CN115736850B

CN115736850B - Pulse data classification system and classification method

Info

Publication number: CN115736850B
Application number: CN202310012128.9A
Authority: CN
Inventors: 李文友; 赵静; 沈新; 樊静; 陈莹; 刘冬; 刘松
Original assignee: Nanjing Dajing Tcm Information Technology Co ltd
Current assignee: Nanjing Dajing Tcm Information Technology Co ltd
Priority date: 2023-01-05
Filing date: 2023-01-05
Publication date: 2023-04-21
Anticipated expiration: 2043-01-05
Also published as: CN115736850A

Abstract

The invention provides a pulse data classification system which comprises a pulse data acquisition module, a waveform display module, a pulse data classification module, a basic management module, a health maintenance scheme recommendation module and a report output module, wherein the pulse data classification module calculates the type of pulse data of a tested person based on pressure value data of a plurality of parts of the tested person sampled by the pulse data acquisition module and a pressure value waveform diagram drawn by the waveform display module. The invention also provides a corresponding pulse data classification method. According to the invention, by collecting pulse signals and combining accurate data management and analysis, classification characteristic values and classification elements are obtained from characteristic values in various aspects of the pressure value oscillogram, and pulse data classification is performed based on the classification elements, so that an objective, standardized and unified quantitative pulse data classification method is formed, the pulse data classification efficiency is improved, the digitization of a pulse data classification means is promoted, and effective pulse data type analysis is provided.

Description

Pulse data classification system and classification method

Technical Field

The invention relates to the technical field of data processing, in particular to a pulse data classification system and a pulse data classification method.

Background

Pulse diagnosis is one of the most distinctive diagnostic methods in traditional Chinese medicine, belongs to the "looking and smelling about" diagnostic method of four diagnostic methods in traditional Chinese medicine, and is a very important ring in traditional Chinese medicine diagnosis. The pulse diagnosis is the pulse condition, i.e. the form of pulse should be pointed. The pulse condition can reflect the comprehensive information of viscera functions, qi and blood, yin and yang, which results from the movement of qi and blood in vessels of the human body. While qi and blood are closely related to viscera functions of the organism, and the viscera functions are changed, so that qi and blood operation is affected, and qi and blood operation fluctuation leads to pulse condition difference. By analyzing the pulse condition variation information, the viscera where the disease occurs and the nature of the disease and the further development of the disease condition can be judged.

For a long time, traditional Chinese medicine pulse diagnosis mainly depends on subjective consciousness judgment of doctors, is greatly influenced by aspects of professional level, clinical experience, diagnosis skills and the like of the doctors, and is also interfered by factors such as surrounding environment and the like, and the defects prevent development and application of pulse diagnosis to a certain extent. After 70 s, scholars at home and abroad conduct pulse diagnosis objectification research, develop a series of intelligent pulse condition detection devices, such as ZM type pulse condition analyzer, TP-I type tongue pulse condition digital analyzer, ZBOX-I type tongue pulse condition digital analyzer, three pulse condition detectors and the like, obtain certain results, but still have the defects: (1) The pulse condition instrument is mainly applied to teaching and scientific research institutions, is less in hospital application, is complex in operation and is difficult to popularize; (2) The pulse condition instrument has larger volume, is not easy to carry and is difficult to detect at any time and any place; (3) Most pulse meters are connected with a computer to complete transmission and detection of pulse data, and wireless or remote transmission and the like cannot be achieved.

At present, the old traditional Chinese medicine of the traditional Chinese medicine practitioner is relatively few, the young traditional Chinese medicine doctors are most, the pulse diagnosis is hard to inherit and learn, the traditional pulse diagnosis has strong subjectivity, and the traditional Chinese medicine practitioner can not master the middle-grade essence more skillfully by feeling according to the accumulated practical experience in the personal long-term diagnosis of the doctor. And the pulse condition identification lacks uniformity and no accurate standard.

In view of the foregoing, there is a need to provide a new system or method that seeks to address at least some of the above-mentioned problems.

Disclosure of Invention

Aiming at one or more problems in the prior art, the invention provides a pulse data classification system and a pulse data classification method, which acquire classification characteristic values and classification elements from characteristic values in multiple aspects of a pressure value oscillogram by collecting pulse signals and combining accurate data management and analysis, classify the pulse data based on the classification elements to form an objective, standardized and unified quantitative pulse data classification method, improve the classification efficiency of the pulse data, promote the digitization of pulse data classification means and provide effective pulse data type analysis.

The technical solution for realizing the purpose of the invention is as follows:

According to one aspect of the present invention, a pulse data classification system comprises:

the pulse data acquisition module is used for continuously sampling pulse signals of a tested person to obtain continuous pressure value data of a plurality of periods;

the waveform display module is used for receiving the pressure value data of the pulse data acquisition module, and sequentially drawing and displaying a pressure value waveform chart;

the pulse data classification module is used for calculating the type of the pulse data of the tested person based on the pressure value data of a plurality of parts of the tested person sampled by the pulse data acquisition module and the pressure value oscillogram drawn by the waveform display module;

the basic management module is used for configuring definition corresponding to the waveform diagram parameters and the pulse data types and setting a plurality of traditional Chinese medicine characteristic health care schemes corresponding to the pulse data types;

the health maintenance scheme recommending module is used for acquiring the corresponding health maintenance scheme in the basic management module based on the pulse data type calculated by the pulse data classifying module;

and the report output module is used for outputting the type of the pulse data and the corresponding definition and the health maintenance scheme.

Further, in the pulse data classification system of the present invention, the pulse data classification module includes:

the characteristic extraction module is used for extracting characteristic values of the pressure value oscillogram and outputting the characteristic values to the characteristic value calculation module, wherein the characteristic values comprise main wave height, tidal wave height, descending wave height, counterpulsation wave height, rising slope of a waveform, fluctuation period, rising time, gap time value and width of 1/3 of the main wave;

The characteristic value calculation module is used for calculating a classification characteristic value based on the characteristic value of the pressure value oscillogram and outputting the classification characteristic value to the element analysis module, and the classification characteristic value comprises: the average value of static pressure corresponding to the peak value of the pressure value, the average number of the peak value of the pressure value appearing in each minute, the average dynamic pressure value corresponding to the main wave of the waveform diagram, the rising branch slope, the fluency coefficient, the relaxation coefficient, the descending isthmus height, the dicrotic wave height, the tension coefficient, the pressure coefficient, the resistance coefficient, the elasticity coefficient and the smoothing coefficient of the waveform diagram of the pressure value;

the element analysis module is used for acquiring six classification elements based on the comparison result of the classification characteristic values and corresponding preset threshold values or standard values and outputting the six classification elements to the data type analysis module, wherein the six classification elements comprise a first element based on a static pressure average value corresponding to a pressure value peak value, a second element based on the average number of times of occurrence of the pressure value peak value in each minute, a third element based on an average dynamic pressure value corresponding to a waveform diagram main wave, fluency, tension and uniformity;

the data type analysis module is used for acquiring and outputting the whole pulse data type of the tested person based on six classification elements of a plurality of parts of the tested person.

Further, in the pulse data classification system of the present invention, the comparing the classification characteristic value in the element analysis module with the corresponding preset threshold value to obtain six classification elements specifically includes:

first element: when the static pressure average value corresponding to the pressure value peak value is smaller than the corresponding lower limit threshold value, the static pressure average value is marked as a first element; when the static pressure average value corresponding to the pressure value peak value is more than the corresponding lower threshold value and the average dynamic pressure value corresponding to the waveform diagram main wave value is less than the median value, the second type first element is marked;

the second element: when the average number of pressure value peaks appearing in each minute is less than the corresponding lower threshold value, the first type second element is marked; when the average number of pressure value peaks appearing in each minute is more than the corresponding lower threshold value, the second element is marked as a second type;

third element: when the average dynamic pressure value corresponding to the main wave of the waveform diagram is less than the corresponding lower threshold value, the waveform diagram is marked as a first type third element; when the average dynamic pressure value corresponding to the main wave of the waveform diagram is more than the corresponding lower threshold value, the waveform diagram is marked as a second type third element;

fluency: when the rising branch slope is satisfied with the rising branch slope being larger than the corresponding standard value, the descending isthmus height being smaller than the corresponding standard value, and the dicrotic wave height being larger than the corresponding standard value, or the descending isthmus height being smaller than the corresponding standard value, the dicrotic wave height being smaller than the corresponding standard value, the fluency coefficient being smaller than the corresponding standard value, and the soothing coefficient being larger than the corresponding standard value, the first fluency is recorded; when the descending isthmus height=its corresponding standard value, the dicrotic wave height=its corresponding standard value, and its corresponding lower limit threshold value < rising branch slope < its corresponding upper limit threshold value are simultaneously satisfied, the second type fluency is recorded;

Tension: when the tension coefficient is satisfied with the corresponding standard value, or the pressure coefficient is satisfied with the corresponding standard value, or the resistance coefficient is satisfied with the corresponding standard value, and the elasticity coefficient is satisfied with the corresponding standard value, the first type tension is marked; when the resistance coefficient < the corresponding standard value and the average dynamic pressure value corresponding to the waveform diagram main wave are simultaneously met and the resistance coefficient < the corresponding standard value, the second type tension is recorded;

uniformity: when the average times of the pressure value peak values in the period of less than or equal to each minute corresponding to the lower threshold value are met simultaneously, namely the average times of the pressure value peak values in the period of less than or equal to each minute corresponding to the upper threshold value, and the smoothing coefficient is more than the corresponding standard value, the first type uniformity is marked; when the average times of the pressure value peak value in each minute < the corresponding lower threshold value and the smoothing coefficient > and the corresponding standard value are met at the same time, the second type uniformity is marked; and when the average number of the pressure value peak values in each minute is more than the corresponding upper threshold value and the smoothing coefficient is more than the corresponding standard value, the third type uniformity is recorded.

Further, in the pulse data classification system of the present invention, the pulse data types in the data type analysis module are divided into a distribution element data type and a common element data type, and the distribution element data type and the common element data type are superimposed into the pulse data type of the whole subject, wherein the distribution element includes a first element, a third element, fluency and tension, and the common element includes a second element and uniformity.

Further, the pulse data classification system of the present invention specifically obtains the distribution element data types as follows:

when a plurality of parts of the tested person meet the condition that the first element is a first type first element and the static pressure average value corresponding to the pressure value peak value is more than or equal to the lower limit threshold value, recording the data type of the first distribution element as the first type first element; if a plurality of parts of the tested person simultaneously meet that the first element is a second type first element and the static pressure average value corresponding to the pressure value peak value is less than or equal to the upper limit threshold value, recording the data type of the first distribution element as the second type first element;

if a plurality of parts of the tested person meet the requirement that the third element is the first type third element, recording the data type of the second distribution element as the first type third element; if a plurality of parts of the tested person meet the requirement that the third element is the second type third element, recording the data type of the second distribution element as the second type third element;

if the plurality of parts of the tested person simultaneously meet the requirement that the fluency is the first type fluency, the third distribution element data type is the first type fluency; if the plurality of parts of the tested person meet the requirement that the fluency is the second type fluency at the same time, recording the third distribution element data type as the second type fluency;

If the part of the tested person at a plurality of parts meets the tension degree as the first type tension degree, recording the fourth distribution element data type as the first type tension degree; if the part of the tested person at a plurality of parts meets the second type of tension, the fourth distribution element data type is recorded as the second type of tension.

Further, the pulse data classification system of the present invention specifically obtains the common element data types as follows:

calculating the average value of the average times of the pressure value peak value in each minute of a plurality of parts of the tested person, and if the average value is smaller than the lower threshold value, recording the data type of the first common element as a first second element; if the average value is greater than the upper limit value, recording the first common element data type as a second element;

when the uniformity of more than two parts of the tested person is the first type uniformity, the second common element data type is the first type uniformity; when more than two parts exist, the uniformity is the second type uniformity, the second common element data type is recorded as the second type uniformity; and when more than two parts exist, the uniformity is third type uniformity, the second common element data type is third type uniformity.

Further, in the pulse data classification system, the pulse data acquisition module changes the sampled static pressure according to the preset rule during sampling, selects the static pressure value with the maximum signal amplitude, and continuously samples the tested person for 10.24 seconds under the condition of keeping the static pressure value.

According to another aspect of the present invention, a pulse data classification method includes:

s1, continuously sampling pulse signals of a tested person at a fixed frequency to obtain continuous pressure value data of a plurality of periods, and drawing a pressure value oscillogram;

s2, extracting characteristic values of a pressure value oscillogram, wherein the characteristic values comprise main wave height, tidal wave height, descending wave height, dicrotic wave height, rising branch slope of a waveform, fluctuation period, rising branch time, gap time value and width of 1/3 of the main wave;

s3, calculating a classification characteristic value of the pulse data according to the characteristic value, wherein the classification characteristic value comprises the following components: the average value of static pressure corresponding to the peak value of the pressure value, the average number of the peak value of the pressure value appearing in each minute, the average dynamic pressure value corresponding to the main wave of the waveform diagram, the rising branch slope, the fluency coefficient, the relaxation coefficient, the descending isthmus height, the dicrotic wave height, the tension coefficient, the pressure coefficient, the resistance coefficient, the elasticity coefficient and the smoothing coefficient of the waveform diagram of the pressure value;

S4, comparing the classification characteristic value with a corresponding preset threshold value or standard value, and obtaining six classification elements according to a comparison result, wherein the six classification elements comprise a first element based on a static pressure average value corresponding to a pressure value peak value, a second element based on the average number of times of occurrence of the pressure value peak value in each minute, and a third element, fluency, tension and uniformity of an average dynamic pressure value corresponding to a waveform diagram main wave;

s5, acquiring six classification elements of a plurality of parts of the tested person, and acquiring the overall pulse data type of the tested person according to the six distribution elements.

Further, in the pulse data classification method of the present invention, the specific step of comparing the classification characteristic value in S4 with the corresponding preset threshold or standard value includes:

s4-1, when the static pressure average value corresponding to the pressure value peak value is smaller than the corresponding lower limit threshold value, marking the static pressure average value as a first element; when the static pressure average value corresponding to the pressure value peak value is more than the corresponding lower threshold value and the average dynamic pressure value corresponding to the waveform diagram main wave value is less than the median value, the second type first element is marked;

s4-2, when the average number of pressure value peaks appearing in each minute is less than the corresponding lower threshold value, marking as a first type second element; when the average number of pressure value peaks appearing in each minute is more than the corresponding lower threshold value, the second element is marked as a second type;

S4-3, when the average dynamic pressure value corresponding to the main wave of the waveform diagram is smaller than the corresponding lower threshold value, marking the average dynamic pressure value as a first type third element; when the average dynamic pressure value corresponding to the main wave of the waveform diagram is more than the corresponding lower threshold value, the waveform diagram is marked as a second type third element;

s4-4, when the rising branch slope > its corresponding standard value, the descending isthmus height=its corresponding standard value, the dicrotic wave height=its corresponding standard value are simultaneously satisfied, or the descending isthmus height=its corresponding standard value, the dicrotic wave height=its corresponding standard value, the fluency coefficient < its corresponding standard value, the soothing coefficient > its corresponding standard value are simultaneously satisfied, the first fluency is recorded; when the descending isthmus height=its corresponding standard value, the dicrotic wave height=its corresponding standard value, and its corresponding lower limit threshold value < rising branch slope < its corresponding upper limit threshold value are simultaneously satisfied, the second type fluency is recorded;

s4-5, when the tension coefficient is satisfied with the corresponding standard value, or the pressure coefficient is satisfied with the corresponding standard value, or the resistance coefficient is satisfied with the corresponding standard value, and the elasticity coefficient is satisfied with the corresponding standard value, the first type tension is marked; when the resistance coefficient < the corresponding standard value and the average dynamic pressure value corresponding to the waveform diagram main wave are simultaneously met and the resistance coefficient < the corresponding standard value, the second type tension is recorded;

S4-6, when the average times of the pressure value peak values in the time of meeting the corresponding lower threshold value is less than or equal to each minute = the corresponding upper threshold value and the smoothing coefficient is greater than the corresponding standard value, marking as the first type uniformity; when the average times of the pressure value peak value in each minute < the corresponding lower threshold value and the smoothing coefficient > and the corresponding standard value are met at the same time, the second type uniformity is marked; and when the average number of the pressure value peak values in each minute is more than the corresponding upper threshold value and the smoothing coefficient is more than the corresponding standard value, the third type uniformity is recorded.

Further, in the pulse data classification method of the present invention, the specific step of acquiring the overall pulse data type of the tested person according to the six distributed elements in S5 includes:

s5-1, when a plurality of parts of a tested person meet that the first element is a first element at the same time, and the static pressure average value corresponding to the pressure value peak value is more than or equal to the lower limit threshold value, recording the data type of the first distribution element as the first element; if a plurality of parts of the tested person simultaneously meet that the first element is a second type first element and the static pressure average value corresponding to the pressure value peak value is less than or equal to the upper limit threshold value, recording the data type of the first distribution element as the second type first element;

S5-2, if a plurality of parts of the tested person meet the requirement that the third element is the first type third element, recording the data type of the second distribution element as the first type third element; if a plurality of parts of the tested person meet the requirement that the third element is the second type third element, recording the data type of the second distribution element as the second type third element;

s5-3, if a plurality of parts of the tested person meet the requirement that the fluency is the first fluency at the same time, the third distribution element data type is the first fluency; if the plurality of parts of the tested person meet the requirement that the fluency is the second type fluency at the same time, recording the third distribution element data type as the second type fluency;

s5-4, if the part of the tested person at a plurality of parts meets the requirement that the tension is the first type tension, recording the data type of the fourth distribution element as the first type tension; if the part of the tested person at a plurality of parts meets the second type of tension, recording the fourth distribution element data type as the second type of tension;

s5-5, calculating the average value of the average times of the pressure value peak value in each minute of a plurality of parts of the tested person, and if the average value is smaller than a lower threshold value, recording the data type of the first common element as a first type second element; if the average value is greater than the upper limit value, recording the first common element data type as a second element;

S5-6, in a plurality of parts of the tested person, when the uniformity of more than two parts is the first type uniformity, the second common element data type is the first type uniformity; when more than two parts exist, the uniformity is the second type uniformity, the second common element data type is recorded as the second type uniformity; when more than two parts exist, the uniformity is third type uniformity, the second common element data type is marked as third type uniformity;

s5-7, superposing the obtained four distribution element data types and the two common element data types into the integral pulse data type of the tested person.

Compared with the prior art, the technical scheme provided by the invention has the following technical effects:

according to the invention, by collecting pulse signals and combining accurate data management and analysis, classification characteristic values and classification elements are obtained from characteristic values in various aspects of the pressure value oscillogram, and pulse data classification is performed based on the classification elements, so that an objective, standardized and unified quantitative pulse data classification method is formed, the pulse data classification efficiency is improved, the digitization of a pulse data classification means is promoted, and effective pulse data type analysis is provided.

Drawings

The accompanying drawings are included to provide a further understanding of the invention, and together with the description serve to explain the embodiments of the invention, and do not constitute a limitation of the invention. In the drawings:

FIG. 1 shows a waveform diagram of pressure values according to an embodiment of the present invention.

Fig. 2 is a diagram showing a structure of a pulse data classification system according to an embodiment of the present invention.

Fig. 3 is a flowchart of a pulse data classification method according to an embodiment of the invention.

Detailed Description

For a further understanding of the present invention, preferred embodiments of the invention are described below in conjunction with the examples, but it should be understood that these descriptions are merely intended to illustrate further features and advantages of the invention, and are not limiting of the claims of the invention.

The description of this section is intended to be illustrative of only a few exemplary embodiments and the invention is not to be limited in scope by the description of the embodiments. Combinations of the different embodiments, and alternatives of features from the same or similar prior art means and embodiments are also within the scope of the description and protection of the invention.

According to one embodiment of the present invention, a pulse data classification system, as shown in fig. 2, includes a pulse data acquisition module 1, a waveform display module 2, a pulse data classification module 4, a base management module 3, a regimen recommendation module 6, and a report output module 5. The pulse data acquisition module 1 is used for continuously sampling pulse signals of a tested person to obtain continuous pressure value data of a plurality of periods. The waveform display module 2 is configured to receive the pressure value data of the pulse data acquisition module 1, and sequentially draw and display a pressure value waveform chart, as shown in fig. 1. The pulse data classification module 4 is used for calculating the type of the pulse data of the tested person based on the pressure value data of the tested person at a plurality of parts sampled by the pulse data acquisition module 1 and the pressure value waveform diagram drawn by the waveform display module 2. The basic management module 3 is used for configuring definition corresponding to the waveform diagram parameters and the pulse data types and setting a plurality of traditional Chinese medicine characteristic health care schemes corresponding to the pulse data types. The health maintenance scheme recommending module 6 is configured to obtain a corresponding health maintenance scheme in the basic management module 3 based on the pulse data type calculated by the pulse data classifying module 4. The report output module 5 is used for outputting the type of the pulse data and the corresponding definition and the health care scheme.

The pulse data acquisition module 1 transforms the sampled static pressure according to a preset rule during sampling, selects a static pressure value when the signal amplitude is maximum, and continuously samples the tested person for 10.24 seconds under the condition of keeping the static pressure value. In a specific embodiment, the pulse data acquisition module samples pulse signals of three parts of the cun, guan and chi of the tested person. In one embodiment, the waveform display module 2 includes a display, and draws a waveform chart according to the pressure value of the pulse signal, and displays the waveform chart through the display.

In a specific embodiment, the basic management module 3 includes a main control module and a memory, the waveform parameters and the threshold values thereof can be set by the main control module and stored by the memory, and the memory also stores the definitions and the corresponding health care schemes corresponding to the pulse data types.

The pulse data classification module 4 includes a feature extraction module 41, a feature value calculation module 42, an element analysis module 43, and a data type analysis module 44. Wherein:

the feature extraction module 41 is configured to extract feature values of the waveform chart of the pressure value and output the feature values to the feature value calculation module 42, where the feature values include a main wave height h1, a main wave height h2, a tidal wave height h3, a descending isthmus height h4, a dicrotic wave height h5, an ascending branch slope k of the waveform, a fluctuation period t, an ascending branch time t1, a gap time t6, and a width w at 1/3 of the main wave, as shown in fig. 1. The parameters in fig. 1 are specifically as follows: h1 refers to the main height, i.e., the length of the perpendicular from the main peak to the base line, and in one embodiment h1 may represent the pressure experienced by the wall of the tube during systole. h2 refers to the main wave height, i.e., the amplitude of the main wave drop, onset of tidal wave. h3 refers to the tidal wave height, i.e., the amplitude of the peak to baseline of the tidal wave, and in one embodiment h3 may reflect arterial vessel tension and peripheral resistance status. h4 refers to the descending isthmus height, i.e., the amplitude of the descending isthmus valley bottom to baseline, and in one embodiment h4 may reflect the magnitude of the peripheral resistance of the artery. h5 refers to the dicrotic wave height, i.e., the amplitude of the dicrotic peak pole to the base line of the level of the valley in the fall, and in one embodiment h5 may reflect the elastic condition of the aorta. k is the rising branch slope of the waveform under the current probe, and the slope value is the average value of the slope of the starting point and the main wave top. t is the duration of the fluctuation period, i.e. the start to end point, and in one embodiment the value of t corresponds to a cardiac cycle. t1 is the time of the ascending branch, i.e., the time from the beginning to the main peak, and in one embodiment the value of t1 corresponds to the rapid left ventricular ejection period. t6 gap duration, the time when the amplitude of the current period is less than 15% h1 is reversely calculated from the starting point of the next period. w is the width at 1/3 of the main wave and in one embodiment w corresponds to the time at which a high pressure level in the artery is maintained. To ensure accuracy of the extracted feature values, waveform data is sampled continuously for 10.24 seconds, and all valid waveform arrays within the sampling period can be synthesized.

A feature value calculation module 42, configured to calculate a classification feature value based on the feature value of the pressure value waveform chart, and output the classification feature value to the element analysis module 43, where the classification feature value includes: the average value of static pressure corresponding to the peak value of the pressure value, the average number of the peak value of the pressure value occurring in each minute, the average dynamic pressure value corresponding to the main wave of the waveform diagram, the rising branch slope, the fluency coefficient, the relaxation coefficient, the descending isthmus height, the dicrotic wave height, the tension coefficient, the pressure coefficient, the resistance coefficient, the elasticity coefficient and the smoothing coefficient of the waveform diagram of the pressure value. In order to reflect the physiological meaning of the pulse condition more sensitively and accurately, the specific process of further processing and analyzing the data from the multiple dimensions of the time index, the amplitude index, the area index and the ratio index is as follows:

(1) Static pressure average value corresponding to pressure value peak value:

f refers to the static pressure applied by the sensor during each cycle, N represents the number of current cycles, and N represents the total number of cycles.

(2) Average number of pressure value peaks per minute:

v represents the fourier signal of the pulse signal acquired on one sensor calculated by a fast fourier algorithm (FFT), and n represents the number of sensors.

(3) Average dynamic pressure value corresponding to waveform diagram main wave:

h1 represents the dynamic pressure at the main wave height in a certain period, N represents the current period number, and N represents the total period number.

(4) Rising branch slope:

k represents the slope value of each cycle of the waveform, and n represents the current number of cycles.

(5) Fluency coefficient:

the fluency coefficient is the ratio of the main wave height to the main wave isthmus amplitude, and m and n represent the number of periods.

(6) Relief coefficient:

the relaxation coefficients represent the relaxation coefficients of the current waveform, and m and n represent the number of cycles of the acquired waveform.

(7) Canyon height lowering:

n, m denote the number of cycles of the acquisition waveform.

(8) Height of the dicrotic wave:

n represents the number of cycles of the acquisition waveform.

(9) Tension coefficient:

h1 is the main wave height dynamic pressure representation, h3 is the tidal wave height dynamic pressure representation, n, m is the number of cycles of the acquired waveform.

(10) Pressure coefficient:

w is the height of one of 1/3 of the main wave, in one embodiment w corresponds to the time during which a high pressure level in the artery is maintained, t is the period of the wave, and n, m is the number of periods in which the waveform is acquired.

(11) Coefficient of resistance:

/>

the resistance coefficient refers to the ratio of the descending isthmus height to the dominant wave, and in one embodiment the resistance coefficient may reflect the peripheral resistance of the artery; n, m denote the number of cycles of the acquisition waveform.

(12) Coefficient of elasticity:

the elasticity coefficient refers to the specific gravity of the height of the dicrotic wave to the main wave, and in one specific embodiment, the elasticity coefficient can reflect the elasticity condition of the aorta; n, m denote the number of cycles of the acquisition waveform.

(13) Smoothing coefficients:

the smoothing coefficient means that the time for reversely calculating the amplitude of the period to be smaller than 15% h1 at the starting point of the next period is the proportion of the whole pulse condition period, the uniformity of the pulse condition is represented by t6/t, t is the fluctuation period time value, t6 is the gap time value, and n and m are the period number of the acquired waveform.

The element analysis module 43 is configured to obtain six classification elements based on a comparison result between the classification feature value and a corresponding preset threshold value or standard value, and output the six classification elements to the data type analysis module 44, where the six classification elements include a first element based on a static pressure average value corresponding to a pressure value peak, a second element based on an average number of times of occurrence of the pressure value peak in each minute, and a third element based on an average dynamic pressure value corresponding to a waveform diagram main wave, fluency, tension, and uniformity. The data type analysis module is used for acquiring and outputting the whole pulse data type of the tested person based on six classification elements of a plurality of parts of the tested person.

The comparing the classification characteristic value in the element analysis module 43 with the corresponding preset threshold value to obtain six classification elements specifically includes: first element: when the static pressure average value corresponding to the pressure value peak value is smaller than the corresponding lower limit threshold value, the static pressure average value is marked as a first element; and when the static pressure average value corresponding to the pressure value peak value is more than the corresponding lower threshold value and the average dynamic pressure value corresponding to the waveform diagram main wave value is less than the median value, the second type first element is marked. The second element: when the average number of pressure value peaks appearing in each minute is less than the corresponding lower threshold value, the first type second element is marked; and when the average number of pressure value peaks appearing in each minute is more than the corresponding lower threshold value, the second element is marked as a second type. Third element: when the average dynamic pressure value corresponding to the main wave of the waveform diagram is less than the corresponding lower threshold value, the waveform diagram is marked as a first type third element; when the average dynamic pressure value corresponding to the main wave of the waveform diagram is greater than the corresponding lower threshold value, the waveform diagram is marked as a second type third element. Fluency: when the rising branch slope is satisfied with the rising branch slope being larger than the corresponding standard value, the descending isthmus height being smaller than the corresponding standard value, and the dicrotic wave height being larger than the corresponding standard value, or the descending isthmus height being smaller than the corresponding standard value, the dicrotic wave height being smaller than the corresponding standard value, the fluency coefficient being smaller than the corresponding standard value, and the soothing coefficient being larger than the corresponding standard value, the first fluency is recorded; and when the descending isthmus height=the corresponding standard value, the dicrotic wave height=the corresponding standard value and the corresponding lower limit threshold value < the ascending branch slope < the corresponding upper limit threshold value are simultaneously satisfied, the second type fluency is recorded. Tension: when the tension coefficient is satisfied with the corresponding standard value, or the pressure coefficient is satisfied with the corresponding standard value, or the resistance coefficient is satisfied with the corresponding standard value, and the elasticity coefficient is satisfied with the corresponding standard value, the first type tension is marked; and when the resistance coefficient < the corresponding standard value and the average dynamic pressure value corresponding to the waveform diagram main wave are simultaneously satisfied, the second type tension is recorded. Uniformity: when the average times of the pressure value peak values in the period of less than or equal to each minute corresponding to the lower threshold value are met simultaneously, namely the average times of the pressure value peak values in the period of less than or equal to each minute corresponding to the upper threshold value, and the smoothing coefficient is more than the corresponding standard value, the first type uniformity is marked; when the average times of the pressure value peak value in each minute < the corresponding lower threshold value and the smoothing coefficient > and the corresponding standard value are met at the same time, the second type uniformity is marked; and when the average number of the pressure value peak values in each minute is more than the corresponding upper threshold value and the smoothing coefficient is more than the corresponding standard value, the third type uniformity is recorded.

In a specific embodiment, the six-element classification in the element analysis module is specifically determined as:

if the static pressure relative value is less than the lower limit value, the model is marked as a floating model, and if the static pressure relative value is more than the upper limit value and the average dynamic pressure value corresponding to the main wave diagram is less than the median value in the normal section, the model is marked as a sinking model.

If the average number of the pressure value peak values appearing in each minute is less than the lower limit value, the pressure value peak value is recorded as a delay value; if the average number of pressure peak values occurring per minute > the upper limit value, the number is counted.

If the average dynamic pressure value corresponding to the main wave of the waveform diagram is less than the lower limit value, the waveform diagram is marked as a weak type; if the average dynamic pressure value corresponding to the main wave of the waveform map is greater than the upper limit value, the waveform map is marked as powerful.

Fluency: (a) rule 1: and simultaneously satisfies K > standard value, h4=standard value, h5=standard value. Rule 2: simultaneously, the standard values of h4=standard values, h5=standard values, h2/h1< standard values and (h 3-h 2)/h 1> are satisfied. If any of the above rules is satisfied, the slide type is defined. (b) And satisfying h4=standard value, h5=standard value and lower limit value < K < upper limit value, and then marking as astringent.

Tension: (a) rule 1: h3/h1> standard value. Rule 2: w/t > standard value. Rule 3: and simultaneously satisfies h4/h1> standard value and h5/h1< standard value. If any of the above rules is satisfied, the string is marked as a chord. (b) And simultaneously, h4/h1< standard value and h1< standard value are satisfied, and the soft type is marked.

Uniformity: (a) And meanwhile, the lower limit value is less than or equal to V=the upper limit value and t6/t > standard value is met, and the generation type is marked. (b) And satisfying V < lower limit value and t6/t > standard value, and marking as junction type. (c) And meanwhile, the V > upper limit value and the t6/t > standard value are met, and the model is marked as the pro-model.

In this particular embodiment, the threshold values for each classification characteristic value are as follows:

parameter value	Upper limit value	Lower limit value	Standard value
				F _pos	50	15	--
V	80	60	--
				h1	6	4	--
K	--	--	1.8
				h2/h1	--	--	0.4
(h3-h2)/h1	--	--	0.1
				h4	--	--	0
H5	--	--	0
				h3/h1	--	--	0.7
w/t	--	--	0.2
				h4/h1	--	--	0.4
h5/h1	--	--	0.05
				t6/t	--	--	0.6

The pulse data types in the data type analysis module 44 are divided into a distribution element data type and a common element data type, and the distribution element data type and the common element data type are overlapped to form an integral pulse data type of the tested person, wherein the distribution element comprises a first element, a third element, fluency and tension, the distribution elements have no influence on each other, and the common element comprises a second element and uniformity. The acquisition of the distribution element data type is specifically as follows: when a plurality of parts of the tested person meet the condition that the first element is a first type first element and the static pressure average value corresponding to the pressure value peak value is more than or equal to the lower limit threshold value, recording the data type of the first distribution element as the first type first element; if a plurality of parts of the tested person simultaneously meet that the first element is a second type first element and the static pressure average value corresponding to the pressure value peak value is less than or equal to the upper limit threshold value, the data type of the first distribution element is recorded as the second type first element. If a plurality of parts of the tested person meet the requirement that the third element is the first type third element, recording the data type of the second distribution element as the first type third element; if the plurality of parts of the tested person simultaneously meet the third element as the second type third element, the second distribution element data type is recorded as the second type third element. If the plurality of parts of the tested person simultaneously meet the requirement that the fluency is the first type fluency, the third distribution element data type is the first type fluency; if the fluency of the plurality of parts of the tested person is the second type fluency, the third distribution element data type is recorded as the second type fluency. If the part of the tested person at a plurality of parts meets the tension degree as the first type tension degree, recording the fourth distribution element data type as the first type tension degree; if the part of the tested person at a plurality of parts meets the second type of tension, the fourth distribution element data type is recorded as the second type of tension. The type of the acquired common element data is specifically as follows: calculating the average value of the average times of the pressure value peak value in each minute of a plurality of parts of the tested person, and if the average value is smaller than the lower threshold value, recording the data type of the first common element as a first second element; if the average value is greater than the upper limit value, the first common element data type is recorded as a second element of the second type. When the uniformity of more than two parts of the tested person is the first type uniformity, the second common element data type is the first type uniformity; when more than two parts exist, the uniformity is the second type uniformity, the second common element data type is recorded as the second type uniformity; and when more than two parts exist, the uniformity is third type uniformity, the second common element data type is third type uniformity.

In a specific embodiment, the pulse data type classification is specifically as follows: if 3 parts of the tested person are floating at the same time and the static pressure relative value corresponding to the pressure value peak value is not lower than the lower limit value, the first distribution element data type is floating; if the 3 parts of the tested person are heavy at the same time and the static pressure relative value corresponding to the pressure value peak value is not higher than the upper limit value, the first distribution element data type is heavy. If the 3 parts of the tested person are of the weak type at the same time, the second distribution element data type is of the weak type; if the 3 parts of the tested person are powerful at the same time, the second distribution element data type is powerful. If the fluency of 3 parts of the tested person is smooth, the third distribution element data type is smooth; if the fluency of 3 parts of the tested person is astringent at the same time, the third distribution element data type is astringent. If the tension of more than 2 parts of the tested person is chord type, the fourth distribution element data type is chord type; if the tension of more than 2 parts of the tested person is soft at the same time, the fourth distribution element data type is soft. The four pulse data types obtained above are combined and superimposed. Calculating the average value of the average times of pressure value peak values in each minute of three parts of the tested person, and if the average value is less than a lower threshold value, the first common element is digital; if the mean value is greater than the upper threshold, the first common element is late. If the uniformity of more than 2 parts of the tested person is knot-shaped, the second common element is knot-shaped; if the uniformity of more than 2 parts of the tested person is the generation type at the same time, the second common element is the generation type; if uniformity of more than 2 parts of the tested person is the acceleration type at the same time, the second common element is the acceleration type. And combining and superposing the first four pulse data types and the last two pulse data types to form a final pulse data type.

According to another embodiment of the present invention, a pulse data classification method, as shown in fig. 3, includes:

s1, continuously sampling pulse signals of a tested person at a fixed frequency to obtain continuous pressure value data of a plurality of periods, and drawing a pressure value oscillogram.

S2, extracting characteristic values of a pressure value oscillogram, wherein the characteristic values comprise a main wave height, a tide wave height, a descending wave height, a dicrotic wave height, an ascending branch slope of a waveform, a fluctuation period, an ascending branch time, a gap time value and a width of 1/3 of the main wave.

S3, calculating a classification characteristic value of the pulse data according to the characteristic value, wherein the classification characteristic value comprises the following components: the average value of static pressure corresponding to the peak value of the pressure value, the average number of the peak value of the pressure value occurring in each minute, the average dynamic pressure value corresponding to the main wave of the waveform diagram, the rising branch slope, the fluency coefficient, the relaxation coefficient, the descending isthmus height, the dicrotic wave height, the tension coefficient, the pressure coefficient, the resistance coefficient, the elasticity coefficient and the smoothing coefficient of the waveform diagram of the pressure value.

S4, comparing the classification characteristic value with a corresponding preset threshold value or standard value, and obtaining six classification elements according to a comparison result, wherein the six classification elements comprise a first element based on a static pressure average value corresponding to a pressure value peak value, a second element based on the average number of times of occurrence of the pressure value peak value in each minute, and a third element, fluency, tension and uniformity of an average dynamic pressure value corresponding to a waveform diagram main wave. The method comprises the following specific steps:

S5, acquiring six classification elements of a plurality of parts of the tested person, and acquiring the overall pulse data type of the tested person according to the six distribution elements. The method comprises the following specific steps:

The description and applications of the present invention herein are illustrative and are not intended to limit the scope of the invention to the embodiments described above. The relevant descriptions of effects, advantages and the like in the description may not be presented in practical experimental examples due to uncertainty of specific condition parameters or influence of other factors, and the relevant descriptions of effects, advantages and the like are not used for limiting the scope of the invention. Variations and modifications of the embodiments disclosed herein are possible, and alternatives and equivalents of the various components of the embodiments are known to those of ordinary skill in the art. It will be clear to those skilled in the art that the present invention may be embodied in other forms, structures, arrangements, proportions, and with other assemblies, materials, and components, without departing from the spirit or essential characteristics thereof. Other variations and modifications of the embodiments disclosed herein may be made without departing from the scope and spirit of the invention.

Claims

1. A pulse data classification system, comprising:

the pulse data classification module is used for calculating the type of the pulse data of the tested person based on the pressure value data of a plurality of parts of the tested person sampled by the pulse data acquisition module and the pressure value oscillogram drawn by the waveform display module; the pulse data classification module comprises:

The element analysis module is used for acquiring six classification elements based on the comparison result of the classification characteristic values and corresponding preset threshold values or standard values and outputting the six classification elements to the data type analysis module, wherein the six classification elements comprise a first element based on a static pressure average value corresponding to a pressure value peak value, a second element based on the average number of times of occurrence of the pressure value peak value in each minute, a third element based on an average dynamic pressure value corresponding to a waveform diagram main wave, fluency, tension and uniformity; the element analysis module compares the classification characteristic value with a corresponding preset threshold value to obtain six classification elements specifically:

Uniformity: when the average times of the pressure value peak values in the period of less than or equal to each minute corresponding to the lower threshold value are met simultaneously, namely the average times of the pressure value peak values in the period of less than or equal to each minute corresponding to the upper threshold value, and the smoothing coefficient is more than the corresponding standard value, the first type uniformity is marked; when the average times of the pressure value peak value in each minute < the corresponding lower threshold value and the smoothing coefficient > and the corresponding standard value are met at the same time, the second type uniformity is marked; when the average number of the pressure value peak values in each minute is more than the corresponding upper threshold value and the smoothing coefficient is more than the corresponding standard value, the third type uniformity is recorded;

the data type analysis module is used for acquiring and outputting the overall pulse data type of the tested person based on six classification elements of a plurality of parts of the tested person;

2. The pulse data classification system of claim 1, wherein the pulse data types in the data type analysis module are divided into a distribution element data type and a common element data type, the distribution element data type and the common element data type are superimposed into a pulse data type of the whole subject, wherein the distribution element comprises a first element, a third element, fluency and tension, and the common element comprises a second element and uniformity.

3. The pulse data classification system of claim 2, wherein the acquisition of the distribution element data types is specifically:

4. The pulse data classification system of claim 2, wherein the acquiring of the common element data types is specifically:

5. The pulse data classification system of claim 1, wherein the pulse data acquisition module transforms the sampled static pressure according to a predetermined rule during sampling and selects a static pressure value at which the signal amplitude is maximum, and continuously samples the subject for 10.24 seconds while maintaining the static pressure value.

6. A pulse data classification method, comprising:

S4, comparing the classification characteristic value with a corresponding preset threshold value or standard value, and obtaining six classification elements according to a comparison result, wherein the six classification elements comprise a first element based on a static pressure average value corresponding to a pressure value peak value, a second element based on the average number of times of occurrence of the pressure value peak value in each minute, and a third element, fluency, tension and uniformity of an average dynamic pressure value corresponding to a waveform diagram main wave; the specific steps of comparing the classification characteristic value with a corresponding preset threshold value or standard value comprise:

s4-6, when the average times of the pressure value peak values in the time of meeting the corresponding lower threshold value is less than or equal to each minute = the corresponding upper threshold value and the smoothing coefficient is greater than the corresponding standard value, marking as the first type uniformity; when the average times of the pressure value peak value in each minute < the corresponding lower threshold value and the smoothing coefficient > and the corresponding standard value are met at the same time, the second type uniformity is marked; when the average number of the pressure value peak values in each minute is more than the corresponding upper threshold value and the smoothing coefficient is more than the corresponding standard value, the third type uniformity is recorded;

S5, repeating the steps S1-S4, obtaining six classifying elements of a plurality of parts of the tested person, and obtaining the whole pulse data type of the tested person according to the six classifying elements.

7. The pulse data classification method according to claim 6, wherein the specific step of obtaining the overall pulse data type of the subject according to the six classification elements in S5 comprises: