CN110600128A - Blood sugar management system for insulin dependent diabetes mellitus patient and use method - Google Patents

Abstract

The invention relates to a blood sugar management system for "insulin-dependent" diabetic patients, comprising: a cloud server, a data acquisition device and a mobile terminal; the data acquisition device is communicated and connected with the cloud server, and can collect the first physiological parameters of the patients. The state data is sent to the cloud server; the cloud server is connected in communication with the mobile terminal; the mobile terminal can input the second physiological state data of the patient and the patient's personal information, and send the second physiological state data and the patient's personal information to the cloud server; the cloud server can A matching treatment plan is recommended according to the received first and second physiological state data of the patient and the patient's personal information, and the treatment plan is sent to the mobile terminal; the mobile terminal can display the treatment plan to the doctor or patient. The blood sugar management system provided by the invention can monitor and control the blood sugar condition of the patient in real time, and recommend the optimal blood sugar management.

Description

Blood sugar management system and method of use for "insulin-dependent" diabetic patients

technical field

The invention belongs to the technical field of diabetes medical treatment, and in particular relates to a blood sugar management system and a using method for "insulin-dependent" diabetic patients.

Background technique

"Insulin-dependent" diabetes refers to a type of diabetes in which the insulin secreted by the pancreatic β cells of the patient is very small, which is difficult to meet the needs of the human body, and must rely on subcutaneous insulin injection to maintain the blood sugar concentration at a normal level. For this type of diabetes, insulin doses need to be strictly controlled to avoid hypoglycemia and hyperglycemia. Hyperglycemia can cause long-term complications such as retinopathy, neuropathy, and cardiovascular disease. Hypoglycemia can quickly lead to conditions such as hypoglycemic coma, neurological symptoms, and nocturnal hypoglycemia that endanger the life of patients. Therefore, for "insulin-dependent" diabetic patients, a blood sugar management system that can monitor and control their blood sugar in real time is very necessary.

SUMMARY OF THE INVENTION

(1) Technical problems to be solved

In view of the existing technical problems, the present invention provides a blood sugar management system and a method for using it for "insulin-dependent" diabetic patients.

(2) Technical solutions

In order to achieve the above-mentioned purpose, the main technical scheme adopted in the present invention includes:

A blood sugar management system for "insulin-dependent" diabetic patients, comprising: a cloud server, a data acquisition device and a mobile terminal;

The data collection device is connected in communication with the cloud server, and can send the collected first physiological state data of the patient to the cloud server;

the cloud server is in communication connection with the mobile terminal;

The mobile terminal can input the second physiological state data and the patient's personal information of the patient, and send the second physiological state data and the patient's personal information to the cloud server;

The cloud server can recommend a matching treatment plan according to the received first physiological state data, the second physiological state data and the patient's personal information, and send the treatment plan to the mobile terminal;

The mobile terminal can display the treatment plan to the doctor or patient;

The second physiological state data includes at least: whether the patient is sleeping, whether the patient is exercising, and whether the patient is eating;

The patient's personal information data at least includes: name, gender, age, weight, and insulin dosage before treatment with the pump.

Preferably, the data acquisition device includes at least a continuous blood glucose monitor;

The continuous blood glucose monitor can collect data on the blood glucose level of the patient.

Preferably, the cloud server includes: a processor and a memory, and a plurality of instruction sets stored in the memory;

The plurality of instruction sets are executed by the processor and the data acquisition device.

Preferably, the multiple instruction sets include: a blood glucose collection instruction set, a physiological state instruction set, an insulin administration instruction set, and a data display instruction set.

Preferably, the number of the mobile terminals is multiple;

The mobile terminal is a patient terminal and/or a doctor terminal.

The technical solution also provides a method for using a blood sugar management system for "insulin-dependent" diabetic patients, comprising the following steps:

S1. The data collection device sends the collected blood glucose level data of the patient to a cloud server;

S2, the cloud server performs soft measurement according to the received blood glucose value data of the patient, and obtains a soft measurement value, and the cloud server judges whether the data acquisition device fails through the sensor fault detection rule, the patient blood glucose value data and the soft measurement value;

If so, execute S3;

If not, execute S4;

S3, perform data reconstruction, that is, replace the received blood glucose level data of the patient with the soft measurement value, and store it in the cloud server;

S4. Store the received blood glucose level data of the patient in the cloud server.

Preferably, the step S3 further includes: the cloud server sends the fault type obtained based on the judgment and the preset experience-based fault solution method to the mobile terminal, so as to be displayed to the patient or doctor;

The failure types include at least one or more of: data loss, spikes, drift, stagnation, pressure-induced sensor attenuation, and bias.

Preferably, the method further includes:

When the patient is in the eating state, the meal information is manually input by means of the patient's mobile terminal;

If the patient forgets to input, the cloud server identifies the eating state through the stored blood glucose level data and the preset fuzzy logic algorithm, and generates a second physiological state label in the eating state for the identified eating state;

If the patient completes the manual input, the cloud server generates a second physiological state label in the eating state according to the manually input eating information;

The generated second physiological state label of the patient is stored in the cloud server and/or sent to the mobile terminal for displaying to the patient or doctor.

Preferably, the method further includes:

A1. The cloud server provides a medication strategy model suitable for the patient according to the received blood glucose level data of the patient, the patient's physiological state label and the pre-stored medication strategy

Wherein, the patient's physiological state label includes at least a second patient's physiological state label;

A2. Input the patient's current blood glucose value into the medication strategy model to obtain the insulin dose;

A3. Display the obtained dose to the patient or doctor by means of a mobile terminal.

Preferably, the step A2 further includes the following sub-steps:

A201. Use a prediction algorithm to predict the predicted blood glucose value after 30 minutes according to the current blood glucose value, and then store the predicted blood glucose value in the cloud server;

A202. Calculate and obtain the insulin dose according to the current blood glucose value, the predicted blood glucose value, the current blood glucose change rate, the current physiological state and the state label in the cloud server;

A203. Save the insulin administration dose to the cloud server.

(3) Beneficial effects

The beneficial effects of the present invention are as follows: a blood glucose management system and a method of use for "insulin-dependent" diabetic patients provided by the present invention have the following beneficial effects:

Using the system provided by the present invention enables patients to see their current blood sugar level, predicted value after 30 minutes, insulin dosage, low blood sugar early warning and whether the sensor is faulty. Doctors can see the situation of all patients within their jurisdiction, and if there is an abnormal situation, they can help the patient return to a normal state based on experience in a timely manner.

The system can also effectively reduce the occurrence of hyper/hypoglycemia and increase the time when the patient is in normal blood sugar fluctuations.

Description of drawings

1 is a schematic diagram of the system structure in a blood sugar management system for "insulin-dependent" diabetic patients and a method of use provided by the present invention;

2 is a schematic diagram of the workflow of a blood sugar collection device in a blood sugar management system and a method of use for "insulin-dependent" diabetic patients provided by the present invention;

3 is a schematic diagram of the workflow of physiological state input in a blood glucose management system for "insulin-dependent" diabetic patients and a method of use provided by the present invention;

4 is a schematic diagram of the workflow of insulin administration in a blood sugar management system for "insulin-dependent" diabetic patients and a method of use provided by the present invention;

FIG. 5 is a schematic diagram of data display information in a blood sugar management system for "insulin-dependent" diabetic patients and a method of use provided by the present invention.

Detailed ways

In order to better explain the present invention and facilitate understanding, the present invention will be described in detail below with reference to the accompanying drawings and through specific embodiments.

As shown in FIG. 1 : this embodiment discloses a blood glucose management system for "insulin-dependent" diabetic patients, including: a cloud server, a data acquisition device and a mobile terminal;

The data collection device is connected in communication with the cloud server, and can send the collected first physiological state data of the patient to the cloud server.

The cloud server is connected in communication with the mobile terminal.

The mobile terminal can input the second physiological state data and the patient's personal information of the patient, and send the second physiological state data and the patient's personal information to the cloud server.

The cloud server can recommend a matching treatment plan according to the received first physiological state data, the second physiological state data and the patient's personal information, and send the treatment plan to the mobile terminal.

It should be noted that: the treatment plan described in this embodiment is a treatment plan in the cloud server based on the expert rule preset value, and the cloud server can receive the first physiological state data, the second physiological state data and the patient's personal information according to the received treatment plan. Combine the preset treatment plan and recommend suitable treatment plan for the patient or doctor with the help of mobile terminal.

The mobile terminal can display the treatment plan to the doctor or patient.

The second physiological state data includes at least: whether the patient is sleeping, whether the patient is exercising, and whether the patient is eating;

The patient's personal information data at least includes: name, gender, age, weight, and insulin dosage before treatment with the pump.

It should be noted here that the personal information data described in this embodiment includes, but is not limited to, gender, age, weight, insulin dosage before pump treatment, activity status, such as meals, exercise, what meals you eat, participation in What sports etc.

The data acquisition device described in this embodiment includes at least a continuous blood glucose monitor.

The continuous blood glucose monitor can collect blood glucose level data of a patient.

The cloud server described in this embodiment includes: a processor, a memory, and multiple instruction sets stored in the memory.

The plurality of instruction sets are executed by the processor and the data acquisition device.

The multiple instruction sets in this embodiment include: a blood glucose collection instruction set, a physiological state instruction set, an insulin administration instruction set, and a data display instruction set.

The physiological state instruction set described here at least includes: an instruction set for inputting the second physiological state and an instruction set for generating a physiological state label.

In this embodiment, the number of mobile terminals is multiple.

The mobile terminal is a patient terminal and/or a doctor terminal.

It should be noted here that this embodiment also provides a method for using a blood glucose management system for "insulin-dependent" diabetic patients based on the system in the above embodiment, including the following steps:

S1. The data collection device sends the collected blood glucose level data of the patient to a cloud server;

S2, the cloud server performs soft measurement according to the received blood glucose value data of the patient, and obtains a soft measurement value, and the cloud server judges whether the data acquisition device fails through the sensor fault detection rule, the patient blood glucose value data and the soft measurement value;

If so, execute S3;

If not, execute S4;

S3, perform data reconstruction, replace the received blood glucose level data of the patient with the soft measurement value, and store it in the cloud server;

S4. Store the received blood glucose level data of the patient in the cloud server.

The step S3 in this embodiment further includes: the cloud server sends the fault type obtained based on the judgment and the preset experience-based fault solution method to the mobile terminal, so as to be displayed to the patient or doctor.

Finally, it should be noted that the failure types include at least one or more of: data loss, spikes, drift, stagnation, pressure-induced sensor attenuation and deviation.

The method in this embodiment also includes:

When the patient is in the eating state, the meal information is manually input by means of the patient's mobile terminal;

If the patient forgets to input, the cloud server identifies the eating state through the stored blood glucose level data and the preset fuzzy logic algorithm, and generates a second physiological state label in the eating state for the identified eating state;

If the patient completes the manual input, the cloud server generates a second physiological state label in the eating state according to the manually input eating information;

The generated second physiological state label of the patient is stored in the cloud server and/or sent to the mobile terminal for displaying to the patient or doctor.

The method described in this embodiment also includes:

A1. The cloud server provides a medication strategy model suitable for the patient according to the received blood glucose level data of the patient, the patient's physiological state label and the pre-stored medication strategy;

Wherein, the patient's physiological state label includes at least a second patient's physiological state label.

A2. Input the patient's current blood glucose value into the medication strategy model to obtain the insulin dose;

A3. Display the obtained dose to the patient or doctor by means of a mobile terminal.

Step A2 described in this embodiment also includes the following sub-steps:

A201. Use a prediction algorithm to predict the predicted blood glucose value after 30 minutes according to the current blood glucose value, and then store the predicted blood glucose value in the cloud server;

A202. Calculate and obtain the insulin dose according to the current blood glucose value, the predicted blood glucose value, the current blood glucose change rate, and the current patient's physiological state label in the cloud server;

A203. Save the insulin administration dose to the cloud server.

The system of the invention is composed of a data acquisition device, a physiological state input module, an insulin administration module, a data processing module, a data display module, a cloud server and a plurality of mobile terminals.

The data acquisition device includes at least: a continuous blood glucose monitor;

The physiological state input module: the second physiological state data at least includes whether the patient is in a sleeping state, whether the patient is in an exercising state, and whether the patient is in a eating state;

The insulin dosing module: collects diabetes drug strategies to formulate an expert rule base, gives calculation rules for large doses and basal doses, and formulates different dosing strategies according to the label classification in the cloud server. In the dosing strategy, the blood glucose value data in the cloud server is first extracted, and the dosing strategy can be directly obtained according to the expert rules and labels without the predicted blood glucose value, and the insulin dose can be calculated. When the predicted blood sugar level can be calculated, the blood sugar level data is used as the input of the prediction algorithm, the blood sugar level after 30 minutes is obtained, and the predicted value data is stored in the cloud server. Finally, the insulin dose is calculated according to the current blood glucose value, the predicted blood glucose value, the current blood glucose change rate, the current physiological state and the refined label.

The data processing module is connected to the cloud server, and mainly provides the main calculation methods for the above modules:

According to the sensor fault detection and diagnosis method, it can be obtained whether the sensor has abnormal conditions and fault types.

If the patient does not input meal information, a control algorithm is used to identify whether the patient is in a meal state.

According to the blood sugar level of the patient stored in the cloud server, the predicted blood sugar level after 30 minutes is obtained by the prediction algorithm, which can not only provide help for the insulin administration strategy, but also give the patient an early warning system for hypoglycemia.

Dosing strategies based on expert rules are divided into two cases: no predicted blood glucose value and one with predicted blood glucose value. In the case of no predicted blood glucose value, the insulin dose is obtained by inference based on expert rules using the current blood glucose value and information stored in the cloud server. When there is a predicted blood sugar value, the insulin dose is calculated according to the current blood sugar, the predicted blood sugar, the current blood sugar change rate, the current physiological state, and the refined label.

The data display module: extracts the useful information of the patient from the cloud server and transfers it to multiple mobile terminals, which can provide the current blood glucose value of the patient, the predicted value of blood glucose after 30 minutes, the dosage of insulin administration, and the low blood sugar warning for multiple mobile terminals. and sensor fault diagnosis results, among which the cloud server can provide experience-based fault solutions for the fault diagnosis results.

The cloud server includes at least a cloud storage module and a cloud computing module.

The mobile terminal at least includes a patient client used by patients and a doctor monitoring terminal used by doctors. The patient client needs the patient to enter his own personal information and second physiological state data and can at least see his current blood glucose value, predicted blood glucose value, insulin dosage, low blood sugar warning and advice, sensor failure types and solutions The doctor's monitoring terminal can see the situation of all patients in the area under its jurisdiction. When the patient has low blood sugar or the sensor fails, the doctor can remind the patient in time.

Blood glucose collection module

As shown in Figure 2: a schematic diagram of the workflow of the blood glucose collection device in this embodiment, which specifically includes the following steps:

S1. Use a data acquisition device to measure a plurality of physiological data of the patient, and then upload the data.

S2. The cloud server receives the uploaded data and performs soft measurement. Among them, soft measurement refers to the use of one-step prediction method to predict the blood glucose level of the patient after 5 minutes.

S3. Use the sensor failure detection method to determine whether the sensor device fails.

If so, execute S4;

If not, execute S6;

S4. Use the fault diagnosis method to determine the fault type of the abnormal equipment. The fault type at least includes data loss, spike, drift, stagnation, sensor attenuation and deviation caused by pressure.

S5. Display the experience-based fault solution method on the mobile terminal based on the fault type, and then perform data reconstruction, that is, replace the measured value with the soft measurement value to reconstruct the data measured by the continuous blood glucose monitor and store it in the cloud server.

S6. Store the personal information entered by the patient and the blood glucose information collected by the sensor in the cloud server.

Physiological state entry module

As shown in Figure 3 : a schematic diagram of the physiological state entry workflow in this embodiment, including the following steps:

When the patient is in the eating state, the meal information is manually input by means of the patient's mobile terminal;

If the patient forgets to input, the cloud server identifies the eating state through the stored blood glucose level data and the preset fuzzy logic algorithm, and generates a second physiological state label in the eating state for the identified eating state;

If the patient completes the manual input, the cloud server generates a second physiological state label in the eating state according to the manually input eating information;

The generated second physiological state label of the patient is stored in the cloud server and/or sent to the mobile terminal for displaying to the patient or doctor.

Insulin Administration Module

As shown in Figure 4: In this example, the insulin administration workflow is schematic, including the following steps:

S1. Extract the patient's blood glucose level information and the patient's personal information in the cloud server.

S2. Collect diabetes drug strategies to formulate an expert rule base, give calculation rules for large doses and basic doses, and formulate different drug delivery strategies according to the label classification in the cloud server.

If the current system can provide the predicted blood glucose value, execute S3;

If the current system cannot provide the predicted blood glucose value, execute S4;

S3. Input the current blood glucose value into the expert rule to give the dosage.

S4. Use a prediction algorithm to predict the blood sugar level after 30 minutes according to the current blood sugar level, and then store the predicted blood sugar level in the cloud server.

S5. Calculate the insulin dose according to the current blood glucose value, the predicted blood glucose value, the current blood glucose change rate, the current physiological state, and the refined label in the cloud server.

S6. Save the insulin dose to the cloud server.

data display module

As shown in Figure 5: the data display information in this embodiment is shown; in addition, the blood glucose value, insulin injection amount and low blood sugar warning after 30 minutes are stored in the cloud server in the insulin administration module.

Finally, it should be noted that the system workflow in this embodiment may be:

S1. The patient inputs the second physiological state data and the patient's personal information, and collects the first physiological state data of the patient through the data acquisition device.

S2. Save all data and information of the patient to the cloud server.

S3. Determine whether the continuous blood glucose monitor is faulty, and if there is a fault, reconstruct the data of the continuous blood glucose monitor and save it to the cloud, and give the patient's experience-based adjustment advice.

S4 , formulating an insulin administration strategy according to the second physiological state label using expert rule reasoning and the presence/absence of blood glucose prediction values.

S5, formulate a blood sugar early warning function according to the current blood sugar value, the blood sugar predicted value and the blood sugar change trend.

The technical principles of the present invention have been described above with reference to specific embodiments. These descriptions are only for explaining the principles of the present invention, and cannot be interpreted as limiting the protection scope of the present invention in any way. Based on the explanations herein, those skilled in the art can think of other specific embodiments of the present invention without creative efforts, and these methods will all fall within the protection scope of the present invention.

Claims (10)

1. An insulin-dependent diabetes patient oriented blood glucose management system comprising: the system comprises a cloud server, a data acquisition device and a mobile terminal;

the data acquisition device is in communication connection with the cloud server and can send acquired first physiological state data of the patient to the cloud server;

the cloud server is in communication connection with the mobile terminal;

the mobile terminal can input second physiological state data and patient personal information of a patient and send the second physiological state data and the patient personal information to the cloud server;

the cloud server can recommend a matched treatment scheme according to the received first physiological state data, the second physiological state data and the personal information of the patient, and send the treatment scheme to the mobile terminal;

the mobile terminal can show a treatment scheme to a doctor or a patient;

the second physiological state data includes at least: whether the patient is in a sleeping state, whether the patient is in a moving state, and whether the patient is in a eating state;

the patient personal information data includes at least: name, sex, age, weight, insulin dose before treatment with the pump.

2. The system of claim 1,

the data acquisition device at least comprises a continuous blood glucose monitor;

the continuous glucose monitor is capable of collecting patient blood glucose value data.

3. The system of claim 2,

the cloud server includes: a processor and a memory, and a plurality of instruction sets stored in the memory;

the plurality of instruction sets are executed by the processor and the data acquisition device.

4. The system of claim 3,

the plurality of instruction sets includes: the blood glucose monitoring system comprises a blood glucose collection instruction set, a physiological state instruction set, an insulin administration instruction set and a data display instruction set.

5. The system of claim 1,

the number of the mobile terminals is multiple;

the mobile terminal is a patient terminal and/or a doctor terminal.

6. A method for using a blood sugar management system for an insulin-dependent diabetic patient is characterized by comprising the following steps:

s1, the data acquisition device sends the acquired blood sugar value data of the patient to a cloud server;

s2, the cloud server performs soft measurement according to the received patient blood sugar value data to obtain a soft measurement value, and the cloud server judges whether the data acquisition device fails according to the sensor fault detection rule, the patient blood sugar value data and the soft measurement value;

if yes, go to S3;

if not, go to S4;

s3, reconstructing data, namely replacing the received blood glucose value data of the patient with a soft measurement value, and storing the data in a cloud server;

and S4, storing the received blood sugar value data of the patient in a cloud server.

7. The method according to claim 6, wherein the step S3 further comprises: the cloud server sends the fault type obtained based on the judgment and a preset fault solution based on experience to the mobile terminal for displaying to a patient or a doctor;

the fault types include at least: data loss, spikes, drift, stagnation, pressure induced sensor decay and bias.

8. The method of claim 6, further comprising:

manually inputting eating information by a patient with the aid of the mobile terminal of the patient in a eating state;

if the patient forgets to input the information, the cloud server identifies the eating state through the stored blood sugar value data and a preset fuzzy logic algorithm, and generates a second physiological state label in the eating state according to the identified eating state;

if the patient completes manual input, the cloud server generates a second physiological state label in a eating state according to the manually input eating information;

the generated second physiological state label of the patient is stored in the cloud server and/or sent to the mobile terminal for being displayed to the patient or the doctor.

9. The method of claim 8,

the method further comprises the following steps:

a1, the cloud server gives a medication strategy model adapted to the patient according to the received blood sugar value data of the patient, the physiological state label of the patient and a pre-stored medication strategy;

wherein the patient physiological state label comprises at least a patient second physiological state label;

a2, inputting the current blood sugar value of the patient into a medication strategy model to obtain the insulin administration dose;

a3, displaying the obtained administration dose to a patient or a doctor by means of a mobile terminal.

10. The method according to claim 9, wherein said step a2 further comprises the sub-steps of:

a201, predicting a predicted blood sugar value after 30 minutes according to the current blood sugar value by using a prediction algorithm, and then storing the predicted blood sugar value into a cloud server;

a202, calculating to obtain an insulin administration dosage according to a current blood sugar value, a predicted blood sugar value, a current blood sugar change rate and a current physiological state label in a cloud server;

and A203, storing the insulin administration dose into a cloud server.