CN116602668B - Full-automatic intelligent blood sugar detection system - Google Patents
Full-automatic intelligent blood sugar detection system Download PDFInfo
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- A61B5/14532—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 glucose, e.g. by tissue impedance measurement
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Abstract
The application relates to the technical field of blood glucose monitoring, in particular to a full-automatic intelligent blood glucose detection system, which comprises: the blood sugar detector is used for collecting personal information of the tested object and noninvasively detecting blood sugar information of the tested object; the management terminal is used for managing user information, including the personal information and the blood glucose information; the mobile client is used for providing information inquiry service for the user; and the database is used for storing the personal information, the blood sugar information and treatment schemes of various blood sugar symptoms of the tested object. The system provided by the application is suitable for different scenes, can meet the blood sugar detection requirements of diabetics and healthy people, has high degree of automation and intelligence, and can effectively improve the primary prevention level of diabetes.
Description
Technical Field
The application relates to the technical field of blood glucose monitoring, in particular to a full-automatic intelligent blood glucose detection system.
Background
In recent years, with the rapid development of economy, rapid change of social environment and continuous upgrade of life and consumption modes of people, people are seriously bothered by diabetes and complications thereof caused by hyperglycemia, and the proportion of illness and illness state caused by worsening and death of diabetes is increased year by year. In the past, people concerned about diabetes, especially type 2 diabetes, are mostly concentrated on middle-aged and elderly people, but from statistics results of data and observation of a large number of clinical patients, people find that diabetes is not exclusive to middle-aged and elderly people, and the onset age of diabetes has a tendency to be younger. According to this situation, a broad, convenient and safe blood glucose test is very important.
At present, the blood glucose detection instrument comprises a traditional blood glucose meter, an insulin pump, a transient feeling and some intelligent wearable devices, the above instruments have respective advantages, but still have points which cannot be covered by the above instruments, and most of the above instruments are applied to diabetics, so that the blood glucose detection and primary prevention effects on non-diabetics are limited. If a blood glucose detecting instrument is provided in a family unit, it is not practical to provide a blood glucose detecting instrument in each family, and therefore, a more practical blood glucose detecting system suitable for various scenes is urgently needed.
Disclosure of Invention
Aiming at the defects in the prior art, the application provides a full-automatic intelligent blood sugar detection system.
To achieve the above object, the present application provides a fully automatic intelligent blood glucose detection system, the system comprising: the blood sugar detector is used for collecting personal information of the tested object and noninvasively detecting blood sugar information of the tested object; the management terminal is used for managing user information, including the personal information and the blood glucose information; the mobile client is used for providing information inquiry service for the user; and the database is used for storing the personal information, the blood sugar information and treatment schemes of various blood sugar symptoms of the tested object. The system provided by the application is suitable for different scenes, can meet the blood sugar detection requirements of diabetics and healthy people, has high degree of automation and intelligence, and can effectively improve the primary prevention level of diabetes.
Optionally, the blood glucose detector includes:
the information control device is used for logging in by a user, collecting the personal information, outputting prompt information and blood glucose information;
the blood sugar collecting device is connected with the information control device and is used for collecting blood sugar information of a tested object.
Further, the tested object can select whether to log in according to own requirements, the tested object which logs in for the first time can set up own account numbers, personal information of the tested object can be input, blood glucose monitoring can be carried out no matter whether the tested object logs in or not, and meanwhile, the information control device can also select the storage mode of information in the database according to whether the tested object logs in or not, so that requirements of blood glucose monitoring and information query of different tested objects can be met, convenience is provided for management of related information of the tested object, and long-term and systematic detection of blood glucose information of a vast crowd is facilitated.
Optionally, the blood glucose collecting device includes:
the finger fixing module is provided with a spring clamp and is used for placing and fixing the finger of the measured object;
the light detection module is connected with the finger fixing module, is arranged on one side, close to the finger, of the finger fixing module and is used for emitting near infrared rays and receiving reflected near infrared rays after the near infrared rays pass through the finger;
the signal processing module is connected with the light detection module and is used for acquiring luminosity data according to the reflected near infrared rays;
the influence factor detection module is connected with the finger fixing module and is used for measuring influence factors influencing blood sugar concentration;
the blood sugar concentration detection module is connected with the signal processing module and the influence factor detection module, and the blood sugar concentration detection module is used for detecting the blood sugar concentration of the tested object by utilizing the luminosity data and the influence factor.
Optionally, the light detection module includes a light emitting sub-module and a light receiving sub-module, the light emitting sub-module and the light receiving sub-module are arranged on the same side of the finger, and the light detection module performs the following steps:
utilizing the light emitting sub-module for emitting the near infrared light;
and the light receiving sub-module is used for receiving the reflected near infrared light.
Furthermore, the diffuse reflection type near infrared light collection mode is adopted, so that the condition that near infrared light is difficult to penetrate skin tissue when human tissue is thicker is avoided, and the accuracy of blood glucose detection is improved.
Optionally, the signal processing module performs the following steps:
converting the reflected near infrared light into an electrical signal;
amplifying the electric signal to obtain an amplified signal;
performing analog-to-digital conversion on the amplified signal to obtain a digital signal;
extracting infrared spectrum information according to the digital signal;
and obtaining the luminosity data by utilizing the infrared spectrum information.
Optionally, the blood glucose collecting device further includes:
the pathology judgment module is connected with the blood glucose concentration detection module and is used for judging and outputting the blood glucose pathology;
the treatment scheme matching module is connected with the pathology judging module, and the treatment scheme matching device is used for judging and outputting the treatment scheme.
Optionally, the pathology determining module includes a computer storage medium for determining a blood sugar pathology, where a first type of computer program is stored in the computer storage medium for determining a blood sugar pathology, and when the first type of computer program is running, the following steps are executed:
judging the blood sugar condition of the tested object according to the blood sugar concentration;
judging whether to output the blood sugar symptoms according to the prompt information.
Further, the blood sugar symptoms comprise a hyperglycemia state, a hypoglycemia state and a normal blood sugar state, if the blood sugar symptom is not the normal blood sugar state, the information control device can send out prompt information whether to output the blood sugar symptoms, and the blood sugar symptoms are output after the blood sugar symptoms are determined by the tested object, so that the privacy of the tested object can be protected in public places.
Optionally, the treatment plan matching module includes a treatment plan matching computer storage medium, in which a second computer program is stored, and the second computer program executes the following steps when running:
matching an appropriate treatment regimen based on the personal information and the glycemic condition;
judging whether to output the treatment scheme and the output path of the treatment scheme according to the prompt information.
Furthermore, the treatment scheme matching module matches an appropriate treatment scheme for the tested object in the database according to the personal information and the blood sugar symptom, and then the information control device gives prompt information whether to output the treatment scheme or not, and outputs the treatment scheme after the tested object is determined, so that the privacy of the tested object is protected in public places and a preliminary treatment method is provided for the tested object.
Optionally, the blood glucose concentration detection module includes a blood glucose concentration detection model, and the blood glucose concentration detection model is constructed by the following steps:
selecting a plurality of personnel to be tested and all reference influence factors which possibly influence the blood sugar concentration measurement value;
setting a time sequence of blood glucose monitoring, measuring the blood glucose concentration of the person to be tested by using an invasive method according to the time sequence to obtain invasive blood glucose concentration data, and measuring the reference influence factors to obtain measured values;
comparing the invasive blood glucose concentration data with the measured values time by time, calculating the change similarity of the invasive blood glucose concentration data and each reference influence factor, setting a similarity threshold to exclude redundant reference influence factors to obtain the influence factors, wherein the change similarity satisfies the following relation:
wherein L is the variation similarity,for the measurement value of the influencing factor at time j+1, -/->For the measurement of the influencing factor at moment j, < >>As a positive rate function of the influence factor, and (2)>For the invasive blood glucose concentration data at time j+1,/th time>For the invasive blood glucose concentration data at time j,>as a positive rate of change function of said invasive blood glucose concentration data +.>For the measurement of the influencing factor at time i+1,/for the measurement of the influencing factor at time i+1>For the measurement of the influencing factor at time i, < >>As a negative rate of change function of the influencing factor, and (2)>For the invasive blood glucose concentration data at time i+1,/a blood glucose concentration data of->For the invasive blood glucose concentration data at time j,>a negative rate of change function for the invasive blood glucose concentration data;
measuring photometric data of the person to be tested by using the light detection module and the signal processing module according to the time sequence to obtain test photometric data;
and establishing the blood glucose concentration detection model by using the test luminosity data, the invasive blood glucose concentration data and the influence factors.
Furthermore, the artificial neural network is adopted to establish the blood glucose concentration detection model, so that the nonlinear relation between the influence factors and the luminosity data and the blood glucose concentration is solved, the functional relation between each variable and the blood glucose concentration is fitted better, and the accuracy and the reliability of blood glucose concentration detection are improved.
Optionally, the mobile client includes:
a blood glucose query client including, but not limited to, blood glucose query software, a blood glucose query website, and a blood glucose query applet;
blood glucose query devices including, but not limited to, cell phones and computers.
Furthermore, a two-dimensional code and an information query website address can be attached to the blood glucose detector, the tested object can download the blood glucose query software through code scanning, or log in the blood glucose query website and the blood glucose query applet, and the tested object can log in the blood glucose query website through the information query website address, so that remote information query service is provided for a user, time is saved for the tested object when the tested object is in time shortage, convenience of the system is improved, and the application scene of the system is increased.
In conclusion, the system provided by the application has high automation and intelligent degree, is suitable for various scenes, such as hospitals, community health service centers, enterprises and markets, achieves primary prevention, and is convenient for statistics of various data information; the tested object can detect blood sugar at any time by self-help, so that the diagnosis rate is improved, the workload and the working pressure of medical staff are greatly relieved, the time of the tested object is saved, and the anxiety emotion of the tested object waiting in line is relieved. In addition, the system is also beneficial to promoting people to develop healthy living habits.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a diagram of a fully automatic intelligent blood glucose testing system in accordance with an embodiment of the present application;
FIG. 2 is a schematic diagram of a blood glucose detector according to an embodiment of the present application;
fig. 3 is a schematic diagram of a blood glucose collecting device according to an embodiment of the present application.
Detailed Description
Specific embodiments of the application will be described in detail below, it being noted that the embodiments described herein are for illustration only and are not intended to limit the application. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. However, it will be apparent to one of ordinary skill in the art that: no such specific details are necessary to practice the application. In other instances, well-known circuits, software, or methods have not been described in detail in order not to obscure the application.
Throughout the specification, references to "one embodiment," "an embodiment," "one example," or "an example" mean: a particular feature, structure, or characteristic described in connection with the embodiment or example is included within at least one embodiment of the application. Thus, the appearances of the phrases "in one embodiment," "in an embodiment," "one example," or "an example" in various places throughout this specification are not necessarily all referring to the same embodiment or example. Furthermore, the particular features, structures, or characteristics may be combined in any suitable combination and/or sub-combination in one or more embodiments or examples. Moreover, those of ordinary skill in the art will appreciate that the illustrations provided herein are for illustrative purposes and that the illustrations are not necessarily drawn to scale.
It should be noted in advance that in an alternative embodiment, the same symbols or alphabet meaning and number are the same as those present in all formulas, except where separate descriptions are made.
In an alternative embodiment, referring to fig. 1, the present application provides a fully automatic intelligent blood glucose detection system, the system includes a blood glucose detector A1, the blood glucose detector A1 is used for collecting personal information of a tested object and noninvasively detecting blood glucose information of the tested object; a management terminal A2, wherein the management terminal A2 is used for managing user information, including the personal information and the blood glucose information; a mobile client A3, where the mobile client A3 is configured to provide an information query service for a user; a database A4, wherein the database A4 is used for storing the personal information, the blood glucose information and treatment schemes of various blood glucose symptoms of the tested object.
Specifically, in this embodiment, the blood glucose information is the blood glucose condition of the measured object measured each time, including the blood glucose concentration, the blood glucose condition, and the like, and the database A4 includes an information sub-database and a regimen sub-database, where the information sub-database is used for storing various data generated by the measured object when measuring blood glucose, and includes, in addition to the personal information and the blood glucose information, measurement time, a therapeutic regimen, and the like; the regimen sub-database is used to store various of the treatment regimens.
Furthermore, the database A4 is divided into different areas, so that the data processing efficiency can be effectively improved, and faults of information output and information storage caused by information confusion are prevented. In addition, various data are stored in the database, so that the blood sugar condition of people can be monitored and analyzed.
Further, the database A4 is connected to the blood glucose detector A1, the management terminal A2 and the mobile client A3 through the internet, and the database A4 completes information transfer with the blood glucose detector A1, the management terminal A2 and the mobile client A3 through the internet.
In an alternative embodiment, referring to fig. 2, the blood glucose detector A1 includes an information control device a11 and a blood glucose collecting device a12. The information control device A11 is used for logging in by a user, collecting the personal information, outputting prompt information and blood sugar information; the blood sugar acquisition device A12, blood sugar acquisition device A12 with information control device A11 is connected, blood sugar acquisition device A12 is used for gathering the blood sugar information of testee. The blood glucose detector A1 is suitable for various scenes and has high practicability.
The information control device A11 is provided with a touch display screen, the tested object using the system can register by using the name and the telephone number of the tested object through the touch display screen for the first time, after the registration is completed, the tested object can selectively perfect the personal information, which is favorable for accurately managing the information of the tested object, providing long-term information inquiry service for users and protecting the privacy of the tested object in public places, and meanwhile, buttons can be reduced by using the touch display screen, so that the convenience of the blood glucose detector A1 and the satisfaction of the tested object are improved.
Further, the information control apparatus a11 may implant an information recording app, record information such as a time of registration login of the measured object and a time of blood glucose measurement using the information recording app, and store the recorded information in the information sub-database through the internet.
In an alternative embodiment, referring to fig. 3, the blood glucose collecting device a12 includes a finger fixing module a121, a light detecting module a122, a signal processing module a123, an influence factor detecting module a124, a blood glucose concentration detecting module a125, a pathology judging module a126, and a treatment scheme matching module a127.
Specifically, in this embodiment, a spring clip is disposed in the finger fixing module a121, and the finger fixing module a121 is used for placing and fixing a finger of the measured object.
Specifically, in this embodiment, the light detection module a122 is connected to the finger fixing module a121, the light detection module a122 is installed on a side of the finger fixing module a121 near the finger, and the light detection module a122 is configured to emit near infrared light and receive reflected near infrared light after the near infrared light passes through the finger. The light detection module a122 performs the following steps:
s1, utilizing the light emitting sub-module to emit the near infrared light.
The light emitting sub-module emits near infrared light having a wavelength of 1550nm using at least one photodiode.
S2, the light receiving sub-module is used for receiving the reflected near infrared light.
The diffuse reflection type near infrared light collection mode is adopted, so that the condition that near infrared light is difficult to penetrate skin tissue when human tissue is thicker is avoided, and the accuracy of blood glucose detection is improved.
Specifically, in this embodiment, the signal processing module a123 is connected to the light detecting module a122, and the signal processing module a123 is configured to obtain photometric data according to the reflected near infrared light. The signal processing module a123 performs the steps of:
and C1, converting the reflected near infrared rays into electric signals.
And C2, amplifying the electric signal to obtain an amplified signal.
And C3, carrying out analog-to-digital conversion on the amplified signal to obtain a digital signal.
And C4, extracting infrared spectrum information according to the digital signals.
And C5, obtaining the luminosity data by utilizing the infrared spectrum information.
The steps C1 to C5 can efficiently and accurately extract the photometric data, and the steps C1 to C5 can refer to the prior art, and will not be described herein.
Further, the luminosity data is recorded by the information record app and stored in the information sub-database through the internet.
Specifically, in this embodiment, the influence factor detection module a124 is connected to the finger fixing module a121, and the influence factor detection module a124 is configured to measure an influence factor affecting the blood glucose concentration.
Further, the influence factor to be measured by the influence factor detection module a124 needs to be determined according to the blood glucose concentration detection module a125, and the accuracy of the detected blood glucose concentration is improved by measuring the influence factor.
Still further, the influence factors include body temperature, pulse rate and systolic blood pressure, and the influence factor detection module a124 includes a temperature sensor and a sphygmomanometer. The temperature sensor is arranged on one side of the finger fixing module A121 close to the finger and is used for measuring the body temperature of a measured object; the sphygmomanometer can be selectively arranged on any surface far from the geometric center of the blood glucose detector according to actual conditions and is used for measuring the pulse rate and the systolic pressure of a tested object. The measured influence factors are recorded by the information record app and stored in the information sub-database via the internet.
Specifically, in this embodiment, the blood glucose concentration detection module a125 is connected to the signal processing module a123 and the influence factor detection module a124, and the blood glucose concentration detection module a125 is configured to detect the blood glucose concentration of the measured object by using the photometric data and the influence factor. The blood glucose concentration detection module a125 includes a blood glucose concentration detection model, which is constructed by:
d1, selecting a plurality of personnel to be tested and all reference influencing factors which possibly influence the blood sugar concentration measurement value.
The number of the personnel to be tested is 10, and the reference influence factors comprise ambient temperature, ambient humidity, body temperature, pulse rate, systolic pressure, diastolic pressure, height and waistline.
And D2, setting a time sequence of blood glucose monitoring, measuring the blood glucose concentration of the person to be tested by using an invasive method according to the time sequence to obtain invasive blood glucose concentration data, and measuring the reference influence factors to obtain measured values.
And measuring the blood glucose concentration of the person to be measured and the reference influence factor every half an hour from seven in the morning to ten in the evening, and recording measured data.
And D3, comparing the invasive blood glucose concentration data with the measured values time by time, calculating the change similarity of the invasive blood glucose concentration data and each reference influence factor, setting a similarity threshold to exclude redundant reference influence factors to obtain the influence factors, wherein the change similarity satisfies the following relation:
wherein L is the variation similarity,for the measurement value of the influencing factor at time j+1, -/->For the measurement of the influencing factor at moment j, < >>As a positive rate function of the influence factor, and (2)>For the invasive blood glucose concentration data at time j+1,/th time>For the invasive blood glucose concentration data at time j,>as a positive rate of change function of said invasive blood glucose concentration data +.>For the measurement of the influencing factor at time i+1,/for the measurement of the influencing factor at time i+1>For the measurement of the influencing factor at time i, < >>As a negative rate of change function of the influencing factor, and (2)>For the invasive blood glucose concentration data at time i+1,/a blood glucose concentration data of->For the invasive blood glucose concentration data at time j,>is a negative rate of change function of the invasive blood glucose concentration data.
Further, the positive and negative rate of change functions are differences between the later and the previous time instants, the influencing factor or the invasive blood glucose concentration data. The positive change rate function indicates that the influence factor or the invasive blood glucose concentration data is between two adjacent moments, the influence factor or the invasive blood glucose concentration data presents a situation that increases with time, and the negative change rate function indicates that the influence factor or the invasive blood glucose concentration data is between two adjacent moments, the influence factor or the invasive blood glucose concentration data presents a situation that decreases with time.
Further, calculating the variation similarity between each reference influence factor and the invasive blood glucose concentration data according to the data measured in the step D2 and the relational expression in the step, setting the similarity threshold to 0.5 to exclude redundant reference influence factors, and finally obtaining the influence factors such as body temperature, pulse rate and systolic blood pressure. When the blood glucose concentration of the measured object is measured, the influence factor is measured by the influence factor detection module A124, and the influence factor required to be measured by the influence factor detection module A124 is also determined by the step.
And D4, measuring the photometric data of the person to be tested by using the light detection module and the signal processing module according to the time sequence to obtain test photometric data.
The photometric data of the person to be tested is measured using the light detection module a122 and the signal processing module a123, and the photometric data in this step is taken as the test photometric data.
And D5, establishing the blood glucose concentration detection model by using the testing luminosity data, the invasive blood glucose concentration data and the influence factors.
And establishing a PSO-BP detection model by taking the weights and the threshold values of the BP neural network as particle positions of PSO, and establishing the blood glucose concentration detection model by taking the test luminosity data and the influence factors as inputs of the PSO-BP detection model.
Furthermore, the blood sugar concentration detection model can meet the requirement of noninvasive blood sugar measurement of multiple persons, and is suitable for measuring the blood sugar of the persons in public places, so that the blood sugar concentration detection model is suitable for various scenes, is beneficial to increasing the applicable scenes of the blood sugar detector A1, further improves the applicable scenes of the system provided by the application, and improves the primary protection capability on diabetes.
Specifically, in this embodiment, the condition determining module a126 is connected to the blood glucose concentration detecting module a125, and the condition determining module a126 is configured to determine and output the blood glucose condition. The condition determining module a126 includes a computer storage medium for determining a blood sugar condition, where a first type of computer program is stored in the computer storage medium for determining a blood sugar condition, and when the first type of computer program is running, the following steps are executed:
and E1, judging the blood sugar condition of the tested object according to the blood sugar concentration.
Depending on the blood glucose concentration, the blood glucose conditions can be divided into a hyperglycemic state, a hypoglycemic state and a normoglycemic state.
Further, in the fasting state, the blood glucose concentration is determined to be a hypoglycemic state when the blood glucose concentration is lower than 3.9mmol/L, the blood glucose concentration is determined to be a hyperglycemic state when the blood glucose concentration is higher than 6.1mmol/L, and the blood glucose concentration is determined to be a normoglycemic state when the blood glucose concentration is between 3.9mmol/L and 6.1 mmol/L.
Further, the blood glucose status is recorded by the information record app and stored in the information sub-database via the internet.
In other alternative embodiments, the glycemic condition may also be determined in other ways, for example, the glycemic condition may be further divided in connection with the dietary time of the subject, in which case the dietary time of the subject also needs to be collected.
And E2, judging whether to output the blood sugar symptoms according to the prompt information.
If the blood sugar symptom is not in a normal blood sugar state, the information control device A11 sends out prompt information whether to output the blood sugar symptom or not on the touch display screen, and the tested object can determine whether to output the blood sugar symptom or not on the touch display screen according to the self requirement and the environment. The privacy of the tested object is protected in public places, the satisfaction of the tested object is improved, and meanwhile, the tested object can know the blood sugar condition of the tested object and can be treated in time when needed.
Specifically, in this embodiment, the treatment scheme matching module a127 is connected to the condition determining module a126, and the treatment scheme matching device is configured to determine and output the treatment scheme. The treatment plan matching module a127 comprises a treatment plan matching computer storage medium, in which a second computer program is stored, which executes the following steps when running:
f1, matching an appropriate treatment regimen based on the personal information and the glycemic condition.
The treatment schemes of various blood sugar symptoms are stored in the scheme sub-database of the database A4, and after the blood sugar symptoms are determined, the treatment scheme matching module A127 can search the appropriate treatment scheme in the database A4 according to the blood sugar symptoms and the personal information such as the gender, weight, height and the like of the tested object.
Furthermore, whether the tested object logs in or not, whether the personal information is perfected or not, the treatment scheme is generated and recorded by the information record app, and finally stored in the information sub-database through the internet.
And F2, judging whether to output the treatment scheme and the output path of the treatment scheme according to the prompt information.
After matching with the treatment scheme, the information control device A11 sends out prompt information whether to output the treatment scheme or not on the touch display screen, and the tested object can determine whether to output the treatment scheme or not on the touch display screen according to the self requirement and the environment. The privacy protection method is beneficial to protecting the privacy of the tested object in public places and improving the satisfaction degree of the tested object.
In an optional embodiment, the management terminal A2 is connected to the mobile client A3 through the internet, the management terminal A2 includes two main functions of registration and login, an administrator performs online registration through the registration and login function, after the registration is successful, the administrator can use the registered account to log in to manage information of the user, the administrator can monitor and query data in the database A4 in real time through the user management function, so as to monitor blood sugar conditions of different people, and in the case that the measured object is registered and logged in, the administrator can query the treatment scheme, and according to the personal information such as gender, height, weight and the like of the measured object, provide more treatment comments in combination with the treatment scheme, and send the treatment comments to the mobile client A3 through the user management function of the management terminal A2. When the measured object is in the hyperglycemia state and the hypoglycemia state, an administrator can send an information confirmation prompt to the mobile client A3 through the management terminal A2 to remind the measured object to further check and confirm, and can also send a short message according to the registration number of the measured object or directly contact the measured object to go to a relevant place for further check and confirm by telephone, so that the patient is ensured to be treated in time, and the physical health of people is ensured.
In an alternative embodiment, the mobile client A3 comprises a blood glucose query client and a blood glucose query device. The blood sugar inquiry client comprises, but is not limited to blood sugar inquiry software, a blood sugar inquiry website and a blood sugar inquiry applet, and the blood sugar inquiry equipment comprises, but is not limited to, a mobile phone and a computer.
Specifically, in this embodiment, the object to be tested may register the account number in the blood glucose query software, the blood glucose query website, and the blood glucose query applet of the mobile phone and log in the blood glucose query software, the blood glucose query website, and the blood glucose query applet, and selectively perfect the personal information after logging in, that is, the object to be tested does not have to complete registration and perfect information on the information control device a11, but also can complete registration and perfect information on the mobile client A3, thereby improving the convenience of the system and facilitating popularization.
Furthermore, the tested object can inquire the blood sugar information, the treatment scheme, the treatment opinion given by the administrator and the information confirmation prompt on blood sugar inquiring software, a blood sugar inquiring website and a blood sugar inquiring applet.
In summary, the system provided by the application is connected with the blood glucose detector, the management terminal, the mobile client and the database through the Internet, has high degree of automation and intelligence, and is suitable for various scenes by combining the corresponding blood glucose concentration detection model. Such as hospitals, community health service centers, businesses, and malls. The method realizes blood sugar detection on diabetics and non-diabetics in different scenes, achieves primary prevention of diabetes, and provides convenience for statistics and analysis of blood sugar information. The blood sugar detection method has the advantages that the blood sugar can be detected by the detected object at any time, the diagnosis rate is improved, the workload and the working pressure of medical staff are greatly relieved, the time of the detected object is saved, the anxiety emotion of the detected object waiting in a queue is relieved, meanwhile, the fear psychology of the detected object is reduced by the blood sugar detection method of noninvasive detection, and the physical injury to the detected object is avoided. In addition, the system is also beneficial to promoting people to develop healthy living habits.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the application, and are intended to be included within the scope of the appended claims and description.
Claims (5)
1. A fully automatic intelligent blood glucose testing system, comprising:
the blood sugar detector is used for collecting personal information of the tested object and noninvasively detecting blood sugar information of the tested object;
the management terminal is used for managing user information, including the personal information and the blood glucose information;
the mobile client is used for providing information inquiry service for the user;
a database for storing the personal information, the glycemic information, and treatment regimens for various glycemic conditions of a subject;
the blood glucose detector includes:
the information control device is used for logging in by a user, collecting the personal information, outputting prompt information and blood glucose information;
the blood sugar acquisition device is connected with the information control device and is used for acquiring the blood sugar information of the tested object;
the blood glucose collection device includes:
the finger fixing module is provided with a spring clamp and is used for placing and fixing the finger of the measured object;
the light detection module is connected with the finger fixing module, is arranged on one side, close to the finger, of the finger fixing module and is used for emitting near infrared rays and receiving reflected near infrared rays after the near infrared rays pass through the finger;
the signal processing module is connected with the light detection module and is used for acquiring luminosity data according to the reflected near infrared rays;
the influence factor detection module is connected with the finger fixing module and is used for measuring influence factors influencing blood sugar concentration; the influence factors comprise body temperature, pulse rate and systolic blood pressure, and the influence factor detection module (A124) comprises a temperature sensor and a sphygmomanometer;
the blood sugar concentration detection module is connected with the signal processing module and the influence factor detection module and is used for detecting the blood sugar concentration of a tested object by utilizing the luminosity data and the influence factor;
the light detection module includes a light emitting sub-module and a light receiving sub-module, which are arranged on the same side of a finger, and performs the steps of:
utilizing the light emitting sub-module for emitting the near infrared light;
the light receiving sub-module is used for receiving the reflected near infrared light;
the signal processing module performs the steps of:
converting the reflected near infrared light into an electrical signal;
amplifying the electric signal to obtain an amplified signal;
performing analog-to-digital conversion on the amplified signal to obtain a digital signal;
extracting infrared spectrum information according to the digital signal;
obtaining the photometric data using the infrared spectral information;
the blood glucose concentration detection module comprises a blood glucose concentration detection model, and the blood glucose concentration detection model is constructed through the following steps:
selecting a plurality of personnel to be tested and all reference influence factors which possibly influence the blood sugar concentration measurement value; the reference influencing factors comprise ambient temperature, ambient humidity, body temperature, pulse rate, systolic pressure, diastolic pressure, height and waistline;
setting a time sequence of blood glucose monitoring, measuring the blood glucose concentration of the person to be tested by using an invasive method according to the time sequence to obtain invasive blood glucose concentration data, and measuring the reference influence factors to obtain measured values;
comparing the invasive blood glucose concentration data with the measured values time by time, calculating the change similarity of the invasive blood glucose concentration data and each reference influence factor, setting a similarity threshold to exclude redundant reference influence factors to obtain the influence factors, wherein the change similarity satisfies the following relation:
，
wherein L is the variation similarity,for the measurement value of the influencing factor at time j+1, -/->For the measurement of the influencing factor at moment j, < >>As a positive rate function of the influence factor, and (2)>For the invasive blood glucose concentration data at time j+1,/th time>For the invasive blood glucose concentration data at time j,>as a positive rate of change function of said invasive blood glucose concentration data +.>For the measurement of the influencing factor at time i+1,/for the measurement of the influencing factor at time i+1>For the measurement of the influencing factor at time i, < >>As a negative rate of change function of the influencing factor, and (2)>For the invasive blood glucose concentration data at time i+1, P i For the invasive blood glucose concentration data at time i,>a negative rate of change function for the invasive blood glucose concentration data;
measuring photometric data of the person to be tested by using the light detection module and the signal processing module according to the time sequence to obtain test photometric data;
establishing the blood glucose concentration detection model by using the test luminosity data, the invasive blood glucose concentration data and the influence factors; and establishing a PSO-BP detection model by taking the weights and the threshold values of the BP neural network as particle positions of PSO, and establishing the blood glucose concentration detection model by taking the test luminosity data and the influence factors as inputs of the PSO-BP detection model.
2. The fully automatic intelligent blood glucose testing system of claim 1, wherein the blood glucose collection device further comprises:
the pathology judgment module is connected with the blood glucose concentration detection module and is used for judging and outputting the blood glucose pathology;
the treatment scheme matching module is connected with the pathology judging module, and the treatment scheme matching device is used for judging and outputting the treatment scheme.
3. The fully automatic intelligent blood glucose testing system of claim 2, wherein the condition determination module comprises a blood glucose condition determination computer storage medium, wherein the blood glucose condition determination computer storage medium stores a first computer program, and wherein the first computer program performs the following steps when running:
judging the blood sugar condition of the tested object according to the blood sugar concentration;
judging whether to output the blood sugar symptoms according to the prompt information.
4. A fully automatic intelligent blood glucose testing system according to claim 3, wherein said treatment regimen matching module comprises a treatment regimen matching computer storage medium having a second computer program stored therein, said second computer program executing the steps of:
matching an appropriate treatment regimen based on the personal information and the glycemic condition;
judging whether to output the treatment scheme and the output path of the treatment scheme according to the prompt information.
5. The fully automatic intelligent blood glucose testing system of claim 4, wherein the mobile client comprises:
a blood glucose query client including, but not limited to, blood glucose query software, a blood glucose query website, and a blood glucose query applet;
blood glucose query devices including, but not limited to, cell phones and computers.
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