CN110600128A - Blood sugar management system for insulin dependent diabetes mellitus patient and use method - Google Patents
Blood sugar management system for insulin dependent diabetes mellitus patient and use method Download PDFInfo
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- CN110600128A CN110600128A CN201910907634.8A CN201910907634A CN110600128A CN 110600128 A CN110600128 A CN 110600128A CN 201910907634 A CN201910907634 A CN 201910907634A CN 110600128 A CN110600128 A CN 110600128A
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
- G16H40/67—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H70/00—ICT specially adapted for the handling or processing of medical references
- G16H70/40—ICT specially adapted for the handling or processing of medical references relating to drugs, e.g. their side effects or intended usage
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H80/00—ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
Abstract
The invention relates to a blood sugar management system for 'insulin dependent' diabetes patients, 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 the 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 the 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 present the treatment plan to a doctor or a patient. The blood sugar management system provided by the invention can monitor and control the blood sugar condition of a patient in real time and recommend the optimal blood sugar management.
Description
Technical Field
The invention belongs to the technical field of diabetes medical treatment, and particularly relates to a blood sugar management system for an insulin-dependent diabetes patient and a using method thereof.
Background
"insulin-dependent" diabetes refers to diabetes in which the beta cells of the islets of langerhans in the body secrete very little insulin, which is difficult to meet the needs of the human body, and subcutaneous insulin injection is needed to maintain the blood sugar concentration at a normal level. For such diabetes, the injected dose of insulin needs to be tightly controlled to avoid hypoglycemic and hyperglycemic conditions. Hyperglycemia causes long-term complications such as retinopathy, neuropathy, and cardiovascular disease. Hypoglycemia can rapidly result in such things as: hypoglycemia coma, nervous symptoms, nighttime hypoglycemia and the like which are harmful to the life safety of patients. Therefore, a blood glucose management system that can monitor and control the blood glucose level of an "insulin-dependent" diabetic patient in real time is very necessary.
Disclosure of Invention
Technical problem to be solved
Aiming at the existing technical problems, the invention provides a blood sugar management system for an insulin-dependent diabetic patient and a using method thereof.
(II) technical scheme
In order to achieve the purpose, the invention adopts the main technical scheme that:
an "insulin-dependent" diabetic-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.
Preferably, the data acquisition device comprises at least a continuous blood glucose monitor;
the continuous glucose monitor is capable of collecting patient blood glucose value data.
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 plurality of instruction sets comprises: 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.
Preferably, the number of the mobile terminals is multiple;
the mobile terminal is a patient terminal and/or a doctor terminal.
The technical scheme also provides a use method of the blood sugar management system for the 'insulin dependent' diabetic, which comprises 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.
Preferably, the step S3 further includes: 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.
Preferably, the method further comprises:
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.
Preferably, the method further comprises:
a1, the cloud server gives out 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 the 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.
Preferably, the step a2 further includes the following sub-steps:
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, a current physiological state and a state label in a cloud server;
and A203, storing the insulin administration dose into a cloud server.
(III) advantageous effects
The invention has the beneficial effects that: the invention provides a blood sugar management system for 'insulin dependent' diabetes mellitus patients and a using method thereof, which have the following beneficial effects:
the system provided by the invention can enable the patient to see the current blood sugar value, the predicted value after 30 minutes, the insulin administration amount, the hypoglycemia early warning and whether the sensor has a fault or not. The doctor can see the condition of all patients in the own jurisdiction, and if abnormal conditions occur, the doctor can help the patients to recover to a normal state based on experience in time.
The system can also effectively reduce the occurrence frequency of hyperglycemia and hypoglycemia, and increase the normal blood sugar fluctuation time of the patient.
Drawings
FIG. 1 is a schematic structural diagram of a system for managing blood sugar of an "insulin-dependent" diabetic and a method for using the same according to the present invention;
FIG. 2 is a schematic view of the working flow of the blood sugar collecting device in the blood sugar management system and the use method for the "insulin dependent" diabetic of the present invention;
FIG. 3 is a schematic view of a workflow of physiological status entry in an "insulin dependent" diabetic-oriented blood glucose management system and a method of use thereof according to the present invention;
FIG. 4 is a schematic view of the working flow of insulin administration in the blood sugar management system and the use method for the "insulin dependent" diabetic of the present invention;
FIG. 5 is a schematic diagram of data display information in the blood glucose management system and the method for the "insulin dependent" diabetic of the present invention.
Detailed Description
For the purpose of better explaining the present invention and to facilitate understanding, the present invention will be described in detail by way of specific embodiments with reference to the accompanying drawings.
As shown in fig. 1: the embodiment discloses a blood sugar management system for 'insulin dependent' diabetes patients, which comprises: 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 enter 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 sends the treatment scheme to the mobile terminal.
It should be noted that: the treatment scheme in the embodiment is a treatment scheme preset in the cloud server based on expert rules, and the cloud server can combine the preset treatment scheme according to the received first physiological state data, the received second physiological state data and the personal information of the patient, and recommend a proper treatment scheme to the patient or the doctor by means of the mobile terminal.
The mobile terminal can present a treatment plan 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.
Here, it should be noted that: the personal information data described in this embodiment includes, but is not limited to, sex, age, weight, insulin amount before treatment with the pump, activity status such as meal, exercise, what meal was eaten, what exercise was attended, and the like.
The data acquisition device in this embodiment at least includes a continuous blood glucose monitor.
The continuous glucose monitor is capable of collecting patient blood glucose value data.
The cloud server described in this embodiment 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.
In this embodiment, the instruction sets include: 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.
The physiological state instruction set described herein includes at least: the instruction set for the second physiological state is entered and the instruction set for generating the physiological state label is generated.
In this embodiment, the number of the mobile terminals is multiple.
The mobile terminal is a patient terminal and/or a doctor terminal.
It should be noted here that the present embodiment also provides a method for using the blood sugar management system for the "insulin dependent" diabetic based on the system in the above embodiment, which includes 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, 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.
In this embodiment, the step S3 further includes: and 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.
Finally, it should be noted that: the fault types include at least: data loss, spikes, drift, stagnation, pressure induced sensor decay and bias.
The method in this embodiment further includes:
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.
The method described in this embodiment further includes:
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.
Step a2 described in this embodiment further includes the following sub-steps:
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 patient physiological state label in a cloud server;
and A203, storing the insulin administration dose into a cloud server.
The system is composed of a data acquisition device, a physiological state recording 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 at least comprises: a continuous blood glucose monitor;
the physiological state recording module: the second physiological state data at least comprises 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 insulin delivery module: collecting diabetes drug strategies to make an expert rule base, giving calculation rules of large dose and basic quantity, and making different drug administration strategies according to the labels in the cloud server in a classified mode. In the administration strategy, blood sugar value data in the cloud server is extracted firstly, and the administration strategy can be directly obtained according to expert rules and labels under the condition of no predicted blood sugar value, so that the insulin administration amount is calculated. When the predicted blood glucose level can be calculated, blood glucose level data after 30 minutes is obtained using the blood glucose level data as an input of the prediction algorithm, and the predicted value data is stored in the cloud server. And finally, calculating the insulin dosage according to the current blood sugar value, the predicted blood sugar value, the current blood sugar change rate, the current physiological state and the detailed label.
The data processing module is connected with the cloud server and mainly provides a main computing method for the modules:
and obtaining whether the sensor has abnormal conditions and fault types according to the sensor fault detection and diagnosis method.
If the patient does not input the eating information, a control algorithm is adopted to identify whether the patient is in a eating state.
The predicted blood glucose value after 30 minutes is obtained by using a prediction algorithm according to the blood glucose value of the patient stored by the cloud server, so that the insulin administration strategy can be helped, and the early warning system for hypoglycemia of the patient can be provided.
The expert rule-based administration strategy is divided into two cases, non-prediction blood glucose value and prediction blood glucose value. In the case where the blood glucose level is not predicted, the insulin administration amount is inferred based on the expert rule using the current blood glucose level and information stored in the cloud server. When the predicted blood glucose value exists, the insulin dosage is calculated according to the current blood glucose, the predicted blood glucose, the current blood glucose change rate, the current physiological state and the detailed label.
The data display module: useful information of a patient is extracted from the cloud server and transferred to the plurality of mobile terminals, the current blood glucose value of the patient, the predicted blood glucose value after 30 minutes, the insulin administration dosage, the hypoglycemia early warning and sensor fault diagnosis result and the like can be provided for the plurality of mobile terminals, and the cloud server can provide an experience-based fault solution for the fault diagnosis result.
The cloud server at least comprises a cloud storage module and a cloud computing module.
The mobile terminal at least comprises a patient client used by a patient and a doctor monitoring end used by a doctor. The patient client needs the patient to enter personal information and second physiological state data of the patient and can at least see information of current blood sugar value, predicted blood sugar value, insulin administration dosage, hypoglycemia early warning and suggestion, sensor fault type, solution and the like of the patient, the monitoring end of the doctor can see the conditions of all patients in an area under the jurisdiction of the doctor, and the doctor can timely remind the patient when hypoglycemia occurs to the patient or the sensor fails.
Blood sugar collecting module
As shown in fig. 2: the workflow diagram of the blood sugar collecting device in this embodiment specifically includes the following steps:
and S1, measuring a plurality of physiological data of the patient by using the data acquisition device, and uploading the data.
And S2, the cloud server receives the uploaded data and performs soft measurement. Wherein the soft measurement means that the blood sugar value of the patient is predicted after 5 minutes by using a one-step prediction method.
And S3, judging whether the sensor equipment has faults or not by using a sensor fault detection method.
If yes, go to S4;
if not, go to S6;
and S4, judging the fault type of the abnormal equipment by using a fault diagnosis method, wherein the fault type at least comprises sensor attenuation and deviation caused by data loss, spike, drift, stagnation and pressure.
And S5, displaying an experience-based fault solution on the mobile terminal based on the fault type, and then reconstructing data, namely replacing the measured value with a soft measured value to reconstruct the data measured by the continuous blood glucose monitor and storing the data in a cloud server.
And S6, storing the personal information input by the patient and data such as the blood sugar information collected by the sensor in a cloud server.
Physiological state recording module
As shown in fig. 3: the physiological state recording workflow in the embodiment is schematic, and comprises the following steps:
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.
Insulin administration module
As shown in fig. 4: the insulin administration workflow in the embodiment is schematic, and comprises the following steps:
and S1, extracting the blood sugar value information of the patient and the personal information of the patient in the cloud server.
S2, collecting diabetes drug strategies to make an expert rule base, giving calculation rules of large dose and basic quantity, and making different drug administration strategies according to the labels in the cloud server in a classified mode.
If the current system can provide the predicted blood glucose value, go to S3;
if the current system does not provide the predicted blood glucose value, go to S4;
and S3, inputting the current blood sugar value into an expert rule to give a dosing dose.
And S4, predicting the 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 the cloud server.
And S5, calculating the insulin dosage according to the current blood sugar value, the predicted blood sugar value, the current blood sugar change rate, the current physiological state and the detailed label in the cloud server.
And S6, storing the insulin dosage in the cloud server.
Data display module
As shown in fig. 5: data display information in this embodiment is illustrated; and in addition, the blood glucose value, the insulin injection amount and the hypoglycemia early warning are stored in the insulin administration module in the cloud server after 30 minutes.
Finally, it should be noted that the system workflow in this embodiment may be:
and S1, the patient enters the second physiological state data and the personal information of the patient, and the data acquisition device acquires the first physiological state data of the patient.
And S2, storing all data and information of the patient to a cloud server.
And S3, judging whether the continuous blood sugar monitor fails, if so, reconstructing the data of the continuous blood sugar monitor and storing the data to a cloud end, and giving an adjustment suggestion of the patient based on experience.
And S4, making an insulin administration strategy according to the second physiological state label by using expert rule reasoning and the blood sugar prediction value.
And S5, formulating 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 in connection with specific embodiments, which are intended to explain the principles of the present invention and should not be construed as limiting the scope of the present invention in any way. Based on the explanations herein, those skilled in the art will be able to conceive of other embodiments of the present invention without inventive efforts, which shall fall within the 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.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113096802A (en) * | 2021-03-30 | 2021-07-09 | 浙江新医智联信息科技有限公司 | Blood sugar management method and management system based on mobile terminal equipment |
| CN113140313A (en) * | 2020-01-19 | 2021-07-20 | 浙江爱多特大健康科技有限公司 | Blood glucose detection data processing method, device, equipment and computer storage medium |
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