second window size to continuously acquire the original pulse data. The third delay module 30 has the same window width as the second average filtering unit 220, the third delay module 30 is configured to obtain the first average value, and output the third segment data after the baseline obtaining module 400 obtains the maximum value, and the baseline obtaining module 400 is further configured to set data between the lift start point and the lift end point in the third segment data as the maximum value to determine the baseline. The fourth delay module 40 has the same window width as the second average filtering unit 220, the fourth delay module 40 is configured to obtain the original pulse data and output the fourth segment data when the subtractor module 500 obtains the baseline, and the subtractor module 500 is further configured to determine the target pulse data after subtracting the baseline from the fourth segment data, where the data width may be understood as the window width.
In this embodiment, the pulse data processing apparatus has a requirement on real-time performance, data in the pulse data processing apparatus cannot be automatically cached, and a Verilog language can be used for programming to execute the pulse data processing method. The First delay module 10, the second delay module 20, the third delay module 30, and the fourth delay module 40 are all FIFO (First Input First Output) memories.
Specifically, the sampling module 100 simultaneously outputs the original pulse data to the first average filtering unit 210, the first delay module 10, the second average filtering unit 220, and the second delay module 20, where the first average filtering unit 210 and the first delay module 10 are full of N data points, and the second average filtering unit 220 and the second delay module 20 are full of M data points, and because the sizes of M and N are much smaller than the size of the original pulse data, the original pulse data needs to be stored continuously after the first average filtering unit 210 is full of M data points, at this time, the first delay module 10 outputs the first segment data, that is, the data point that enters the first delay module 10 at first, the first average filtering unit 210 subtracts the data point, so as to continuously obtain the next data point in the original pulse data, and the processing methods of the second average filtering unit 220 and the second delay module 20 are the same as above, which is not repeated in this embodiment of the present invention. The first average filtering unit 210 and the second average filtering unit 220 output the first average value and the second average value at the same time, that is, when the first average filtering unit 210 outputs the first average value, the second average filtering unit 220 also outputs the first second average value.
Further, the results of the first average value and the second average value are input into the first comparing module 300, whether the original pulse data has a partial baseline lifting or not can be determined by comparing the two results, and the difference result is input into the baseline acquiring module 400. For example, if the output point a of the first comparator module 300 is the baseline lifting starting point, the baseline acquisition module 400 may obtain the maximum value of the first mean midpoint a and the number M-1 thereafter. Further, the result of the first mean filtering unit 210 is input into the third delay module 30. In this embodiment, the width of the third delay module 30 is the same as the window size of the second mean filtering unit 220. It should be noted that the result of the third delay module 30 lags behind the first mean value M data points, that is, when the first mean filtering unit 210 outputs the M +1 data points, the third delay module 20 outputs the 1 st data point, and the output result of the third delay module 20 lags behind the first comparison module 300, and the M data points, that is, when the third delay module 30 outputs the result corresponding to the point a, the first comparison module 300 already outputs the result corresponding to the point a + M-1, and meanwhile, if a is the starting point, the baseline acquisition module 400 already obtains the maximum value from the point a to the point a + M-1. Further, the output result of the third delay module 30 is input to the baseline acquisition module 400, and if the input data point of the third segment is the baseline lifting start point, the values of the lifting start point and M-1 data points after the lifting start point in the third segment are set to the maximum values obtained in the above steps, otherwise, the values are kept unchanged. The new third segment data result obtained by the step is the baseline result.
Further, after the result of the baseline is inputted to the subtractor module 500, the original pulse data has been lost from the pulse data processing apparatus, so the sampling module 100 needs to input the original pulse data to the fourth delay module 40. For example, when the baseline acquisition module 400 outputs the baseline result corresponding to the point a, the fourth delay module 40 just outputs the original pulse data result corresponding to the point a, and inputs the data corresponding to the baseline and the fourth segment into the subtractor module 500, and the subtractor module 500 may output the difference result between the fourth segment data and the corresponding baseline data to obtain the target pulse data. Further, the second comparator module 600 inputs the target pulse data obtained by the subtractor module 500, and outputs a final result.
According to the embodiment of the invention, the problem that the pulse data in the real-time system cannot be cached is solved through the first delay module 10, the second delay module 20, the third delay module 30 and the fourth delay module 40, and the efficiency of removing the baseline uplift in the pulse data is further improved.
As shown in fig. 9, in one embodiment, a blood cell analyzer 700 is provided, the blood cell analyzer 700 including a pulse data processing apparatus 800 according to any one of the embodiments of the present invention.
In this embodiment, the sampling module 100 in the pulse data processing apparatus 800 is specifically configured to perform pulse detection on target blood cells to obtain raw pulse data of the target blood cells.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, and these are all within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method of pulse data processing, the method comprising:
acquiring original pulse data;
determining a first mean value of the original pulse data based on a first window size, and determining a second mean value of the original pulse data based on a second window size, wherein the first window size is smaller than the second window size, and the first window size and the second window size are both larger than the data width of single pulse data in the original pulse data;
determining whether the original pulse data has baseline lifting according to the magnitude relation of the first mean value and the second mean value, and determining a lifting starting point of the baseline according to the first mean value and the second mean value when the original pulse data has baseline lifting;
determining the baseline according to the first mean and the lifting starting point;
target pulse data is determined from the raw pulse data and a baseline.
2. The method of claim 1, wherein said determining the baseline from the first mean and the origin of lift comprises:
acquiring the maximum value between the lifting starting point and the lifting end point from the first average value, wherein the distance between the lifting end point and the lifting starting point is the size of the second window;
determining the baseline according to the maximum value and the first mean value.
3. The method of claim 1, wherein determining target pulse data from the raw pulse data and a baseline comprises:
the target pulse data larger than the first threshold value is output as it is, and the target pulse data smaller than or equal to the first threshold value is output as the first threshold value.
4. An apparatus for pulse data processing, the apparatus comprising:
the sampling module is used for acquiring original pulse data;
the mean filtering module comprises a first mean filtering unit and a second mean filtering unit, wherein the first mean filtering unit is used for determining a first mean value of the original pulse data based on a first window size, the second mean filtering unit is used for determining a second mean value of the original pulse data based on a second window size, the first window size is smaller than the second window size, and the first window size and the second window size are both larger than the data width of single pulse data in the original pulse data;
the first comparison module is used for comparing the first mean value with the second mean value to determine whether the original pulse data has baseline lifting, and when the original pulse data has baseline lifting, the first comparison module is further used for determining a lifting starting point of the baseline according to the first mean value and the second mean value;
the base line acquisition module is used for determining the base line according to the first mean value and the lifting starting point;
and the subtractor module is used for determining target pulse data according to the original pulse data and the baseline.
5. The apparatus of claim 4, wherein the baseline acquisition module is further configured to acquire a maximum value between the lift start point and the lift end point from the first mean value, and determine the baseline according to the maximum value and the first mean value, wherein a distance between the lift end point and the lift start point is the second window size.
6. The apparatus of claim 4, further comprising:
and the second comparison module is used for outputting the target pulse data which is larger than the first threshold value as an original value and outputting the target pulse data which is smaller than or equal to the first threshold value as the first threshold value.
7. The apparatus of claim 4, further comprising:
the first delay module is used for outputting first segment data, and the first mean value filtering unit is used for discarding the first segment data after acquiring the original pulse data with the size of a first window so as to continuously acquire the original pulse data;
and the second delay module is used for outputting second segmented data, and the second mean filtering unit is used for discarding the second segmented data to continuously acquire the original pulse data after acquiring the original pulse data with the size of a second window.
8. The apparatus of claim 5, further comprising:
and the third delay module is used for acquiring the first average value and outputting third segment data after the baseline acquisition module acquires the maximum value, and the baseline acquisition module is also used for setting the third segment data between the lifting starting point and the lifting ending point as the maximum value so as to determine the baseline.
9. The apparatus of claim 7, further comprising:
and the fourth delay module is the same as the window width of the second mean value filtering unit, is used for acquiring the original pulse data and outputting fourth segmented data when the subtractor module acquires the baseline, and is also used for subtracting the baseline from the fourth segmented data to determine target pulse data.
10. A blood cell analyzer, comprising a pulse data processing device according to any one of claims 4 to 9, wherein the sampling module is specifically configured to obtain raw pulse data of a target blood cell by pulse detection of the target blood cell.
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