KR20170047993A - Judgment system for risk of diabetes by transmitting data security - Google Patents

Judgment system for risk of diabetes by transmitting data security Download PDF

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Publication number
KR20170047993A
KR20170047993A KR1020150148801A KR20150148801A KR20170047993A KR 20170047993 A KR20170047993 A KR 20170047993A KR 1020150148801 A KR1020150148801 A KR 1020150148801A KR 20150148801 A KR20150148801 A KR 20150148801A KR 20170047993 A KR20170047993 A KR 20170047993A
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South Korea
Prior art keywords
diabetes
data
diabetic
risk
level
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KR1020150148801A
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Korean (ko)
Inventor
박성훈
백진동
김종탁
판희준
문용일
최석우
이병문
강운구
Original Assignee
가천대학교 산학협력단
주식회사 엠에스피씨앤에스
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Priority to KR1020150148801A priority Critical patent/KR20170047993A/en
Publication of KR20170047993A publication Critical patent/KR20170047993A/en

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • 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
    • A61B5/14532—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
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • G06F19/3418—
    • G06F19/3431—
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
    • G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
    • G06F21/6245—Protecting personal data, e.g. for financial or medical purposes
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/06—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols the encryption apparatus using shift registers or memories for block-wise or stream coding, e.g. DES systems or RC4; Hash functions; Pseudorandom sequence generators
    • H04L9/0643—Hash functions, e.g. MD5, SHA, HMAC or f9 MAC
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/08—Key distribution or management, e.g. generation, sharing or updating, of cryptographic keys or passwords
    • H04L9/0861—Generation of secret information including derivation or calculation of cryptographic keys or passwords

Abstract

The present invention relates to a system for calculating a risk for diabetes through a data security transmission. The diabetes-risk calculating system through a data security transmission comprises: a diabetes data collecting unit which receives measuring data from a plurality of measuring devices which measure biometric data to output the same as measuring data, or receives data related to user information; a diabetes risk calculating unit which uses the diabetes data to calculate the degree of the diabetes risk and categorize the same as normal, danger or risk steps; a diabetes data encryption unit which receives diabetes data containing the measuring data and data related to the user information from the diabetes data collecting unit and the degree of the diabetes risk, encrypts the same by using Spritz code and algorithm and checks the integrity by means of MD5; and a server which has a diabetes data collecting terminal containing a first diabetes data transmitting/receiving portion which transmits the diabetes data encrypted and integrity checked by the diabetes data encryption unit or the degree of the diabetes risk to the outside, and a second diabetes data transmitting/receiving portion which receives the encrypted and integrity checked diabetes data transmitted from the first diabetes data transmitting/receiving portion or the degree of the diabetes risk, and saves the same in a database unit.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to a diabetes risk calculation system,

The present invention relates to a diabetes risk calculation system through data security transmission.

Diabetes mellitus is a type of metabolic disease that lacks insulin secretion or does not function normally. It is characterized by hyperglycemia in which the concentration of glucose in the blood rises. It causes many symptoms and signs due to hyperglycemia, It is one of the diseases.

The glucose measuring device is a device for measuring glucose in the blood of a diabetic patient. The glucose measuring device can be easily operated by a patient as well as a hospital.

For example, the patient measured glucose levels using a glucose meter, and judged the risk of diabetes at the time of measurement according to the measured values, and took measures such as dietary control or taking medication.

However, in the case of judging the risk of diabetes using the conventional glucose meter, only the blood sugar is used as an indicator, so that it is judged that there is no consideration of other variables that affect the risk of diabetes.

Therefore, there is a need for an apparatus or method for judging the risk of diabetes using various variables.

In addition, when the user information is transmitted to the server and the server determines that the diabetic risk is determined, there is a risk that the user information stored in the server and stored may be hacked.

DISCLOSURE OF INVENTION Technical Problem The present invention provides a method for diagnosing a diabetic risk in a diabetic patient by using diabetes data, which includes various information such as blood glucose, hypertension, age, family history, etc., The present invention is intended to more specifically calculate the risk of diabetic state using a conventional glucose meter used.

The diabetes data collection terminal transmits the diabetes data to the diabetes risk determination unit and stores the data in the diabetes risk determination unit to encrypt and transmit and store the diabetes data to improve the security of transmission and storage of diabetes data .

The diabetic risk calculation system for data security transmission according to an embodiment of the present invention includes a plurality of measurement devices for measuring body data and outputting measurement data as measurement data, A diabetic risk calculator for calculating a diabetic risk level to a normal level, a risk level, or a warning level using the diabetes data; Data and a degree of danger of diabetes, and encrypting the data with Spritz cipher and algorithm and performing an integrity check with MD5, and the diabetes data encryption unit encrypts and verifies the integrity of the diabetes data or diabetes risk, The first diabetic de And a second diabetes data transmitting and receiving unit for receiving the diabetes data or the degree of diabetes risk transmitted from the first diabetes data transmitting and receiving unit and storing the diabetes data or the degree of diabetes risk transmitted from the first diabetes data transmitting and receiving unit, .

In one example, the body data collected by the diabetes data collection unit as the measurement data is characterized by at least two of blood pressure, oxygen saturation, body weight, fasting blood glucose, random blood glucose, glycated hemoglobin, electrocardiogram, and body temperature.

The diabetic risk calculator calculates the diabetic level as a risk level when the HbA1c is greater than or equal to 6.5 and the diabetic level is calculated as a warning level when the HbA1c is greater than or equal to 5.7 and less than 6.5, When the fasting blood glucose is less than 5.7, the fasting blood glucose is compared with 100. If the fasting blood glucose is greater than or equal to 100 and less than 126 at the same time, the diabetic level is calculated as a warning step. The diabetic level is calculated as a warning level when the patient has a hyperglycemia and the random blood glucose level is less than 200, and the diabetic level is calculated as a level of diabetic level if the random blood glucose level is greater than or equal to 200.

The diabetes data collecting unit receives a plurality of the body data from the plurality of measuring instruments via Bluetooth, Zigbee, Wi-Fi or 6 LowPAN.

In one example, the diabetic risk calculating unit calculates a degree of diabetic risk by assigning a first priority to the glycated hemoglobin and a second priority to fasting blood glucose, among the plurality of the measurement data measured values.

The diabetes risk calculator calculates the diabetic level as a normal level when the BMI is less than 25, comparing the BMI index to 25 when the patient is not a hyperglycemia patient. When the BMI is greater than or equal to 25, the age is calculated as 45 And the diabetic level is calculated as a risk level when the age is 45 or more.

The diabetic risk calculating unit calculates the diabetic level warning step when the blood pressure is 140/90 or more when the blood pressure is 140/90 or more when the age is less than 45 or less.

In addition, when the blood pressure is less than 140/90, the family history of diabetes is calculated. If the patient has a family history, the diabetes level warning is calculated. If the patient has no family history, .

According to this aspect, since the diabetes risk judgment unit receives a plurality of diabetes data collected from the diabetes data collection terminal and determines the risk of diabetes, it has an effect of calculating a specific diabetes risk level rather than a diabetes risk judgment through conventional blood glucose measurement .

The diabetes data collection terminal encrypts diabetes data, processes the diabetes data by applying a forgery and modulation detection algorithm, and transmits the data to the diabetes risk judgment unit. Thus, the diabetes risk judgment unit improves data security when transmitting and storing diabetes data .

1 is a block diagram illustrating a configuration of a diabetes risk calculation system through data security transmission according to an embodiment of the present invention.
FIG. 2 is a flowchart illustrating a method of calculating a diabetic risk of a diabetic risk calculation system through data security transmission according to an exemplary embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily carry out the present invention. The present invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. In order to clearly illustrate the present invention, parts not related to the description are omitted, and similar parts are denoted by like reference characters throughout the specification.

Hereinafter, an apparatus and method for calculating a diabetic risk using the Internet according to an embodiment of the present invention will be described with reference to the accompanying drawings.

Referring first to FIG. 1, the structure of a diabetes risk calculation system through data security transmission according to an embodiment of the present invention will be described in detail.

As shown in FIG. 1, the diabetes risk calculation system through data security transmission includes a diabetes data collection terminal 100 and a server 200.

The diabetes data collecting terminal 100 has a structure of connecting to the second diabetes data transmitting and receiving unit 210 of the server 200 through the first diabetes data transmitting and receiving unit 130. In one example, The first diabetes data transmitting and receiving unit 130 of the server 200 is a communication module that transmits and receives data to and from the second diabetes data transmitting and receiving unit 210 of the server 200. The first diabetes data transmitting and receiving unit 130 includes a wireless communication module for communicating with a mobile communication network, May be formed as a module.

When the first diabetes data transmitting and receiving unit 130 is a wireless communication module, the first diabetes data transmitting and receiving unit 130 transmits and receives data to and from the second diabetes data transmitting and receiving unit 210 (210) of the server 200 through a wireless communication network such as Wi- As shown in Fig.

When the first diabetes data transmitting and receiving unit 130 is a mobile communication module, the first diabetes data transmitting and receiving unit 130 accesses the 3G network or the LTE network and transmits the second diabetes data to the second diabetes data transmitting and receiving unit 210 of the server 200. [ As shown in Fig.

The first diabetes data transmission / reception unit 130 has a structure in which the first diabetes data transmission / reception unit 130 is connected to the wireless communication network or the mobile communication network and is connected to the second diabetes data transmission / reception unit 210 of the server 200, The second diabetes data transmission and reception unit 210 of the server 200 may be connected to the Internet and may transmit data transmitted by the first diabetes data transmission and reception unit 130 to the Internet And transmits the data that has been received or received and stored according to an external request.

In one example, an object to which the second diabetes data transmitting / receiving unit 210 transmits data may be the diabetes data collecting terminal 100 or other terminal connected to the server 200, and more specifically, It may be a terminal owned by a manager who manages health.

The diabetes data collecting terminal 100 is connected to the server 200 via the Internet network. Thus, it is possible to prevent the diabetes data collecting terminal 100 The diabetes data collection terminal 100 and the server 200 will be described in more detail.

First, the diabetes data collecting terminal 100 is a portable terminal such as a smart phone or a tablet PC, or a computer, and has a user terminal form. The diabetes data collecting terminal 110 includes a diabetes data encrypting unit 120, a first diabetes data transmitting / A diabetic data decoding unit 140, a diabetic risk calculating unit 150, and an output unit 160. The diabolic data decoding unit 140,

In one embodiment of the present invention, the diabetes data collection terminal 100 will be described as an example of a smart phone-type portable terminal.

At this time, the diabetes data collection unit 110 collects diabetes data.

In one example, the diabetic data includes data related to the user information input to the diabetic data collection terminal 100 and measurement data that is a measurement value input from an external measurement device.

The data related to the user information in the diabetic data may be data input using an input unit (not shown) provided in the diabetes data collecting terminal 100. In this case, the input unit may be a touch input / output unit, which is the output unit 160, .

The data related to the user information is generated by the user directly inputting through the input unit, and the data related to the user information includes at least one of name, sex, key, weight, and blood type information.

In one example, the data related to the user information may be data input through a diabetes risk determination application, which is a program installed in the diabetes data collecting terminal 100, and may be data collected during the initial operation of the diabetes risk judgment application .

When the data related to the user information is inputted by driving the diabetes risk judgment application, it is preferable that the data related to the user information is inputted at the first time when the account is created through the membership registration procedure, and the key or the weight is corrected according to the change It should be possible.

At this time, the diabetes risk judgment application installed and driven in the diabetes data collecting terminal 100 may be provided when the diabetes data collecting terminal 100 is manufactured, or may be provided when the diabetes data collecting terminal 100 accesses the Internet, And can be provided.

As described above, the measurement data in the diabetic data are data received from external measuring instruments and used for measuring blood pressure, oxygen saturation, body weight, blood glucose, glycosylated hemoglobin (HbA1c), electrocardiogram, Or the like.

At this time, it is preferable that the activity amount is a consumed calorie value.

The external measuring device that generates the measurement data input to the diabetes data collecting terminal 100 may be a blood pressure monitor, an oxygen saturation measuring device, a weight meter, a blood glucose meter, a HbA1c analyzer, an electrocardiogram meter, a thermometer, and an activity amount collector.

In one example, the activity collection unit may be a gateway for collecting activity from activity sensors and calculating activity, and in one example, an activity hub.

At this time, the external measuring device may be a measuring device for measuring the body information used for calculating the diabetic state, but may use a measuring device other than the example of the measuring device provided.

The external measurement device that generates the measurement data and transmits the measurement data to the diabetes data collection terminal 100 uses the Internet of Things (IoT) to transmit the measurement data to the diabetes data collection terminal 100, (110).

More specifically, the first diabetes data transmitting / receiving unit 130 of the diabetes data collecting terminal 100, which is a wireless communication module, receives measurement data from an external measuring device that performs the object Internet and transmits the measurement data to the diabetes data collecting unit 110 .

In this case, in an example, when an external measuring device transmits measurement data through the Internet, the external measuring device can use Bluetooth, Zigbee, WiFi, or 6 LowPAN have.

The external measurement device may further include a wireless communication module corresponding to each object Internet protocol and thus the diabetes data collecting unit 100 of the diabetes data collecting terminal 100 The first diabetes data transmitting and receiving unit 130 may further include a wireless communication module corresponding to a wireless communication module of an external measuring device so that the first diabetes data transmitting and receiving unit 110 may communicate with an external measuring device.

As described above, the diabetes data collection unit 110 receives data and measurement data related to user information, collects the data and the measurement data as diabetes data, and transmits the collected data to the diabetes data encryption unit 120.

The diabetes data encryption unit 120 encrypts diabetes data received from the diabetes data collecting unit 110.

In one example, the diabetes data encryption unit 120 encrypts data and measurement data related to user information, which is diabetes data received from the diabetes data collection unit 110, using the Spritz encryption algorithm, To MD5 (Message Digest 5), which is a message hash algorithm.

As described above, the diabetes data encryption unit 120 encrypts the diabetes data using the Spritz encryption algorithm and performs an integrity check to detect forgery and tampering using the MD5 algorithm, thereby improving the security of diabetes data.

Since the first diabetes data transmitting and receiving unit 130 has a structure of connecting to the second diabetes data transmitting and receiving unit 210 of the server 200 through mobile communication or wireless communication as described above, The diabetes data encryption unit 120 encrypts and verifies the integrity of the diabetes data, and transmits the diabetes data to the second diabetes data transmission / reception unit 210.

The first diabetes data transmission / reception unit 130, which receives measurement data from an external measurement device or transmits the diabetes data, which is encrypted and integrity-checked in the diabetes data encryption unit 120, to the second diabetes data transmission / reception unit 210 And receives data stored in the server 200 from the second diabetes data transmission / reception unit 210 and transmits the data to the diabetes data decoding unit 140.

Since the data received by the diabetes data decoding unit 140 through the first diabetes data transmission and reception unit 130 is the data stored in the server 200 and is the encrypted and integrity-checked diabetes data, the diabetes data decoding unit 140 Performs an integrity check and a decryption process thereof.

At this time, the diabetes data, which is received and decrypted by the diabetes data decryption unit 140 from the second diabetes data transmission / reception unit 210, includes data related to user information, which is diabetes data of a user, and measurement data .

The diabetes data decryption unit 140 extracts the diabetes data by checking the integrity of the received diabetes data, which is encrypted and integrity-checked, and decrypting the data.

In one example, the diabetes data decryption unit 140 checks the integrity of the received diabetes data, which is encrypted and integrity-checked using the MD5 hash algorithm, and decrypts the diabetes data encrypted using the Spritz encryption algorithm.

As described above, the diabetes data decryption unit 140 stores the diabetes data, which is encrypted and integrity-checked by the diabetes data encryption unit 120, in the server 200, and transmits the diabetes data to the second diabetes data transmitting / receiving unit 210 and the first diabetes data transmission / The data stored in the server 200 is the encrypted and integrity-checked diabetic data by performing the integrity check and the decryption processing in the diabetes data decryption unit 140 through the authentication unit 130. In the diabetes data collection terminal 100, Or decrypts the encrypted diabetic data, and transmits the decrypted diabetic data to the diabetic risk calculation unit 150.

Therefore, the diabetes data stored in the server 200 is improved and the diabetes data is collected from the diabetes data collection terminal 100 to the server 200, since the diabetes data encrypted and checked for integrity is stored in the server 200. [ In data transmission and reception, data security is improved.

The diabetic risk calculator 150 receives the diabetic data decrypted from the diabetic data decryption unit 140 and calculates the risk of diabetes. The diabetic risk calculator 150 will be described in detail with reference to the flowchart of FIG.

Referring to FIG. 2, a method for calculating the diabetic risk through data security transmission according to an embodiment of the present invention will be described. First, in the data collection unit 110 of the diabetic risk data collection terminal 100, (S110).

The first diabetic data is the highest number of glycated hemoglobin among the body data measurements that are the basis for the calculation of diabetic risk.

In this case, the diabetic risk calculator 150 compares the collected first diabetes data with the HbA1c value of 5.7 (Q11). If the HbA1c value is greater than 5.7 (in the direction of the arrow NO in Q11), the glycated hemoglobin If the blood glucose level is greater than 5.7 and smaller than 6.5 (YES in Q12), the diabetes level is calculated as a warning level (S210).

At this time, if the HbA1c value is greater than 6.5 (arrow NO in Q12), the diabetic level is calculated as a danger level (S220).

If the glycated hemoglobin level is lower than 5.7 in the step Q11 of comparing the glycated hemoglobin level to 5.7 (YES in the direction of arrow Q11), the diabetic data collection unit 110 of the diabetic risk calculation apparatus collects the second diabetic data (S120).

The second diabetes data is the second highest blood glucose figure among the body data measurements that are the basis for calculating diabetes risk.

At this time, the diabetic risk calculator 150 compares the collected second diabetes data, for example, the fasting plasma glucose (FPG) value to 100 (Q21), and if the fasting blood glucose level is greater than or equal to 100 (In the direction of the arrow NO in Q21), the fasting blood glucose level is again compared with 126 (Q22), and the diabetes level warning step is performed when the fasting blood glucose level is lower than 126 (YES in the case of Q22) (S211).

At this time, if the fasting blood glucose level is equal to or greater than 126 (arrow NO in Q22), the diabetic level is calculated as a danger level (S221).

If the fasting blood glucose level is less than 100 (YES in the arrow Q21), the diabetes data collection unit 110 collects the third diabetes data (S130).

The third diabetes data are information on hyperglycemia, BMI index, random blood glucose value, age, blood pressure, and family history, which are data for the calculation of diabetic risk, and are calculated in order according to their priorities.

Accordingly, when the third diabetes data is collected (S130), the diabetes risk calculator 150 calculates whether hyperglycemia is present (Q31). If it is not hyperglycemia (Q32). If the random blood glucose value is greater than or equal to 200 (in the direction of the arrow NO in Q32), the diabetes level warning step is performed (step S232) , And the diabetic level is calculated as a danger level (S222).

In the hyperglycemia calculation step (Q31), the BMI index is compared with 25 (Q41) when the hyperglycemia is not hyperglycemia (in the direction of arrow NO in Q31) (S230). If the BMI index is equal to or larger than 25 (the direction of arrow NO in Q41), the process proceeds to the age comparison step Q51.

At this time, in the age comparison step (Q51), the age is compared with 45, and if the age is greater than or equal to 45 (arrow NO in Q51), the diabetes level is calculated as a danger level (S221) YES in arrow Q51), the flow advances to the blood pressure comparison step Q61.

In the blood pressure comparison step Q61, the blood pressure is 140/90, that is, the systolic blood pressure is 140, and the diastolic blood pressure is 90. When the blood pressure is greater than or equal to 140/90 (arrow NO direction of Q61) (S213). If the blood pressure is lower than 140/90 (YES in the arrow of Q61), the family history comparing step (Q71) is performed.

In this case, in the family history comparing step (Q71), the diabetic condition of the immediate family member is calculated. If the family member has experienced the diabetic condition (YES in Q71), the diabetic member is calculated as the diabetic level warning step (S213) If no person experiences a diabetes mellitus (arrow NO in Q71), the diabetic level is calculated as a normal level (S230).

Since the diabetic risk calculating unit 150 calculates the degree of diabetic risk using the diabetic risk calculating method described with reference to FIG. 2, the diabetic data collecting terminal 100 having the diabetic risk calculating unit 150, In the diabetic risk calculation system based on the data security transmission of the present invention having the server 200 receiving the degree of diabetes data and diabetes risk, the patient having the diabetic data collection terminal 100 easily calculates the degree of risk of diabetes The self-diagnosis can be easily carried out.

In this case, the body data used to calculate the risk of diabetes include blood pressure, oxygen saturation, body weight, blood sugar, glycated hemoglobin, electrocardiogram, body temperature, family history, etc., Therefore, it is possible to solve the conventional problems of the diabetic patients using the blood glucose meter to calculate the risk of diabetes using only the blood glucose measurement value.

2, the diabetic risk calculating unit 150 calculates the diabetic risk level, that is, the result of any one of the diabetic normal level, the warning level, and the risk level to the first diabetic data transmission / reception To the second diabetes data transmission / reception unit 210 of the server 200 through the first diabetes data transmission /

In this case, the degree of diabetes risk calculated by the diabetes risk calculator 150 is transmitted to the second diabetes data transmitting and receiving unit 210 of the server 200 through the first diabetes data transmitting and receiving unit 130, The encryption unit 120 encrypts and verifies the degree of risk of diabetes and sends it to the server 200. [

The output unit 160 of the diabetes data collecting terminal 100 may be a touch input / output unit or a display device formed in the diabetes data collecting terminal 100 and may output the diabetes data collected by the diabetes data collecting unit 110 in real time , And outputs the diabetic risk degree calculation result of the diabetic risk calculation unit 150.

In addition, the output unit 140 outputs data according to the operation of the diabetes risk determination application installed in the diabetes data collecting terminal 100.

The diabetes data collecting terminal 100 includes the diabetes data collecting unit 110, the diabetes data encrypting unit 120, the first diabetes data transmitting and receiving unit 130, the diabetes data decoding unit 140, the diabetes risk calculating unit 150 ) And an output unit 160. The data and measurement data related to user information, which is diabetes data of a user using the diabetes data collecting terminal 100, are generated and encrypted, And transmits the data to the server 200 of the server 200 or calculates the degree of danger of diabetes and transmits the data to the server 200. Thus, the risk of hacking that may occur in data transmission can be prevented.

Referring to FIG. 1, the server 200 receives the encrypted diabetes data and diabetes risk information from the diabetes data collecting terminal 100. The server 200 includes a second diabetes data transmitting / receiving unit 210, And a database unit 220.

The server 200 may be formed as a computer or a server remotely located from the diabetes data collecting terminal 100 and the second diabetes data transmitting and receiving unit 210 may be formed of a diabetes data transmitting / Receiving the diabetes data subjected to the encryption and integrity checking from the first diabetes data transmitting and receiving unit 130 of the collecting terminal 100 and storing the same in the database unit 220, And transmits the integrity-checked diabetes data to the outside.

At this time, when the second diabetes data transmission / reception unit 210 transmits the diabetes data that is stored in the database unit 220 to the outside, the device for requesting and receiving the diabetes data may be the diabetes data collection terminal 100 In one example, the diabetic data collecting terminal 100 may be a diabetic data collecting terminal 100 having a patient and generating diabetic data of the patient. However, the diabetic data collecting terminal 100 may be a manager managing the patient's health, But is not limited thereto.

The second diabetes data transmission / reception unit 210 stores the degree of diabetes risk, which is received from the first diabetes data transmission / reception unit 130, in the database unit 220, and transmits the degree of diabetes risk to the database unit 220 It is possible.

At this time, the related data stored in the database unit 220 for receiving and storing the diabetes data or the degree of diabetes risk, which is encrypted and checked for integrity according to the operation of the second diabetes data transmission / reception unit 210, is decrypted, And is stored in the inspected state, thereby improving the security of the diabetes-related data of the patient stored in the server 200. [

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments, It belongs to the scope of right.

100: diabetes data collection terminal 110: diabetes data collection unit
120: diabetes data encryption unit 130: first diabetes data transmission /
140: diabetes data decoding unit 150: diabetes risk calculation unit
160: output unit 200: server
210: second diabetic transmission / reception unit 220:

Claims (8)

A diabetes data collection unit for receiving a plurality of the measurement data from a plurality of measurement devices measuring body data and outputting the measurement data as measurement data or receiving data related to user information,
A diabetic risk calculator for calculating the degree of diabetic risk using the diabetic data as normal,
A diabetes data encryption unit for receiving diabetes data including data related to the measurement data and the user information from the diabetes data collection unit and encrypting the received data with the Spritz cipher algorithm and the MD5 to check integrity of the diabetes data;
A first diabetes data transmission / reception unit for externally transmitting the degree of diabetes data or the degree of diabetes risk,
A diabetes data collecting terminal,
And a second diabetes data transmission / reception unit for receiving the encrypted and integrity-checked diabetes data or degree of diabetes risk transmitted from the first diabetes data transmission /
Wherein the diabetic risk calculation system comprises: The method according to claim 1,
Wherein the body data collected by the diabetes data collection unit as the measurement data includes at least two of blood pressure, oxygen saturation, body weight, fasting blood glucose, random blood glucose, glycated hemoglobin, electrocardiogram and body temperature. system. 3. The method of claim 2,
The diabetic risk calculator calculates,
If the glycated hemoglobin is greater than or equal to 6.5, the diabetic level is calculated as a danger level. If the glycated hemoglobin is greater than or equal to 5.7 and less than 6.5,
The fasting blood glucose level is calculated as 100. If the fasting blood glucose level is greater than or equal to 100 and less than 126 at the same time, it is calculated as the diabetic level warning step. If the fasting blood glucose level is greater than or equal to 126, Respectively,
Wherein the diabetic level is calculated as a warning level when the patient has a hyperglycemia when the random blood glucose level is less than 200, and the diabetic level is calculated as the danger level when the random blood glucose level is equal to or greater than 200. Risk calculation system. The method of claim 1,
Wherein the diabetes data collection unit receives a plurality of the body data from the plurality of measurement devices via Bluetooth, Zigbee, Wi-Fi or 6 LowPAN. 4. The method of claim 3,
Wherein the diabetic risk calculator calculates a diabetic risk by applying a first priority to the glycated hemoglobin and a second priority to the fasting blood glucose among the plurality of the measurement data measured values, system. The method of claim 3,
The diabetic risk calculator calculates,
If the patient is not hyperglycemic, the BMI index is compared to 25, and when the BMI is less than 25, the diabetic level is calculated as normal,
Wherein the BMI is greater than or equal to 25 and the age is 45 or greater and the age is greater than or equal to 45, the diabetic level is calculated as a risk level. The method according to claim 6,
The diabetic risk calculator calculates,
Wherein the diabetic level is calculated as a diabetic level warning step when the blood pressure is 140/90 or more and the blood pressure is equal to or greater than 140/90 when the age is less than 45 or less. 8. The method of claim 7,
Calculating the family history of the patient's diabetes when the blood pressure is less than 140/90, calculating the diabetes level warning step if the patient has a family history, and calculating the normal level of the diabetes level if the patient has no family history Wherein the diabetic risk calculation system comprises:
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109276258A (en) * 2018-08-10 2019-01-29 北京大学深圳研究生院 Blood glucose trend forecasting method, system and Medical Devices based on DTW
KR20210004993A (en) * 2018-04-23 2021-01-13 메드트로닉 미니메드 인코포레이티드 Personalized closed loop drug delivery system using patient's digital twin
WO2022114793A1 (en) * 2020-11-26 2022-06-02 가톨릭대학교 산학협력단 Big data-based system, method, and program for predicting risk for diabetes incidence

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20210004993A (en) * 2018-04-23 2021-01-13 메드트로닉 미니메드 인코포레이티드 Personalized closed loop drug delivery system using patient's digital twin
CN109276258A (en) * 2018-08-10 2019-01-29 北京大学深圳研究生院 Blood glucose trend forecasting method, system and Medical Devices based on DTW
CN109276258B (en) * 2018-08-10 2021-08-03 北京大学深圳研究生院 DTW-based blood glucose trend prediction method and system and medical equipment
WO2022114793A1 (en) * 2020-11-26 2022-06-02 가톨릭대학교 산학협력단 Big data-based system, method, and program for predicting risk for diabetes incidence
KR20220075049A (en) 2020-11-26 2022-06-07 가톨릭대학교 산학협력단 System for providing diabetes disease risk prediction based on bigdata, method, and program for the same
KR20230166054A (en) 2020-11-26 2023-12-06 가톨릭대학교 산학협력단 Diabetes development risk prediction system using deep learning model, method, and program

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