CN112603261A - System and method for predicting abnormal blood lipid value based on gas discharge imaging technology - Google Patents
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Abstract
The invention discloses a system and a method for predicting a blood lipid abnormal value based on a gas discharge imaging technology, and belongs to the technical field of data acquisition and processing. The system of the invention comprises: the GDV instrument acquires glow images of the target ten fingers and transmits the glow images to the energy parameter acquisition module; the meridian energy parameter acquisition module is used for partitioning the glow image aiming at the glow image to acquire a target twelve meridian glow energy parameter; an analysis module that outputs a predicted dyslipidemia value for a target. The prediction system provided by the invention has the characteristics of no wound, simplicity and high practicability, the predicted value of dyslipidemia can be obtained through the pictures of the fingers of the left hand and the right hand, and the coverage rate, the awareness rate, the treatment rate and the control rate of hyperlipidemia screening can be improved by using the prediction system, so that a tested person can pay attention to the health condition of the tested person as early as possible and the progress of a disease course can be blocked in time.
Description
Technical Field
The invention relates to the technical field of data acquisition and processing, in particular to a system and a method for predicting an abnormal blood lipid value based on a gas discharge imaging technology.
Background
In recent years, the incidence of hyperlipidemia has been increasing with changes in lifestyle and dietary structure of people, and it has become an important public health problem threatening human health. Hyperlipidemia (Hyperlipidemia, HLP) is also called hyperlipoproteinemia, which refers to abnormal metabolism of lipoproteins in plasma, and generally refers to an increase in Total Cholesterol (TC) and/or Triglyceride (TG). According to medical observation, cholesterol is deposited on the wall of an artery of a hyperlipidemic person to form an atherosclerotic plaque, the wall of the blood vessel is thickened, the intima of the blood vessel is rough, the wall of the blood vessel is narrow, thrombus is easily formed, and ischemia or infarction of the heart and the brain blood vessels is caused. Cerebrovascular accident, angina pectoris, myocardial infarction, sudden death in severe cases. Hyperlipidemia is an independent risk factor of traditional Chinese medicines for cardiovascular and cerebrovascular events such as coronary heart disease, myocardial infarction, cerebral apoplexy and the like, and is also a risk factor of hypertension and diabetes. According to survey, the total incidence rate of dyslipidemia of adults in China is 40%, the incidence rate of dyslipidemia in partial areas can reach 50%, the detection rate of dyslipidemia in the population for the health examination of middle-aged and elderly people is as high as 56%, the total incidence rate of dyslipidemia of teenagers is 25%, the incidence rate is increased year by year, and people are paid enough attention, and the dyslipidemia screening is carried out timely, and the abnormality is found as soon as possible and intervention is implemented.
The blood fat screening is one of the necessary options in health examination projects, and the blood needs to be fasted 12h before blood sampling, and venous blood is collected on an empty stomach in the early morning for detection. Hyperlipemia patients often have no obvious symptoms and are often found due to physical examination, while many dyslipidemia patients are often not detected due to blood examination or blood examination without the requirement of doctors, or are continuously abnormal, so that cardiovascular and cerebrovascular complications are caused. Therefore, a method for screening blood lipid instead of invasive blood tests is needed to improve the disease detection rate and achieve early detection, early diagnosis, early prevention and early treatment.
Disclosure of Invention
In order to solve the above problems, the present invention provides a blood lipid abnormality value prediction system based on a gas discharge imaging technology, comprising:
the GDV instrument acquires glow images of the target ten fingers and transmits the glow images to the energy parameter acquisition module;
the meridian energy parameter acquisition module is used for partitioning the glow image aiming at the glow image to acquire a target twelve meridian glow energy parameter;
and the analysis module is used for carrying out data analysis on the twelve meridian glow energy parameters and the blood fat parameters to obtain an analysis result, establishing a data model according to the analysis result, inputting the target twelve meridian glow energy parameters into the data model, calculating the twelve meridian glow energy parameters by using a mathematical model, and outputting a predicted blood fat abnormal value of the target.
Optionally, a GDV instrument, comprising:
the high-voltage pulse generator is used for generating a high-voltage pulse signal at the lower side of the transparent discharge platform and generating a high-voltage electric field at the target ten fingers;
a pulsed high-voltage discharge generator that performs high-voltage discharge;
the main controller controls the pulse high-voltage discharge generator to perform high-voltage discharge;
and the image collector is used for collecting glow images of the ten fingers of the target in the high-voltage electric field.
Optionally, the data analysis specifically includes:
and performing normal distribution analysis on the twelve meridian glow energy parameters and the blood fat parameters to determine the correlation between the twelve meridian glow energy parameters and the blood fat parameters.
Optionally, the mathematical model specifically includes:
Y＝-0.531*HT-3.768*LU+2.714*LR-13.173*SP-4.370*KI+4.813*PC+2.199*SI-0.738*LI+2.991*GB-3.251*SJ+16.714*BL-4.437
wherein Y is a dyslipidemia value, HT is a meridian energy value of heart meridian of hand shaoyin, LU is a meridian energy value of lung meridian of hand shaoyin, LR is a meridian energy value of liver meridian of foot jueyin, SP is a meridian energy value of spleen meridian of foot taiyin, KI is a meridian energy value of kidney meridian of foot shaoyin, PC is a meridian energy value of pericardium meridian of hand jueyin, SI is a meridian energy value of small intestine meridian of hand taiyang, LI is a meridian energy value of large intestine meridian of hand yangming, GB is a meridian energy value of gallbladder meridian of foot shaoyang, SJ is a meridian energy value of triple energizer meridian of hand shaoyang, and BL is a meridian energy value of bladder meridian of foot taiyang.
The invention also provides a method for predicting the blood lipid value based on the gas discharge imaging technology, which comprises the following steps:
collecting glow images of the target ten fingers by using a GDV (graphics device video) instrument;
aiming at the glow image, partitioning the glow image to obtain a target twelve meridian glow energy parameter;
and performing data analysis on the twelve meridian glow energy parameters and the blood fat parameters to obtain an analysis result, establishing a data model according to the analysis result, inputting the target twelve meridian glow energy parameters into the data model, performing operation on the twelve meridian glow energy parameters by using a mathematical model, and outputting a predicted blood fat value of the target.
Optionally, a GDV instrument, comprising:
the high-voltage pulse generator is used for generating a high-voltage pulse signal at the lower side of the transparent discharge platform and generating a high-voltage electric field at the target ten fingers;
a pulsed high-voltage discharge generator that performs high-voltage discharge;
the main controller controls the pulse high-voltage discharge generator to perform high-voltage discharge;
and the image collector is used for collecting glow images of the ten fingers of the target in the high-voltage electric field.
Optionally, the data analysis specifically includes:
and performing normal distribution analysis on the twelve meridian glow energy parameters and the blood fat parameters to determine the correlation between the twelve meridian glow energy parameters and the blood fat parameters.
Optionally, the mathematical model specifically includes:
Y＝-0.531*HT-3.768*LU+2.714*LR-13.173*SP-4.370*KI+4.813*PC+2.199*SI-0.738*LI+2.991*GB-3.251*SJ+16.714*BL-4.437
wherein Y is a dyslipidemia value, HT is a meridian energy value of heart meridian of hand shaoyin, LU is a meridian energy value of lung meridian of hand shaoyin, LR is a meridian energy value of liver meridian of foot jueyin, SP is a meridian energy value of spleen meridian of foot taiyin, KI is a meridian energy value of kidney meridian of foot shaoyin, PC is a meridian energy value of pericardium meridian of hand jueyin, SI is a meridian energy value of small intestine meridian of hand taiyang, LI is a meridian energy value of large intestine meridian of hand yangming, GB is a meridian energy value of gallbladder meridian of foot shaoyang, SJ is a meridian energy value of triple energizer meridian of hand shaoyang, and BL is a meridian energy value of bladder meridian of foot taiyang.
The prediction system provided by the invention has the characteristics of no wound, simplicity and high practicability, the predicted value of the blood fat can be obtained through the pictures of the fingers of the left hand and the right hand, and the coverage rate, the awareness rate, the treatment rate and the control rate of the hyperlipidemia screening can be improved by using the prediction system, so that a tested person can pay attention to the self health condition as early as possible and can block the progress of the disease course in time.
Drawings
FIG. 1 is a diagram of a blood lipid abnormality prediction system based on gas discharge imaging technology according to the present invention;
FIG. 2 is a flow chart of a method for predicting dyslipidemia based on gas discharge imaging technology according to the present invention.
Detailed Description
The exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, however, the present invention may be embodied in many different forms and is not limited to the embodiments described herein, which are provided for complete and complete disclosure of the present invention and to fully convey the scope of the present invention to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the accompanying drawings is not intended to be limiting of the invention. In the drawings, the same units/elements are denoted by the same reference numerals.
Unless otherwise defined, terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Further, it will be understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense.
The invention provides a system for predicting a blood lipid abnormal value based on a gas discharge imaging technology, as shown in figure 1, comprising:
the GDV instrument acquires glow images of the target ten fingers and transmits the glow images to the energy parameter acquisition module;
the meridian energy parameter acquisition module is used for partitioning the glow image aiming at the glow image to acquire a target twelve meridian glow energy parameter;
and the analysis module is used for carrying out data analysis on the twelve meridian glow energy parameters and the blood fat parameters to obtain an analysis result, establishing a data model according to the analysis result, inputting the target twelve meridian glow energy parameters into the data model, calculating the twelve meridian glow energy parameters by using a mathematical model, and outputting a predicted blood fat abnormal value of the target.
Wherein, GDV instrument includes:
the high-voltage pulse generator is used for generating a high-voltage pulse signal at the lower side of the transparent discharge platform and generating a high-voltage electric field at the target ten fingers;
a pulsed high-voltage discharge generator that performs high-voltage discharge;
the main controller controls the pulse high-voltage discharge generator to perform high-voltage discharge;
and the image collector is used for collecting glow images of the ten fingers of the target in the high-voltage electric field.
Data analysis, specifically:
and performing normal distribution analysis on the twelve meridian glow energy parameters and the blood fat parameters to determine the correlation between the twelve meridian glow energy parameters and the blood fat parameters.
The mathematical model is specifically as follows:
Y＝-0.531*HT-3.768*LU+2.714*LR-13.173*SP-4.370*KI+4.813*PC+2.199*SI-0.738*LI+2.991*GB-3.251*SJ+16.714*BL-4.437
wherein Y is a dyslipidemia value, HT is a meridian energy value of heart meridian of hand shaoyin, LU is a meridian energy value of lung meridian of hand shaoyin, LR is a meridian energy value of liver meridian of foot jueyin, SP is a meridian energy value of spleen meridian of foot taiyin, KI is a meridian energy value of kidney meridian of foot shaoyin, PC is a meridian energy value of pericardium meridian of hand jueyin, SI is a meridian energy value of small intestine meridian of hand taiyang, LI is a meridian energy value of large intestine meridian of hand yangming, GB is a meridian energy value of gallbladder meridian of foot shaoyang, SJ is a meridian energy value of triple energizer meridian of hand shaoyang, and BL is a meridian energy value of bladder meridian of foot taiyang.
The invention also provides a method for predicting the abnormal blood lipid value based on the gas discharge imaging technology, as shown in fig. 2, comprising the following steps:
collecting glow images of the target ten fingers by using a GDV (graphics device video) instrument;
aiming at the glow image, partitioning the glow image to obtain a target twelve meridian glow energy parameter;
and performing data analysis on the twelve meridian glow energy parameters and the blood fat parameters to obtain an analysis result, establishing a data model according to the analysis result, inputting the target twelve meridian glow energy parameters into the data model, performing operation on the twelve meridian glow energy parameters by using a mathematical model, and outputting a predicted blood fat abnormal value of the target.
A GDV instrument, comprising:
the high-voltage pulse generator is used for generating a high-voltage pulse signal at the lower side of the transparent discharge platform and generating a high-voltage electric field at the target ten fingers;
a pulsed high-voltage discharge generator that performs high-voltage discharge;
the main controller controls the pulse high-voltage discharge generator to perform high-voltage discharge;
and the image collector is used for collecting glow images of the ten fingers of the target in the high-voltage electric field.
Data analysis, specifically:
and performing normal distribution analysis on the twelve meridian glow energy parameters and the blood fat parameters to determine the correlation between the twelve meridian glow energy parameters and the blood fat parameters.
The mathematical model is specifically as follows:
Y＝-0.531*HT-3.768*LU+2.714*LR-13.173*SP-4.370*KI+4.813*PC+2.199*SI-0.738*LI+2.991*GB-3.251*SJ+16.714*BL-4.437
wherein Y is a dyslipidemia value, HT is a meridian energy value of heart meridian of hand shaoyin, LU is a meridian energy value of lung meridian of hand shaoyin, LR is a meridian energy value of liver meridian of foot jueyin, SP is a meridian energy value of spleen meridian of foot taiyin, KI is a meridian energy value of kidney meridian of foot shaoyin, PC is a meridian energy value of pericardium meridian of hand jueyin, SI is a meridian energy value of small intestine meridian of hand taiyang, LI is a meridian energy value of large intestine meridian of hand yangming, GB is a meridian energy value of gallbladder meridian of foot shaoyang, SJ is a meridian energy value of triple energizer meridian of hand shaoyang, and BL is a meridian energy value of bladder meridian of foot taiyang.
The prediction system provided by the invention has the characteristics of no wound, simplicity and high practicability, the predicted value of the blood fat can be obtained through the pictures of the fingers of the left hand and the right hand, and the coverage rate, the awareness rate, the treatment rate and the control rate of the hyperlipidemia screening can be improved by using the prediction system, so that a tested person can pay attention to the self health condition as early as possible and can block the progress of the disease course in time.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein. The scheme in the embodiment of the application can be implemented by adopting various computer languages, such as object-oriented programming language Java and transliterated scripting language JavaScript.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While the preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (8)
1. A system for predicting dyslipidemia based on gas discharge imaging technology, the system comprising:
the GDV instrument acquires glow images of the target ten fingers and transmits the glow images to the energy parameter acquisition module;
the meridian energy parameter acquisition module is used for partitioning the glow image aiming at the glow image to acquire a target twelve meridian glow energy parameter;
and the analysis module is used for carrying out data analysis on the twelve meridian glow energy parameters and the blood fat parameters to obtain an analysis result, establishing a data model according to the analysis result, inputting the target twelve meridian glow energy parameters into the data model, calculating the twelve meridian glow energy parameters by using a mathematical model, and outputting a predicted blood fat abnormal value of the target.
2. The system of claim 1, the GDV instrument, comprising:
the high-voltage pulse generator is used for generating a high-voltage pulse signal at the lower side of the transparent discharge platform and generating a high-voltage electric field at the target ten fingers;
a pulsed high-voltage discharge generator that performs high-voltage discharge;
the main controller controls the pulse high-voltage discharge generator to perform high-voltage discharge;
and the image collector is used for collecting glow images of the ten fingers of the target in the high-voltage electric field.
3. The system of claim 1, wherein the data analysis is specifically:
and performing normal distribution analysis on the twelve meridian glow energy parameters and the blood fat parameters to determine the correlation between the twelve meridian glow energy parameters and the blood fat parameters.
4. The system according to claim 1, the mathematical model being in particular:
Y＝-0.531*HT-3.768*LU+2.714*LR-13.173*SP-4.370*KI+4.813*PC+2.199*SI-0.738*LI+2.991*GB-3.251*SJ+16.714*BL-4.437
wherein Y is a dyslipidemia value, HT is a meridian energy value of heart meridian of hand shaoyin, LU is a meridian energy value of lung meridian of hand shaoyin, LR is a meridian energy value of liver meridian of foot jueyin, SP is a meridian energy value of spleen meridian of foot taiyin, KI is a meridian energy value of kidney meridian of foot shaoyin, PC is a meridian energy value of pericardium meridian of hand jueyin, SI is a meridian energy value of small intestine meridian of hand taiyang, LI is a meridian energy value of large intestine meridian of hand yangming, GB is a meridian energy value of gallbladder meridian of foot shaoyang, SJ is a meridian energy value of triple energizer meridian of hand shaoyang, and BL is a meridian energy value of bladder meridian of foot taiyang.
5. A method for predicting an abnormal blood lipid value based on a gas discharge imaging technology, the method comprising:
collecting glow images of the target ten fingers by using a GDV (graphics device video) instrument;
aiming at the glow image, partitioning the glow image to obtain a target twelve meridian glow energy parameter;
and performing data analysis on the twelve meridian glow energy parameters and the blood fat parameters to obtain an analysis result, establishing a data model according to the analysis result, inputting the target twelve meridian glow energy parameters into the data model, performing operation on the twelve meridian glow energy parameters by using a mathematical model, and outputting a predicted blood fat abnormal value of the target.
6. The method of claim 5, the GDV instrument, comprising:
the high-voltage pulse generator is used for generating a high-voltage pulse signal at the lower side of the transparent discharge platform and generating a high-voltage electric field at the target ten fingers;
a pulsed high-voltage discharge generator that performs high-voltage discharge;
the main controller controls the pulse high-voltage discharge generator to perform high-voltage discharge;
and the image collector is used for collecting glow images of the ten fingers of the target in the high-voltage electric field.
7. The method according to claim 5, wherein the data analysis is in particular:
and performing normal distribution analysis on the twelve meridian glow energy parameters and the blood fat parameters to determine the correlation between the twelve meridian glow energy parameters and the blood fat parameters.
8. The method according to claim 5, the mathematical model being in particular:
Y＝-0.531*HT-3.768*LU+2.714*LR-13.173*SP-4.370*KI+4.813*PC+2.199*SI-0.738*LI+2.991*GB-3.251*SJ+16.714*BL-4.437
wherein Y is a dyslipidemia value, HT is a meridian energy value of heart meridian of hand shaoyin, LU is a meridian energy value of lung meridian of hand shaoyin, LR is a meridian energy value of liver meridian of foot jueyin, SP is a meridian energy value of spleen meridian of foot taiyin, KI is a meridian energy value of kidney meridian of foot shaoyin, PC is a meridian energy value of pericardium meridian of hand jueyin, SI is a meridian energy value of small intestine meridian of hand taiyang, LI is a meridian energy value of large intestine meridian of hand yangming, GB is a meridian energy value of gallbladder meridian of foot shaoyang, SJ is a meridian energy value of triple energizer meridian of hand shaoyang, and BL is a meridian energy value of bladder meridian of foot taiyang.
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