CN103472010A - Diabetes detection device - Google Patents
Diabetes detection device Download PDFInfo
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- CN103472010A CN103472010A CN2013104234634A CN201310423463A CN103472010A CN 103472010 A CN103472010 A CN 103472010A CN 2013104234634 A CN2013104234634 A CN 2013104234634A CN 201310423463 A CN201310423463 A CN 201310423463A CN 103472010 A CN103472010 A CN 103472010A
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- 206010012601 diabetes mellitus Diseases 0.000 title claims abstract description 35
- 238000001514 detection method Methods 0.000 title claims abstract description 31
- 210000002700 urine Anatomy 0.000 claims abstract description 49
- 210000004369 blood Anatomy 0.000 claims abstract description 45
- 239000008280 blood Substances 0.000 claims abstract description 45
- 229910052760 oxygen Inorganic materials 0.000 claims abstract description 19
- 239000001301 oxygen Substances 0.000 claims abstract description 19
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims abstract description 18
- 238000012937 correction Methods 0.000 claims abstract description 16
- 238000006243 chemical reaction Methods 0.000 claims abstract description 14
- WQZGKKKJIJFFOK-GASJEMHNSA-N Glucose Natural products OC[C@H]1OC(O)[C@H](O)[C@@H](O)[C@@H]1O WQZGKKKJIJFFOK-GASJEMHNSA-N 0.000 claims abstract description 11
- 239000008103 glucose Substances 0.000 claims abstract description 11
- 230000005540 biological transmission Effects 0.000 claims abstract description 10
- 239000000306 component Substances 0.000 claims description 32
- 238000005534 hematocrit Methods 0.000 claims description 7
- 239000012503 blood component Substances 0.000 claims description 6
- 238000009535 clinical urine test Methods 0.000 claims description 6
- 210000003743 erythrocyte Anatomy 0.000 claims description 4
- 201000010099 disease Diseases 0.000 claims description 3
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 3
- 230000006870 function Effects 0.000 claims description 3
- 208000017169 kidney disease Diseases 0.000 claims description 3
- 208000019423 liver disease Diseases 0.000 claims description 3
- 238000012360 testing method Methods 0.000 claims description 3
- 208000002249 Diabetes Complications Diseases 0.000 abstract description 15
- 206010012655 Diabetic complications Diseases 0.000 description 8
- 201000001421 hyperglycemia Diseases 0.000 description 7
- 230000007774 longterm Effects 0.000 description 4
- 208000011580 syndromic disease Diseases 0.000 description 4
- 210000000748 cardiovascular system Anatomy 0.000 description 2
- 238000003745 diagnosis Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000004064 dysfunction Effects 0.000 description 2
- 230000002526 effect on cardiovascular system Effects 0.000 description 2
- 210000001508 eye Anatomy 0.000 description 2
- NOESYZHRGYRDHS-UHFFFAOYSA-N insulin Chemical compound N1C(=O)C(NC(=O)C(CCC(N)=O)NC(=O)C(CCC(O)=O)NC(=O)C(C(C)C)NC(=O)C(NC(=O)CN)C(C)CC)CSSCC(C(NC(CO)C(=O)NC(CC(C)C)C(=O)NC(CC=2C=CC(O)=CC=2)C(=O)NC(CCC(N)=O)C(=O)NC(CC(C)C)C(=O)NC(CCC(O)=O)C(=O)NC(CC(N)=O)C(=O)NC(CC=2C=CC(O)=CC=2)C(=O)NC(CSSCC(NC(=O)C(C(C)C)NC(=O)C(CC(C)C)NC(=O)C(CC=2C=CC(O)=CC=2)NC(=O)C(CC(C)C)NC(=O)C(C)NC(=O)C(CCC(O)=O)NC(=O)C(C(C)C)NC(=O)C(CC(C)C)NC(=O)C(CC=2NC=NC=2)NC(=O)C(CO)NC(=O)CNC2=O)C(=O)NCC(=O)NC(CCC(O)=O)C(=O)NC(CCCNC(N)=N)C(=O)NCC(=O)NC(CC=3C=CC=CC=3)C(=O)NC(CC=3C=CC=CC=3)C(=O)NC(CC=3C=CC(O)=CC=3)C(=O)NC(C(C)O)C(=O)N3C(CCC3)C(=O)NC(CCCCN)C(=O)NC(C)C(O)=O)C(=O)NC(CC(N)=O)C(O)=O)=O)NC(=O)C(C(C)CC)NC(=O)C(CO)NC(=O)C(C(C)O)NC(=O)C1CSSCC2NC(=O)C(CC(C)C)NC(=O)C(NC(=O)C(CCC(N)=O)NC(=O)C(CC(N)=O)NC(=O)C(NC(=O)C(N)CC=1C=CC=CC=1)C(C)C)CC1=CN=CN1 NOESYZHRGYRDHS-UHFFFAOYSA-N 0.000 description 2
- 150000002576 ketones Chemical class 0.000 description 2
- 210000003734 kidney Anatomy 0.000 description 2
- 208000030159 metabolic disease Diseases 0.000 description 2
- 238000000034 method Methods 0.000 description 2
- 210000000653 nervous system Anatomy 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 206010010071 Coma Diseases 0.000 description 1
- 208000001380 Diabetic Ketoacidosis Diseases 0.000 description 1
- 208000007342 Diabetic Nephropathies Diseases 0.000 description 1
- 206010014418 Electrolyte imbalance Diseases 0.000 description 1
- 102000004877 Insulin Human genes 0.000 description 1
- 108090001061 Insulin Proteins 0.000 description 1
- 206010023379 Ketoacidosis Diseases 0.000 description 1
- 208000007976 Ketosis Diseases 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 230000001154 acute effect Effects 0.000 description 1
- 210000004204 blood vessel Anatomy 0.000 description 1
- 230000002950 deficient Effects 0.000 description 1
- 230000018044 dehydration Effects 0.000 description 1
- 238000006297 dehydration reaction Methods 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 208000033679 diabetic kidney disease Diseases 0.000 description 1
- 210000003038 endothelium Anatomy 0.000 description 1
- 230000002727 hyperosmolar Effects 0.000 description 1
- 230000001771 impaired effect Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 229940125396 insulin Drugs 0.000 description 1
- 230000003914 insulin secretion Effects 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 210000000056 organ Anatomy 0.000 description 1
- 230000002085 persistent effect Effects 0.000 description 1
- 102000004169 proteins and genes Human genes 0.000 description 1
- 108090000623 proteins and genes Proteins 0.000 description 1
- 230000009885 systemic effect Effects 0.000 description 1
- 210000001519 tissue Anatomy 0.000 description 1
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- Investigating Or Analysing Biological Materials (AREA)
Abstract
The invention provides a diabetes detection device. The diabetes detection device comprises a detection module and a data acquisition module, wherein the detection module comprises an electrochemical sensor, a first analog-digital converter, a hematokrit and oxygen partial pressure fitting curve correction submodule, a color sensor, a second analog-digital converter and a standard color correction submodule, and the data acquisition module comprises a classification submodule, a memory, a medical language conversion submodule and a wireless transmission submodule. According to the diabetes detection device provided by the invention, blood glucose and various urine indexes can be obtained by detecting blood and urine, and are subjected to classified and cross-over analysis so as to be converted into corresponding medical indexes, so that the diabetes detection device can be used for discovering diabetes and diabetes complications more effectively and timely than similar products in the current market, and realizing the daily household detection on the diabetes and the diabetes complications.
Description
Technical Field
The invention relates to a diabetes detection technology, in particular to a diabetes detection device.
Background
With the improvement of living standard of people, the prevalence rate of diabetes in China is remarkably increased in nearly 20 years. At present, one hundred million diabetics, plus 1.5 million high risk groups, are diagnosed. That is, one of ten Chinese people is a diabetic. Therefore, daily household detection is particularly important for diabetics.
Diabetes mellitus is a group of metabolic diseases characterized by hyperglycemia due to defective insulin secretion and/or impaired insulin action. Persistent hyperglycemia and long-term metabolic disorders, among others, can lead to damage to and dysfunction and failure of systemic tissues and organs, particularly the eye, kidney, cardiovascular and nervous systems. Serious patients can cause acute complications of ketoacidosis and hyperosmolar coma, such as dehydration, electrolyte disturbance and acid-base balance disturbance.
At present, aiming at the hyperglycemia characteristics of the diabetic, the household daily detection medical instrument is mainly a portable glucometer which can rapidly detect the blood sugar level of the diabetic within a few seconds mainly through blood of one drop of fingertip. However, in view of the nature of diabetes, hyperglycemia is only an appearance characteristic thereof, and diabetic complications (such as eye, kidney, cardiovascular and nervous system damages and their dysfunctions and failures caused by diabetes) due to long-term hyperglycemia are the most problems to be solved. However, the current home-use diabetes detecting devices on the market only have a portable blood glucose meter, which can indirectly reflect the control of diabetes mainly by rapidly detecting the blood glucose level of the diabetic, but in the actual situation, it is difficult to effectively control the further deterioration of diabetes and the generation of diabetic complications by only monitoring the daily blood glucose level of the diabetic. The main reason is that the hyperglycemia is more or less in daily life, and the damage of hyperglycemia to the endothelium of small blood vessels of the whole body is a long-term damage process, and in the long-term damage process, especially in the middle and early stages, the diabetic complications can be better controlled through diagnosis of medical science data and timely and appropriate professional treatment.
Disclosure of Invention
In view of the above, the present invention provides a diabetes detection device, which can detect blood and urine to obtain blood sugar and various urine indexes, and classify the indexes to convert into corresponding medical indexes, so as to effectively implement daily home detection of diabetes and diabetic complications.
The invention provides a diabetes detection device, which comprises a detection module and a data acquisition module, wherein the detection module comprises an electrochemical sensor, a first analog-to-digital converter, a hematocrit and oxygen partial pressure fitting curve correction submodule, a color sensor, a second analog-to-digital converter and a standard color correction submodule; the data acquisition module comprises a classification sub-module, a memory, a medical language conversion sub-module and a wireless transmission sub-module; wherein,
the electrochemical sensor is used for converting the oxygen content and the blood sugar content in the blood into corresponding analog signals;
the first analog-to-digital converter is used for converting an analog signal input by the electrochemical sensor into a digital signal and sending the digital signal to the erythrocyte volume and oxygen partial pressure fitting curve corrector module;
the erythrocyte volume and oxygen partial pressure fitting curve corrector sub-module is used for correcting the blood sugar content according to the oxygen content in the blood to obtain the corrected blood sugar content;
the color sensor is used for performing photoelectric signal conversion on the urine test paper, generating urine component analog signals corresponding to the color of the urine test paper and sending the urine component analog signals to the second analog-to-digital converter; the second analog-to-digital converter is used for converting photoelectric signals of the standard color test paper to generate standard color analog signals and sending the standard color analog signals to the second analog-to-digital converter;
the second analog-to-digital converter is used for converting an analog signal input by the color sensor into a digital signal and sending the digital signal to the standard color correction submodule;
the standard color correction submodule is used for receiving the urine component digital signal and the standard color digital signal sent by the second analog-to-digital converter, and correcting the urine component according to the standard color to obtain the corrected urine component;
the classification submodule is used for classifying the blood sugar data obtained from the hematocrit and oxygen partial pressure fitting curve correction submodule and the urine component data obtained from the standard color correction submodule according to the types of diseases which are diagnosed by the blood component data and the urine component data;
the memory is used for storing the classified blood component data and the classified urine component data which are obtained from the classification submodule;
the medical index conversion submodule is used for converting the blood sugar component data and the urine component data into corresponding medical indexes;
and the wireless transmission submodule is used for wirelessly transmitting the medical index obtained by the medical index conversion module to a corresponding terminal.
Preferably, the classifying submodule classifies the blood glucose data into diabetes type data, and classifies the urine component data into kidney disease type data, liver disease type data, and number of types of concentration function of basic urine
Accordingly.
Preferably, the wireless transmission sub-module sends the obtained medical index to the corresponding mobile phone in a form of a mobile phone short message by analyzing the SIM card.
According to the technical scheme, the diabetes detection device provided by the invention can be used for obtaining the blood sugar and various urine indexes by detecting blood and urine, classifying and cross-analyzing the blood sugar and various urine indexes to convert the blood sugar and various urine indexes into corresponding medical indexes, so that diabetes and diabetic complications can be found more effectively and timely than like products in the market at present, and daily household detection of the diabetes and diabetic complications is realized.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a diabetes detection device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
Fig. 1 is a schematic diagram of a diabetes detection device according to an embodiment of the present invention, which includes a detection module and a data acquisition module, wherein the detection module includes an electrochemical sensor 11, a first analog-to-digital converter 12, a hematocrit and oxygen partial pressure fitting curve corrector sub-module 13, a color sensor 14, a second analog-to-digital converter 15, and a standard color corrector sub-module 16; the data acquisition module comprises a classification submodule 21, a memory 22, a medical language conversion submodule 23 and a wireless transmission submodule 24; wherein,
the electrochemical sensor 11 is used for converting the oxygen content and the blood sugar content in the blood into corresponding analog signals;
the first analog-to-digital converter 12 is configured to convert an analog signal input by the electrochemical sensor 11 into a digital signal, and send the digital signal to the syndrome module 13 of the fitted curve of hematocrit and oxygen partial pressure;
the syndrome module 13 for fitting a curve of hematocrit and oxygen partial pressure is used for correcting the blood glucose content according to the oxygen content in blood to obtain the corrected blood glucose content;
the color sensor 14 is configured to perform photoelectric signal conversion on the urine test paper, generate an analog signal of urine components corresponding to the color of the urine test paper, and send the analog signal to the second analog-to-digital converter 15; the standard color test paper is used for photoelectric signal conversion to generate a standard color analog signal, and the standard color analog signal is sent to the second analog-to-digital converter 15;
the second analog-to-digital converter 15 is configured to convert an analog signal input by the color sensor 14 into a digital signal, and send the digital signal to the standard color correction sub-module 16;
the standard color correction submodule 16 is configured to receive the urine component digital signal and the standard color digital signal sent by the second analog-to-digital converter 15, and correct the urine component according to the standard color to obtain a corrected urine component;
the classification sub-module 21 is configured to classify the blood glucose data obtained from the hematocrit-oxygen partial pressure fitting curve syndrome module 13 and the urine component data obtained from the standard color syndrome module 16 according to the types of diseases for which the blood component data and the urine component data are used for diagnosis;
the classification submodule divides the blood sugar data into diabetes type data, and divides the urine component data into kidney disease type data, liver disease type data and basic urine concentration function type data.
The memory 22 is used for storing the classified blood component data and the classified urine component data obtained from the classification submodule 21;
the medical index conversion submodule 23 is configured to convert the blood sugar component data and the urine component data into corresponding medical indexes; for example, blood glucose and urine glucose are combined and classified as indicators of diabetes; combining blood sugar with urine ketone body, and classifying the blood sugar and urine ketone body as diabetic ketosis index; blood sugar, urine protein and urine sugar are combined and classified as diabetic nephropathy indexes.
And the wireless transmission submodule 24 is configured to wirelessly transmit the medical index obtained by the medical index conversion module to a corresponding terminal. The wireless transmission sub-module can send the obtained medical index to a corresponding mobile phone in a form of a mobile phone short message by analyzing the SIM card.
According to the technical scheme, the diabetes detection device provided by the invention can be used for obtaining the blood sugar and various urine indexes by detecting blood and urine, classifying and cross-analyzing the blood sugar and various urine indexes to convert the blood sugar and various urine indexes into corresponding medical indexes, so that diabetes and diabetic complications can be found more effectively and timely than like products in the market at present, and daily household detection of the diabetes and diabetic complications is realized.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: it is to be understood that modifications may be made to the above-described arrangements in the embodiments or equivalents may be substituted for some of the features of the embodiments without departing from the spirit or scope of the present invention.
Claims (3)
1. A diabetes detection device comprises a detection module and a data acquisition module, and is characterized in that the detection module comprises an electrochemical sensor, a first analog-to-digital converter, a hematocrit and oxygen partial pressure fitting curve correction submodule, a color sensor, a second analog-to-digital converter and a standard color correction submodule; the data acquisition module comprises a classification sub-module, a memory, a medical language conversion sub-module and a wireless transmission sub-module; wherein,
the electrochemical sensor is used for converting the oxygen content and the blood sugar content in the blood into corresponding analog signals;
the first analog-to-digital converter is used for converting an analog signal input by the electrochemical sensor into a digital signal and sending the digital signal to the erythrocyte volume and oxygen partial pressure fitting curve corrector module;
the erythrocyte volume and oxygen partial pressure fitting curve corrector sub-module is used for correcting the blood sugar content according to the oxygen content in the blood to obtain the corrected blood sugar content;
the color sensor is used for performing photoelectric signal conversion on the urine test paper, generating urine component analog signals corresponding to the color of the urine test paper and sending the urine component analog signals to the second analog-to-digital converter; the second analog-to-digital converter is used for converting photoelectric signals of the standard color test paper to generate standard color analog signals and sending the standard color analog signals to the second analog-to-digital converter;
the second analog-to-digital converter is used for converting an analog signal input by the color sensor into a digital signal and sending the digital signal to the standard color correction submodule;
the standard color correction submodule is used for receiving the urine component digital signal and the standard color digital signal sent by the second analog-to-digital converter, and correcting the urine component according to the standard color to obtain the corrected urine component;
the classification submodule is used for classifying the blood sugar data obtained from the hematocrit and oxygen partial pressure fitting curve correction submodule and the urine component data obtained from the standard color correction submodule according to the types of diseases which are diagnosed by the blood component data and the urine component data;
the memory is used for storing the classified blood component data and the classified urine component data which are obtained from the classification submodule;
the medical index conversion submodule is used for converting the blood sugar component data and the urine component data into corresponding medical indexes;
and the wireless transmission submodule is used for wirelessly transmitting the medical index obtained by the medical index conversion module to a corresponding terminal.
2. The diabetes detection apparatus according to claim 1, wherein the classification sub-module classifies the blood glucose data into diabetes type data and the urine component data into kidney disease type data, liver disease type data, and basic urine concentration function type data.
3. The diabetes detection apparatus according to claim 1, wherein the wireless transmission sub-module sends the obtained medical index to the corresponding mobile phone in a form of a short message through analyzing the SIM card.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2013104234634A CN103472010A (en) | 2013-09-17 | 2013-09-17 | Diabetes detection device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2013104234634A CN103472010A (en) | 2013-09-17 | 2013-09-17 | Diabetes detection device |
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| CN103472010A true CN103472010A (en) | 2013-12-25 |
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| CN2013104234634A Pending CN103472010A (en) | 2013-09-17 | 2013-09-17 | Diabetes detection device |
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103808668A (en) * | 2014-01-20 | 2014-05-21 | 榕盛（苏州）医疗技术有限公司 | Application method of blood glucose analysis system based on APP (application) technology and cloud computing technology |
| CN104697935A (en) * | 2014-12-29 | 2015-06-10 | 满洪柱 | Detection analysis system for urinalysis |
| US10311208B2 (en) | 2014-06-03 | 2019-06-04 | Smart Meter Corporation | System, apparatus and method for the wireless monitoring of medical test data |
| CN110376168A (en) * | 2019-06-18 | 2019-10-25 | 江西掌护医疗科技有限公司 | Long-range system for detecting blood sugar |
| CN110887960A (en) * | 2019-12-02 | 2020-03-17 | 电子科技大学 | A system and method for quantitative detection of urine test strips based on machine vision |
| WO2020053706A1 (en) * | 2018-09-10 | 2020-03-19 | Zhou Tian Xing | Wearable digital device for personal health use for saliva, urine, and blood testing and mobile wrist watch powered by user body |
| CN117153416A (en) * | 2023-10-26 | 2023-12-01 | 天津医科大学第二医院 | Diabetes screening data processing and management system |
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| CN110887960A (en) * | 2019-12-02 | 2020-03-17 | 电子科技大学 | A system and method for quantitative detection of urine test strips based on machine vision |
| CN117153416A (en) * | 2023-10-26 | 2023-12-01 | 天津医科大学第二医院 | Diabetes screening data processing and management system |
| CN117153416B (en) * | 2023-10-26 | 2024-01-26 | 天津医科大学第二医院 | Diabetes screening data processing and management system |
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Application publication date: 20131225 |