CN114469084B - Blood oxygen monitoring system based on high-precision ADC - Google Patents
Blood oxygen monitoring system based on high-precision ADC Download PDFInfo
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
- A61B5/14542—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue for measuring blood gases
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
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- A61B5/08—Detecting, measuring or recording devices for evaluating the respiratory organs
- A61B5/091—Measuring volume of inspired or expired gases, e.g. to determine lung capacity
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- G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
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- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
Abstract
The invention belongs to the technical field of blood oxygen monitoring, and aims to solve the problems that the existing blood oxygen monitoring system cannot be used for analyzing the disease characteristics of a user by combining related parameters and recommending treatment schemes according to different disease characteristics, in particular to a blood oxygen monitoring system based on a high-precision ADC (analog to digital converter), which comprises a monitoring platform, wherein the monitoring platform is in communication connection with a blood oxygen acquisition module, a saturation analysis module, a storage module, a matching module and a treatment recommendation module; the blood oxygen collecting module collects the blood oxygen saturation degree of the user and sends the collected blood oxygen saturation degree to the saturation analysis module, and the saturation analysis module analyzes the blood oxygen saturation condition of the user through the blood oxygen saturation degree after receiving the blood oxygen saturation degree; the saturation analysis module is used for analyzing the blood oxygen saturation of the user, and the disease analysis model is used for analyzing and judging the characteristics of the user with unqualified blood oxygen saturation, so that the diagnosed user is classified.
Description
Technical Field
The invention belongs to the technical field of blood oxygen monitoring, and particularly relates to a blood oxygen monitoring system based on a high-precision ADC (analog to digital converter).
Background
Blood oxygen saturation (SaO)2) Is oxyhemoglobin (HbO) bound by oxygen in blood2) Is a percentage of the total hemoglobin (Hb) available for binding, i.e. the concentration of blood oxygen in the blood, which is an important physiological parameter of the respiratory cycle. And functional oxygen saturation is HbO2Concentration and HbO2The ratio of + Hb concentration is different from the percentage of oxyhemoglobin.
The existing blood oxygen monitoring system can only detect and analyze the blood oxygen saturation of a user, but cannot analyze the disease characteristics of the user by combining related parameters, and recommend a treatment scheme according to different disease characteristics.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a blood oxygen monitoring system based on a high-precision ADC.
The technical problem to be solved by the invention is as follows:
how to provide a blood oxygen monitoring system which can make targeted treatment plan recommendation according to the disease characteristics of blood oxygen disease users.
The purpose of the invention can be realized by the following technical scheme:
a blood oxygen monitoring system based on a high-precision ADC comprises a monitoring platform, wherein the monitoring platform is in communication connection with a blood oxygen acquisition module, a saturation analysis module, a storage module, a matching module and a treatment recommendation module;
the blood oxygen acquisition module is used for acquiring the blood oxygen saturation of a user through an AC/DC converter and sending the acquired blood oxygen saturation to the saturation analysis module;
after receiving the blood oxygen saturation, the saturation analysis module analyzes the blood oxygen saturation condition of the user through the blood oxygen saturation, and performs blood oxygen curve analysis and characteristic judgment on the user with unqualified blood oxygen concentration through the disease analysis model;
the matching module receives the matching signal and then performs user matching on the diagnosis user with the characteristic of disease;
and the treatment recommendation module carries out hospital recommendation for the diagnosis user after receiving the medical signal.
As a further improvement of the present invention, the specific process of analyzing the blood oxygen saturation condition of the user by the saturation analysis module includes: marking the received blood oxygen saturation as XB, acquiring the minimum value XYmin of the blood oxygen range through a storage module, and comparing the blood oxygen saturation XB with the minimum value XYmin of the blood oxygen range: if XB is less than or equal to XYmin, determining that the blood oxygen concentration of the user is unqualified; and if the XB is greater than XYmin, judging that the blood oxygen concentration of the user is qualified.
As a further improvement of the invention, the disease analysis model carries out blood oxygen curve analysis on users with unqualified blood oxygen concentration: marking users with unqualified blood oxygen concentration as diagnosis users, acquiring historical blood oxygen detection data of the diagnosis users, marking the historical blood oxygen detection times of the diagnosis users as i, i =1, 2, …, n, marking the value of the blood oxygen saturation detected each time as XBI, marking the maximum value in the blood oxygen saturation as a blood oxygen peak value XF, and comparing the blood oxygen peak value CF with the minimum value XYmin of the blood oxygen range: if the blood oxygen peak value CF is less than or equal to the minimum value XYmin of the blood oxygen range, the user is judged to be a congenital user, and if the blood oxygen peak value CF is greater than the minimum value XYmin of the blood oxygen range, the user is judged to be a non-congenital user; performing feature analysis for non-congenital users: establishing a saturation set { XB1, XB2, … and XBn } of the blood oxygen saturation level XB detected by the user history, carrying out variance calculation on the saturation set, marking the obtained numerical value as a deviation coefficient PL, obtaining deviation threshold values PLmin and PLmax through a storage module, and comparing the deviation coefficient PL with the deviation threshold values PLmin and PLmax:
if PL is less than or equal to PLmin, judging that the characteristic of the diagnosis user is irregular;
if PLmin < PL < PLmax, judging that the characteristic of the diagnosis user is a disease state;
if PL is greater than or equal to PLmax, the characteristic of the diagnosis user is judged to be disease.
As a further improvement of the invention, aiming at the diagnosis user with irregular characteristics, regular signals are sent to the mobile phone terminal of the diagnosis user through the saturation analysis module;
aiming at a diagnosis user with the characteristic of disease symptoms, sending a matching signal to a matching module through a saturation analysis module;
and aiming at the diagnosis user characterized by the disease, sending a medical seeking signal to the treatment recommending module through the saturation analyzing module.
As a further improvement of the invention, the process of user matching comprises: acquiring heart rate data XL, oxygen partial pressure data YF and vital capacity data FH of a diagnosis user, and analyzing the heart rate data XL, the oxygen partial pressure data YF and the vital capacity data FH of the diagnosis user to obtain a comprehensive coefficient ZH of the diagnosis user;
carrying out scaling conversion on the comprehensive coefficient ZH to obtain a maximum value ZHmax and a minimum value ZHmin of a comprehensive range, wherein ZHmax = t1 xZH, t1 is a proportional coefficient, t1 is more than or equal to 1.15 and less than or equal to 1.25, ZHmin = t2 xZH, t2 is a proportional coefficient, and t2 is more than or equal to 0.75 and less than or equal to 0.85; all users with the comprehensive coefficients within the comprehensive range in the storage module are marked as primary screening users, m primary screening users with the blood oxygen saturation closest to the blood oxygen saturation of the diagnosis users are marked as secondary screening users, the user with the highest recovery efficiency in the secondary screening users is marked as a matching user, and the treatment scheme of the matching user is matched with the diagnosis user.
As a further improvement of the present invention, the process of diagnosing heart rate data acquisition of a user comprises: acquiring the maximum value and the minimum value of a heart rate range through a storage module, summing the maximum value and the minimum value of the heart rate range, taking an average value to obtain a heart rate standard value, subtracting the heart rate standard value from a numerical value detected by diagnosing the heart rate of a user, and taking an absolute value of the heart rate standard value to obtain heart rate data XL;
the oxygen partial pressure data acquisition process for diagnosing the user comprises the following steps: acquiring a minimum threshold value of oxygen partial pressure through a storage module, and subtracting the minimum threshold value of the oxygen partial pressure from a value detected by diagnosing the oxygen partial pressure of a user to obtain oxygen partial pressure data YF;
the process of acquiring vital capacity data for a diagnostic user comprises: and acquiring the minimum threshold of the vital capacity through a storage module, and subtracting the minimum threshold of the vital capacity from the value detected by the vital capacity of the diagnosis user to obtain vital capacity data FH.
As a further improvement of the invention, the process of visiting hospital recommendation comprises the following steps: marking the geographic position of a diagnostic user as a central position, taking the central position as a circle center, taking r1 as a radius to draw a circle, taking r1 as a preset radius value, taking the unit as kilometers, marking the obtained circular area as a screening area, marking all hospitals in the screening area as primary selection objects, marking the linear distance between the primary selection objects and the central position as ZJ, marking the number of registrants of the primary selection objects as YS, and obtaining a recommendation coefficient TJ of the primary selection objects by a formula TJ = (beta 1 × YS)/(beta 2 × ZJ), wherein beta 1 and beta 2 are both proportionality coefficients, and beta 1 is more than beta 2 and more than 1; marking the primary selection object with the maximum recommendation coefficient value as a recommendation object, and sending hospital information of the recommendation object to a mobile phone terminal of a user through a treatment recommendation module; the hospital information of the recommended subject includes: the geographical location of the hospital, the contact phone of the hospital, and the establishment time of the hospital.
As a further improvement of the invention, the working method of the blood oxygen monitoring system based on the high-precision ADC comprises the following steps:
the method comprises the following steps: the blood oxygen acquisition module acquires the blood oxygen saturation of a user through an AC/DC converter and sends the acquired blood oxygen saturation to the saturation analysis module;
step two: after the saturation analysis module receives the blood oxygen saturation degree, the blood oxygen saturation condition of the user is analyzed through the blood oxygen saturation degree, and whether the blood oxygen concentration of the user is qualified or not is judged;
step three: analyzing a blood oxygen curve of the user with unqualified blood oxygen concentration, and judging the characteristics of the diagnosed user according to the blood oxygen curve analysis result;
step four: the matching module performs user matching on the diagnosis user with the characteristic of disease, calculates a comprehensive coefficient through heart rate data XL, oxygen partial pressure data YF and vital capacity data FH, screens the numerical value of the comprehensive coefficient and the blood oxygen saturation to obtain a matching user, and matches the treatment scheme of the matching user with the diagnosis user;
step five: the treatment recommendation module is used for recommending the hospital for the diagnosis of the diagnosis user, obtaining a recommendation coefficient through the straight-line distance and the number of registered doctors, screening the recommendation coefficient to obtain a recommendation object, and sending hospital information of the recommendation object to a mobile phone terminal of the user through the monitoring platform.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the invention, the saturation analysis module is used for analyzing the blood oxygen saturation of the user, and the characteristics of the user with unqualified blood oxygen saturation are analyzed and judged by adopting the disease analysis model, so that the diagnosis user is classified, and corresponding treatment schemes are adopted for recommending different types of disease users, so that the diagnosis user is subjected to targeted treatment, the treatment period of the user is shortened, and the treatment efficiency is accelerated;
2. according to the invention, the matching module is used for carrying out user matching on the diagnosis users with the characteristics of diseases, and the users with the characteristics closest to the diagnosis users are screened out from the database in a parameter comparison mode, so that the users with the best treatment effect are searched for in the users, and the treatment scheme can be recommended to the diagnosis users;
3. according to the invention, hospitals around the diagnosis user can be screened through the treatment recommendation module, the most suitable hospital is obtained through screening the numerical value of the recommendation coefficient, and the diagnosis user can directly go to the corresponding hospital to see a doctor after receiving the information of the recommended hospital, so that the time for selecting and screening the hospitals is saved, and the treatment efficiency is accelerated.
Drawings
In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
FIG. 1 is a block diagram of an overall system according to a first embodiment of the present invention;
FIG. 2 is a flowchart of a method according to a second embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood 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.
Referring to fig. 1, a blood oxygen monitoring system based on a high-precision ADC includes a monitoring platform, which is communicatively connected with a blood oxygen collecting module, a saturation analyzing module, a storage module, a matching module, and a treatment recommending module;
the blood oxygen collecting module is used for collecting the blood oxygen saturation of a user through the AC/DC converter and sending the collected blood oxygen saturation to the saturation analyzing module, and it should be noted that the AC/DC converter is a device for converting alternating current into direct current, the power flow direction of the device can be bidirectional, the power flow is rectified from a power supply to a load, and the power flow is returned from the load to the power supply and is called active inversion. After the saturation analysis module receives the blood oxygen saturation, the blood oxygen saturation condition of the user is analyzed through the blood oxygen saturation: marking the received blood oxygen saturation as XB, acquiring the minimum value XYmin of the blood oxygen range through a storage module, and comparing the blood oxygen saturation XB with the minimum value XYmin of the blood oxygen range: if XB is less than or equal to XYmin, determining that the blood oxygen concentration of the user is unqualified; if XB is larger than XYmin, judging that the blood oxygen concentration of the user is qualified;
and (3) analyzing the blood oxygen curve of the user with unqualified blood oxygen concentration through a disease analysis model: marking users with unqualified blood oxygen concentration as diagnosis users, acquiring historical blood oxygen detection data of the diagnosis users, calling the historical blood sample detection data through a storage module, marking the historical blood oxygen detection times of the diagnosis users as i, i =1, 2, …, n, marking the value of the blood oxygen saturation degree detected each time as XBI, marking the maximum value in the blood oxygen saturation degree as a blood oxygen peak value XF, and comparing the blood oxygen peak value CF with the minimum value XYmin of the blood oxygen range: if the blood oxygen peak value CF is less than or equal to the minimum value XYmin of the blood oxygen range, judging that the user is diagnosed as a congenital user, wherein the blood oxygen concentration insufficiency of the congenital user is caused by congenital diseases, and the user can be regulated through diet and exercise in daily life; if the blood oxygen peak value CF is larger than the minimum value XYmin of the blood oxygen range, judging that the diagnosed user is a non-congenital user, wherein the blood oxygen concentration insufficiency of the non-congenital user is caused by acquired diseases; performing feature analysis for non-congenital users: establishing a saturation set { XB1, XB2, … and XBn } of the blood oxygen saturation level XB detected by the user history, carrying out variance calculation on the saturation set, marking the obtained numerical value as a deviation coefficient PL, obtaining deviation threshold values PLmin and PLmax through a storage module, and comparing the deviation coefficient PL with the deviation threshold values PLmin and PLmax: if PL is less than or equal to PLmin, judging that the characteristic of the diagnosis user is irregular; if PLmin < PL < PLmax, judging that the characteristic of the diagnosis user is a disease state; if PL is larger than or equal to PLmax, judging that the diagnosis user is characterized as a disease, and judging that the diagnosis user is high in disease severity degree and needs to take medical treatment immediately.
Aiming at a diagnosis user with irregular characteristics, a regular signal is sent to a mobile phone terminal of the diagnosis user through a saturation analysis module, and the diagnosis user can adjust the diagnosis user in daily life through regular diet, movement and other modes;
aiming at the diagnosis user with the characteristic of disease, a saturation analysis module sends a matching signal to a matching module, and the matching user is screened for the diagnosis user, so that an optimal treatment scheme is obtained;
aiming at a diagnosis user with disease, a medical seeking signal is sent to a treatment recommending module through a saturation analyzing module, and aiming at a user with higher disease severity, the user is treated in a mode of seeking medical attention immediately.
The matching module receives the matching signal and then carries out user matching on the diagnosis user with the characteristic of disease, and the user matching process comprises the following steps: acquiring heart rate data XL, oxygen partial pressure data YF and vital capacity data FH of a diagnosis user,
the process of diagnosing heart rate data acquisition of a user comprises: acquiring the maximum value and the minimum value of a heart rate range through a storage module, summing the maximum value and the minimum value of the heart rate range to obtain an average value to obtain a heart rate standard value, subtracting the heart rate standard value from a numerical value detected by diagnosing the heart rate of a user, and taking an absolute value of the heart rate standard value to obtain heart rate data XL;
the oxygen partial pressure data acquisition process for diagnosing the user comprises the following steps: acquiring a minimum threshold value of oxygen partial pressure through a storage module, and subtracting the minimum threshold value of the oxygen partial pressure from a value detected by diagnosing the oxygen partial pressure of a user to obtain oxygen partial pressure data YF;
the process of acquiring vital capacity data for a diagnostic user comprises: acquiring a minimum threshold value of the vital capacity through a storage module, and subtracting the minimum threshold value of the vital capacity from a numerical value detected by diagnosing the vital capacity of the user to obtain vital capacity data FH;
by the formula
The comprehensive coefficient ZH of the diagnosis user is obtained,wherein alpha 1, alpha 2 and alpha 3 are all proportionality coefficients, and alpha 1 is more than alpha 2 and more than alpha 3 is more than 1; carrying out scaling on the comprehensive coefficient ZH to obtain the maximum value ZHmax and the minimum value ZHmin of the comprehensive range, wherein ZHmax = t1 xZH, t1 is a proportional coefficient, t1 which is more than or equal to 1.15 and less than or equal to 1.25, ZHmin = t2 xZH, t2 is a proportional coefficient, t2 which is more than or equal to 0.75 and less than or equal to 0.85; all users with the comprehensive coefficients within the comprehensive range in the storage module are marked as primary screening users, m primary screening users with the blood oxygen saturation degree closest to the blood oxygen saturation degree of the diagnosis user are marked as secondary screening users, the user with the highest recovery efficiency in the secondary screening users is marked as a matching user, the matching user is the user with the closest disease condition and the best treatment effect to the diagnosis user, and the treatment scheme of the matching user is matched with the diagnosis user.
The treatment recommendation module carries out hospital recommendation for the diagnosis user after receiving the medical signals, and the hospital recommendation process comprises the following steps: marking the geographic position of a diagnostic user as a central position, taking the central position as a circle center, taking r1 as a radius to draw a circle, taking r1 as a preset radius value and taking the unit as kilometers, marking the obtained circular area as a screening area, marking all hospitals in the screening area as a primary selection object, marking the linear distance between the primary selection object and the central position as ZJ, marking the number of registered physicians of the primary selection object as YS, and obtaining a recommendation coefficient TJ of the primary selection object by a formula TJ = (beta 1 xYS)/(beta 2 xZJ), wherein beta 1 and beta 2 are both proportional coefficients, and beta 1 is more than beta 2 and is more than 1; marking the initially selected object with the maximum recommendation coefficient value as a recommended object, wherein the recommended object is a hospital most suitable for the diagnosis of the diagnosis object at present, and sending hospital information of the recommended object to a mobile phone terminal of a user through a monitoring platform by a treatment recommendation module; the hospital information of the recommended subject includes: the geographical location of the hospital, the contact phone of the hospital, and the establishment time of the hospital.
Example two
Referring to fig. 2, a blood oxygen monitoring method based on a high-precision ADC includes the following steps:
the method comprises the following steps: the blood oxygen acquisition module acquires the blood oxygen saturation of a user through an AC/DC converter and sends the acquired blood oxygen saturation to the saturation analysis module;
step two: after the saturation analysis module receives the blood oxygen saturation degree, the blood oxygen saturation condition of the user is analyzed through the blood oxygen saturation degree, and whether the blood oxygen concentration of the user is qualified or not is judged;
step three: analyzing a blood oxygen curve of the user with unqualified blood oxygen concentration, and judging the characteristics of the diagnosed user according to the blood oxygen curve analysis result;
step four: the matching module performs user matching on the diagnosis user with the characteristic of disease, calculates a comprehensive coefficient through heart rate data XL, oxygen partial pressure data YF and vital capacity data FH, screens the numerical value of the comprehensive coefficient and the blood oxygen saturation to obtain a matching user, and matches the treatment scheme of the matching user with the diagnosis user;
step five: the treatment recommendation module is used for recommending the hospital for the diagnosis of the diagnosis user, obtaining a recommendation coefficient through the straight-line distance and the number of registered doctors, screening the recommendation coefficient to obtain a recommendation object, and sending hospital information of the recommendation object to a mobile phone terminal of the user through the monitoring platform.
A blood oxygen monitoring system based on a high-precision ADC (analog to digital converter) is characterized in that when the blood oxygen monitoring system works, a blood oxygen acquisition module acquires the blood oxygen saturation of a user through an AC/DC (alternating current/direct current) converter and sends the acquired blood oxygen saturation to a saturation analysis module; after the saturation analysis module receives the blood oxygen saturation degree, the blood oxygen saturation condition of the user is analyzed through the blood oxygen saturation degree, and whether the blood oxygen concentration of the user is qualified or not is judged; the blood oxygen curve analysis is carried out on the users with unqualified blood oxygen concentration, the characteristics of the diagnosis users are judged through the blood oxygen curve analysis result, the matching module carries out user matching on the diagnosis users with the characteristics of diseases, and the treatment recommendation module carries out hospital recommendation for the diagnosis users.
The formulas are all calculated by removing dimensions and taking numerical values, the formula is a formula which is obtained by acquiring a large amount of data and performing software simulation to obtain the latest real situation, and the preset parameters in the formula are set by the technical personnel in the field according to the actual situation;
such as the formula:
；
collecting multiple groups of sample data and setting a corresponding rating coefficient for each group of sample data by a person skilled in the art; substituting the set comprehensive coefficient and the acquired sample data into formulas, forming a ternary linear equation set by any three formulas, screening the calculated coefficients and taking the mean value to obtain values of alpha 1, alpha 2 and alpha 3 which are 3.25, 2.58 and 2.21 respectively;
the size of the coefficient is a specific value obtained by quantizing each parameter, so that the subsequent comparison is facilitated, and regarding the size of the coefficient, the proportional relation between the parameter and the quantized value is not affected.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (4)
1. A blood oxygen monitoring system based on a high-precision ADC comprises a monitoring platform, and is characterized in that the monitoring platform is in communication connection with a blood oxygen acquisition module, a saturation analysis module, a storage module, a matching module and a treatment recommendation module;
the blood oxygen acquisition module is used for acquiring the blood oxygen saturation of a user through an AC/DC converter and sending the acquired blood oxygen saturation to the saturation analysis module;
after the saturation analysis module receives the blood oxygen saturation degree, the blood oxygen saturation condition of the user is analyzed through the blood oxygen saturation degree, and the blood oxygen curve analysis and the characteristic judgment are carried out on the user with unqualified blood oxygen concentration through the disease analysis model;
the matching module receives the matching signal and then performs user matching on the diagnosis user with the characteristics of the disease: acquiring heart rate data XL, oxygen partial pressure data YF and vital capacity data FH of a diagnosis user, and analyzing the heart rate data XL, the oxygen partial pressure data YF and the vital capacity data FH of the diagnosis user to obtain a comprehensive coefficient ZH of the diagnosis user;
carrying out scaling conversion on the comprehensive coefficient ZH to obtain a maximum value ZHmax and a minimum value ZHmin of a comprehensive range, wherein ZHmax = t1 xZH, t1 is a proportional coefficient, t1 is more than or equal to 1.15 and less than or equal to 1.25, ZHmin = t2 xZH, t2 is a proportional coefficient, and t2 is more than or equal to 0.75 and less than or equal to 0.85; marking all users of which the comprehensive coefficients are within the comprehensive range in the storage module as primary screening users, marking m primary screening users of which the blood oxygen saturation is closest to the blood oxygen saturation of the diagnosis user as secondary screening users, marking the user with the highest recovery efficiency in the secondary screening users as a matching user, and matching the treatment scheme of the matching user with the diagnosis user;
the treatment recommending module receives the hospitalizing signal and then carries out hospital recommendation for the diagnosis user with the disease characteristic: marking the geographic position of a diagnostic user as a central position, taking the central position as a circle center, taking r1 as a radius to draw a circle, taking r1 as a preset radius value, taking the unit as kilometers, marking the obtained circular area as a screening area, marking all hospitals in the screening area as primary selection objects, marking the linear distance between the primary selection objects and the central position as ZJ, marking the number of registrants of the primary selection objects as YS, and obtaining a recommendation coefficient TJ of the primary selection objects by a formula TJ = (beta 1 × YS)/(beta 2 × ZJ), wherein beta 1 and beta 2 are both proportionality coefficients, and beta 1 is more than beta 2 and more than 1; marking the primary selection object with the maximum recommendation coefficient value as a recommendation object, and sending hospital information of the recommendation object to a mobile phone terminal of a user through a treatment recommendation module; the hospital information of the recommended subject includes: the geographical location of the hospital, the contact telephone of the hospital and the establishment time of the hospital;
the specific process of analyzing the blood oxygen saturation condition of the user by the saturation analysis module comprises the following steps: marking the received blood oxygen saturation as XB, acquiring the minimum value XYmin of the blood oxygen range through a storage module, and comparing the blood oxygen saturation XB with the minimum value XYmin of the blood oxygen range: if XB is less than or equal to XYmin, determining that the blood oxygen concentration of the user is unqualified; if XB is larger than XYmin, judging that the blood oxygen concentration of the user is qualified;
the disease analysis model carries out blood oxygen curve analysis on users with unqualified blood oxygen concentration: marking users with unqualified blood oxygen concentration as diagnosis users, acquiring historical blood oxygen detection data of the diagnosis users, marking the historical blood oxygen detection times of the diagnosis users as i, i =1, 2, …, n, marking the value of the blood oxygen saturation degree detected each time as XBI, marking the maximum value in the blood oxygen saturation degree XBI as a blood oxygen peak value CF, and comparing the blood oxygen peak value CF with the minimum value XYmin of the blood oxygen range: if the blood oxygen peak value CF is less than or equal to the minimum value XYmin of the blood oxygen range, the user is judged to be a congenital user, and if the blood oxygen peak value CF is greater than the minimum value XYmin of the blood oxygen range, the user is judged to be a non-congenital user; performing feature analysis for non-congenital users: establishing a saturation set { XB1, XB2, … and XBn } of the blood oxygen saturation level XB detected by the user history, carrying out variance calculation on the saturation set, marking the obtained numerical value as a deviation coefficient PL, obtaining deviation threshold values PLmin and PLmax through a storage module, and comparing the deviation coefficient PL with the deviation threshold values PLmin and PLmax:
if PL is less than or equal to PLmin, judging that the characteristic of the diagnosis user is irregular;
if PLmin < PL < PLmax, judging that the characteristic of the diagnosis user is a disease state;
if PL is greater than or equal to PLmax, the characteristic of the diagnosis user is judged to be disease.
2. The blood oxygen monitoring system based on the high-precision ADC of claim 1, wherein for a diagnosis user with irregular characteristics, regular signals are sent to a mobile phone terminal of the diagnosis user through a saturation analysis module;
aiming at a diagnosis user with the characteristic of disease symptoms, sending a matching signal to a matching module through a saturation analysis module;
and aiming at the diagnosis user characterized by the disease, sending a medical seeking signal to the treatment recommending module through the saturation analyzing module.
3. The blood oxygen monitoring system based on high-precision ADC of claim 1, wherein the process of diagnosing the heart rate data acquisition of the user comprises: acquiring the maximum value and the minimum value of a heart rate range through a storage module, summing the maximum value and the minimum value of the heart rate range, taking an average value to obtain a heart rate standard value, subtracting the heart rate standard value from a numerical value detected by diagnosing the heart rate of a user, and taking an absolute value of the heart rate standard value to obtain heart rate data XL;
the oxygen partial pressure data acquisition process for diagnosing the user comprises the following steps: acquiring a minimum threshold value of oxygen partial pressure through a storage module, and subtracting the minimum threshold value of the oxygen partial pressure from a value detected by diagnosing the oxygen partial pressure of a user to obtain oxygen partial pressure data YF;
the process of acquiring vital capacity data for a diagnostic user comprises: and acquiring the minimum threshold of the vital capacity through a storage module, and subtracting the minimum threshold of the vital capacity from the value detected by the vital capacity of the diagnosis user to obtain vital capacity data FH.
4. The blood oxygen monitoring system based on high-precision ADC according to any one of claims 1-3, wherein the working method of the blood oxygen monitoring system based on high-precision ADC comprises the following steps:
the method comprises the following steps: the blood oxygen collecting module collects the blood oxygen saturation of a user through the AC/DC converter and sends the collected blood oxygen saturation to the saturation analysis module;
step two: after the saturation analysis module receives the blood oxygen saturation degree, the blood oxygen saturation condition of the user is analyzed through the blood oxygen saturation degree, and whether the blood oxygen concentration of the user is qualified or not is judged;
step three: analyzing a blood oxygen curve of a user with unqualified blood oxygen concentration, and judging the characteristics of a diagnosed user according to the blood oxygen curve analysis result;
step four: the matching module performs user matching on the diagnosis user with the characteristic of disease, calculates a comprehensive coefficient through heart rate data XL, oxygen partial pressure data YF and vital capacity data FH, screens the numerical value of the comprehensive coefficient and the blood oxygen saturation to obtain a matching user, and matches the treatment scheme of the matching user with the diagnosis user;
step five: the treatment recommending module carries out hospital recommendation for the diagnosis users with the characteristics of diseases, obtains a recommending coefficient through the straight line distance and the number of registered doctors, obtains a recommended object through screening of the numerical value of the recommending coefficient, and sends hospital information of the recommended object to a mobile phone terminal of the user through the monitoring platform.
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