CN104958077A - Intelligent control close-loop artificial pancreas system - Google Patents
Intelligent control close-loop artificial pancreas system Download PDFInfo
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- CN104958077A CN104958077A CN201510444435.XA CN201510444435A CN104958077A CN 104958077 A CN104958077 A CN 104958077A CN 201510444435 A CN201510444435 A CN 201510444435A CN 104958077 A CN104958077 A CN 104958077A
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Abstract
The invention discloses an intelligent control close-loop artificial pancreas system, comprising a continuous glucose monitoring device, an intelligent controller, and an insulin infusion device. The continuous glucose monitoring device is used to continuously monitor blood sugar concentration of a human body according to set interval. The intelligent controller is used to receive human body blood sugar monitoring data of the continuous glucose monitoring device in real time, and according to the real-time human body blood sugar monitoring data, by using a built-in fuzzy self-adaption proportion calculus control algorithm, calculates real-time insulin infusion device dosage. The insulin infusion device is used to receive the real-time insulin infusion device dosage of the intelligent controller, and perform real-time insulin on human bodies according to the real-time insulin infusion device dosage. The system can greatly reduce fluctuation range of human body blood sugar, and control blood glucose level in a set target interval, and improves accuracy and effectiveness of an insulin injection therapy, and makes blood glucose level of diabetics close to or reach standard of normal people, thereby greatly reducing various complications and improving living quality of the patients.
Description
Technical field
The present invention relates to a kind of artificial pancreas system, especially a kind of closed loop artificial pancreas system of Based Intelligent Control, belongs to treating diabetes apparatus field.
Background technology
Closed loop artificial pancreas (Artificial Pancreas, AP) three parts are generally comprised: continuous blood sugar monitoring system (Continuous Glucose Monitoring System, CGMS), control algolithm (Control Algorithm, and the insulin pump (Insulin Pump, IP) of precision insulin infusion can be carried out CA).
Over more than 40 year, various countries expert in three of artificial pancreas (CGMS, IP and CA) achieves much important progress, has had more ripe CGMS and IP launch at present.Control algolithm is the brain of artificial pancreas, and since 21 century, the research of external AP control algolithm, part enters clinical trial.In these algorithms, study and more deep mainly contain three classes: proportional integral derivative (PID) algorithm, fuzzy logic (FL) algorithm and model PREDICTIVE CONTROL (MPC) algorithm.
1) pid algorithm.Pid algorithm is the classic algorithm in Traditional control theory, is widely used in industrial control field, and its Research Thinking in AP is the physiology transmitting procedure simulating human body β cells secrete insulin with ratio, differential, integration three components as much as possible; Pid algorithm simple, intuitive, parameter is less, be convenient to calculate, ratio, integration and differentiation three components followed the tracks of preferably blood glucose quick, change at a slow speed, but along with the prolongation of time, there will be saturation integral phenomenon, need to correct, and there is the impact of insulin residual effect due to human body, also need to add insulin feedback module and correct.
2) FL algorithm.FL algorithm is one of Major research field of Based Intelligent Control.Its principle applied in AP first comparatively comprehensively sums up the experience of clinical diabetes treatment long-term practice accumulation, set up expert knowledge library, then basic theories and the method for fuzzy mathematics is used, the condition of clinical treatment experience rule, operation fuzzy set are represented, and using these fuzzy control rules and for information about (as clinical evaluation index etc.) as knowledge stored in expert knowledge library, then according to the blood glucose level data of Real-Time Monitoring, use fuzzy reasoning, draw the infusion of insulin dosimetry parameter adapted.The Heuristics that this FL algorithm relies on clinical expert clinical diabetes to be treated long-term practice accumulation is established as expert knowledge library, is converted into fuzzy logic control rule, meets the standard empirical of clinical treatment, be easy to as clinician is understood.
3) MPC algorithm.MPC algorithm is a kind of System design based on model algorithm, and its basic Thoughts as shown in Figure 1.First preliminary mathematical modeling is carried out, as initial forecast model to human body carbohydrate metabolism physiological process; Then basis is at time t
kbefore known measurement blood glucose y and infusion of insulin speed u, is optimized this model parameter, then the prediction blood glucose in the infusion of insulin speed calculated now and future, to reduce the gap between prediction blood glucose and target blood glucose; At time t
k+1new measurement blood glucose y can be obtained again
k+1if, y
k+1the time t predicted with back
k+1the blood glucose value at place is different, and this model will suboptimization again, and so move in circles, until measure blood glucose value to be stabilized in target blood glucose, computation model also settles out thereupon.
MPC algorithm is based on patient's carbohydrate metabolism physiological models, each step all recalculates based on when pre-test blood glucose value, advantage is that result of calculation better can follow the tracks of change of blood sugar, but it is very complicated that shortcoming is patient's metabolic model, amount of calculation is very large, needs between real-time and accuracy, obtain good balance.
According to investigations with understanding, disclosed prior art is as follows at present:
Application publication number is the application for a patent for invention of CN103889317A, disclose a kind of unified platform of the blood sugar level for monitor and forecast diabetics, it is described that and a kind ofly can utilize the data from different monitoring technology and can offer help to the patient suffering from diabetes in some scalable levels, scope controls the flexible system of (artificial pancreas) from the suggestion about long-term trend and prognosis to real-time automated closed-loop; These scalable monitorings and therapeutic strategy are sent by the integrated system being called as auxiliary (DiAs) platform of diabetes; This system is provided for realizing the basis of various monitoring, consulting and treating diabetes algorithm or method automatically; For the details of each patient, and assess customization DiAs recommendation at any given time for patient risk.But this patent application merely provides a kind of conception of technology platform of monitor and forecast diabetes, to how to carry out diabetics blood sugar monitoring, how closed loop control patient blood sugar level and how all fail clearly to the prognosis of the patient key technical problem such as to advise, cannot to patented technology make clear, effectively define.
Authorization Notice No. is the utility model patent of CN201658692U, disclose a kind of artificial pancreas system, the glucose automatic induction system CGM it provide a kind of insulin-injecting system that automatically can detect blood sugar concentration, specifically comprise serially, automatically human blood glucose concentration being detected, for analyzing blood sugar concentration and calculating the glycemic control system of optimum dosage and according to injection volume signal, human body carried out to the automatic injection system of injection of insulin; Described glucose automatic induction system CGM is communicated with glycemic control system; Described glycemic control system and automatic injection system connectivity.Glucose automatic induction system CGM and automatic injection system organically combine by this utility model, have effectively achieved the integrated of test-and-treat, for patient provides safe, suitable, the accurate injection of insulin of dosage, make patient can obtain best therapeutic effect.Although this patent includes glucose automatic induction system, for analyzing glycemic control system and the Automatic insulin injection system of blood sugar concentration and calculating optimum dosage, but its not clearly this system whether be closed loop control, whether be real-time control, and which kind of technology its most crucial glycemic control system adopts carry out controlling also failing clear and definite, thus and fail to reflect up-to-date artificial pancreas technology trends.
Summary of the invention
The object of the invention is the defect in order to solve above-mentioned prior art, a kind of closed loop artificial pancreas system of Based Intelligent Control is provided, the control algolithm that this system adopts combines the advantage of pid algorithm and FL algorithm, greatly can reduce the fluctuation range of blood sugar for human body, blood sugar level is controlled the target interval in setting, improve accuracy and the effectiveness of injection of insulin therapy, make the blood sugar level of diabetics close to the standard even reaching normal person, greatly reduce the generation of various complication, improve the life quality of patient.
Object of the present invention can reach by taking following technical scheme:
A closed loop artificial pancreas system for Based Intelligent Control, comprises continuous blood sugar monitoring equipment, intelligent controller and insulin infusion devices, and described intelligent controller is connected with continuous blood sugar monitoring equipment and insulin infusion devices respectively;
Described continuous blood sugar monitoring equipment, for monitoring continuously human blood glucose concentration according to setting-up time interval;
Described intelligent controller, for the blood sugar for human body Monitoring Data of real-time reception continuous blood sugar monitoring equipment, and according to real-time body's glucose monitor data, utilize built-in fuzzy self-adaption proportional integral derivative control algolithm, calculate real-time insulin infusion devices dosage; Wherein, described fuzzy self-adaption proportional integral derivative control algolithm is specially:
The physiology transmitting procedure of adoption rate calculus simulation human body β cells secrete insulin, as basic model, and the parameters in the basic model adopting fuzzy logic algorithm comparative example calculus to set up carries out rolling optimization, as shown in Figure 4, Based Intelligent Control is carried out to insulin infusion devices;
Described insulin infusion devices, for receiving the real-time insulin infusion devices dosage that intelligent controller calculates, and according to real-time insulin infusion devices dosage, carries out real-time infusion to human body.
As a kind of embodiment, the physiology transmitting procedure of described adoption rate calculus simulation human body β cells secrete insulin, as basic model, this model is shown below:
Wherein, the amount of insulin PID (t) that human body β cell is secreted because of change of blood sugar is made up of proportional component, quadrature components and differential component, G
bfor target setting blood glucose value, G for measure blood glucose value in real time, K
p, K
iand K
dthe gain of proportional component, quadrature components and differential component respectively; Described proportional component corresponds to amount of insulin secretion when actual measurement blood glucose value departs from target blood glucose value, is then 0 when surveying blood glucose value and equaling target blood glucose value; Described quadrature components is for adjusting amount of insulin secretion when blood glucose surrounding target value fluctuates up and down a little; Described differential component regulates insulin secretion rapidly when corresponding to blood glucose Rapid Variable Design.
As a kind of embodiment, described continuous blood sugar monitoring equipment adopts glucose sensor.
As a kind of embodiment, described insulin infusion devices adopts insulin pump.
As a kind of embodiment, described intelligent controller is connected with continuous blood sugar monitoring equipment and insulin infusion devices respectively by wireless signal.
The present invention has following beneficial effect relative to prior art:
1, intelligent controller of the present invention is built-in with fuzzy self-adaption proportional integral derivative control algolithm, can according to the blood sugar for human body data real-time monitored, automatically, immediately, trace, adjust insulin infusion devices dosage intelligently, thus carry out real-time infusion, the closed-loop control system that formation infusion of insulin and continuous blood sugar are monitored, i.e. artificial pancreas, greatly can reduce the fluctuation range of blood sugar for human body, blood sugar level is controlled the target interval in setting, improve accuracy and the effectiveness of injection of insulin therapy, make the blood sugar level of diabetics close to the standard even reaching normal person, greatly reduce the generation of various complication, improve the life quality of patient.
2, the closed loop artificial pancreas system that the present invention is formed, in control algolithm, organically combine the achievement in research of prior art on PID (proportional integral derivative) algorithm and FL (fuzzy logic) algorithm, form a kind of fuzzy self-adaption proportional integral derivative control algolithm, to control insulin infusion devices, namely the physiology transmitting procedure of pid algorithm simulation human body β cells secrete insulin is adopted, as basic model, and adopt FL algorithm to carry out rolling optimization to each parameter in PID model, Based Intelligent Control is carried out to insulin infusion devices, this fuzzy self-adaption proportional integral derivative control algolithm has given full play to the advantage of the large algorithm of PID and FL two, achieve optimum closed loop control.
Accompanying drawing explanation
Fig. 1 is MPC algorithm principle schematic diagram in prior art.
Fig. 2 is the structured flowchart of closed loop artificial pancreas system of the present invention.
Fig. 3 is the control principle drawing of closed loop artificial pancreas system of the present invention.
Fig. 4 is Fuzzy Adaptive PID Control algorithm principle figure of the present invention.
Detailed description of the invention
Embodiment 1:
Below in conjunction with embodiment and accompanying drawing, the present invention is described in further detail, but embodiments of the present invention are not limited thereto.
As shown in Figure 2, the closed loop artificial pancreas system of the present embodiment comprises continuous blood sugar monitoring equipment, intelligent controller and insulin infusion devices, and described intelligent controller is connected with continuous blood sugar monitoring equipment and insulin infusion devices respectively by wireless signal (as bluetooth, GSM/GPRS, 2G, 3G etc.); Wherein:
Described continuous blood sugar monitoring equipment, for monitoring continuously human blood glucose concentration according to setting-up time interval, having Monitoring Data real-time radio emission function, the data of monitoring can be sent to intelligent controller;
Described intelligent controller can adopt PLC, 51 Series Controllers, ARM Series Controller etc., it is the core of whole system (artificial pancreas), it is built-in with fuzzy self-adaption proportional integral derivative control algolithm, for the blood sugar for human body Monitoring Data of real-time reception continuous blood sugar monitoring equipment, and according to real-time body's glucose monitor data, utilize fuzzy self-adaption proportional integral derivative control algolithm, calculate real-time insulin infusion devices dosage, this real-time insulin infusion devices dosage can send to insulin infusion devices;
Described insulin infusion devices, for receiving the real-time insulin infusion devices dosage of intelligent controller, and according to real-time insulin infusion devices dosage, carries out real-time infusion to human body.
As shown in Figures 2 and 3, the closed loop artificial pancreas system control procedure of the present embodiment is as follows:
1) continuous blood sugar monitoring equipment is monitored human blood glucose concentration continuously according to setting-up time interval, and blood sugar for human body Monitoring Data is sent to intelligent controller;
2) intelligent controller receives the blood sugar for human body Monitoring Data of continuous blood sugar monitoring equipment, and according to real-time body's glucose monitor data, utilize built-in fuzzy self-adaption proportional integral derivative control algolithm, calculate real-time insulin infusion devices dosage, then real-time insulin infusion devices dosage is sent to insulin infusion devices;
3) insulin infusion devices receives the real-time insulin infusion devices dosage of intelligent controller, and according to real-time insulin infusion devices dosage, carries out real-time infusion to human body.
Above-mentioned steps 2) in, described fuzzy self-adaption proportional integral derivative control algolithm is specially:
The physiology transmitting procedure of adoption rate calculus (PID) algorithm simulation human body β cells secrete insulin, as basic model, and the parameters in the basic model adopting fuzzy logic (FL) algorithm comparative example calculus to set up carries out rolling optimization, as shown in Figure 4, Based Intelligent Control is carried out to insulin infusion devices, fuzzy self-adaption proportional integral derivative control algolithm has given full play to the advantage of two large algorithms, realizes optimum closed loop control;
The physiology transmitting procedure of described adoption rate calculus simulation human body β cells secrete insulin, as basic model, this model is shown below:
Wherein, the amount of insulin PID (t) that human body β cell is secreted because of change of blood sugar is made up of ratio (proportion) component, integration (integration) component and differential (differentiation) component, G
bfor target setting blood glucose value, G for measure blood glucose value in real time, K
p, K
iand K
dthe gain of proportional component, quadrature components and differential component respectively; Described proportional component corresponds to amount of insulin secretion when actual measurement blood glucose value departs from target blood glucose value, is then 0 when surveying blood glucose value and equaling target blood glucose value, and thus this component is for keeping daily basal insulin infusion without any contribution; Described quadrature components is for adjusting amount of insulin secretion when blood glucose surrounding target value fluctuates up and down a little, also be the sole component making glucostasis keep basal insulin infusion amount when desired value, due to the quadrature components only trace adjustment insulin secretion when blood glucose surrounding target value fluctuates a little, thus can guarantee that blood glucose can be stabilized in desired value; Described differential component regulates insulin secretion rapidly when corresponding to blood glucose Rapid Variable Design.
In above-described embodiment, described continuous blood sugar monitoring equipment adopts glucose sensor, generally adopts glucose oxidase sensor; Described insulin infusion devices adopts insulin pump.
In sum, the present invention can according to the blood sugar for human body data real-time monitored, the fuzzy self-adaption proportional integral derivative control algolithm utilizing intelligent controller built-in, automatically, immediately, trace, adjust insulin infusion devices dosage intelligently, thus carry out real-time infusion, the closed-loop control system that formation infusion of insulin and continuous blood sugar are monitored, i.e. artificial pancreas, greatly can reduce the fluctuation range of blood sugar for human body, blood sugar level is controlled the target interval in setting, improve accuracy and the effectiveness of injection of insulin therapy, make the blood sugar level of diabetics close to the standard even reaching normal person, greatly reduce the generation of various complication, improve the life quality of patient.
The above; be only patent preferred embodiment of the present invention; but the protection domain of patent of the present invention is not limited thereto; anyly be familiar with those skilled in the art in the scope disclosed in patent of the present invention; be equal to according to the technical scheme of patent of the present invention and inventive concept thereof and replace or change, all belonged to the protection domain of patent of the present invention.
Claims (5)
1. a closed loop artificial pancreas system for Based Intelligent Control, it is characterized in that: comprise continuous blood sugar monitoring equipment, intelligent controller and insulin infusion devices, described intelligent controller is connected with continuous blood sugar monitoring equipment and insulin infusion devices respectively;
Described continuous blood sugar monitoring equipment, for monitoring continuously human blood glucose concentration according to setting-up time interval;
Described intelligent controller, for the blood sugar for human body Monitoring Data of real-time reception continuous blood sugar monitoring equipment, and according to real-time body's glucose monitor data, utilize built-in fuzzy self-adaption proportional integral derivative control algolithm, calculate real-time insulin infusion devices dosage; Wherein, described fuzzy self-adaption proportional integral derivative control algolithm is specially:
The physiology transmitting procedure of adoption rate calculus simulation human body β cells secrete insulin, as basic model, and the parameters in the basic model adopting fuzzy logic algorithm comparative example calculus to set up carries out rolling optimization, carries out Based Intelligent Control to insulin infusion devices;
Described insulin infusion devices, for receiving the real-time insulin infusion devices dosage of intelligent controller, and according to real-time insulin infusion devices dosage, carries out real-time infusion to human body.
2. the closed loop artificial pancreas system of a kind of Based Intelligent Control according to claim 1, is characterized in that: the physiology transmitting procedure of described adoption rate calculus simulation human body β cells secrete insulin, and as basic model, this model is shown below:
Wherein, the amount of insulin PID (t) that human body β cell is secreted because of change of blood sugar is made up of proportional component, quadrature components and differential component, G
bfor target setting blood glucose value, G for measure blood glucose value in real time, K
p, K
iand K
dthe gain of proportional component, quadrature components and differential component respectively; Described proportional component corresponds to amount of insulin secretion when actual measurement blood glucose value departs from target blood glucose value, is then 0 when surveying blood glucose value and equaling target blood glucose value; Described quadrature components is for adjusting amount of insulin secretion when blood glucose surrounding target value fluctuates up and down a little; Described differential component regulates insulin secretion rapidly when corresponding to blood glucose Rapid Variable Design.
3. the closed loop artificial pancreas system of a kind of Based Intelligent Control according to claim 1, is characterized in that: described continuous blood sugar monitoring equipment adopts glucose sensor.
4. the closed loop artificial pancreas system of a kind of Based Intelligent Control according to claim 1, is characterized in that: described insulin infusion devices adopts insulin pump.
5. the closed loop artificial pancreas system of a kind of Based Intelligent Control according to claim 1, is characterized in that: described intelligent controller is connected with continuous blood sugar monitoring equipment and insulin infusion devices respectively by wireless signal.
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| CN106860955A (en) * | 2017-01-21 | 2017-06-20 | 广东食品药品职业学院 | Method based on fuzzy self-adaption proportional integral derivative control insulin pump closed loop infusion |
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101310686A (en) * | 2007-05-23 | 2008-11-26 | 希森美康株式会社 | Medical diagnosis support computer system, computer program, and server computer |
| CN102946923A (en) * | 2010-06-22 | 2013-02-27 | 美敦力迷你迈德公司 | Method and/or system for closed-loop control of glucose to a treatment range |
| WO2014035570A2 (en) * | 2012-08-30 | 2014-03-06 | Medtronic Minimed, Inc. | Safeguarding measures for a closed-loop insulin infusion system |
| CN104667379A (en) * | 2015-03-06 | 2015-06-03 | 上海交通大学 | Insulin pump with dynamic closed-loop control |
-
2015
- 2015-07-24 CN CN201510444435.XA patent/CN104958077A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101310686A (en) * | 2007-05-23 | 2008-11-26 | 希森美康株式会社 | Medical diagnosis support computer system, computer program, and server computer |
| CN102946923A (en) * | 2010-06-22 | 2013-02-27 | 美敦力迷你迈德公司 | Method and/or system for closed-loop control of glucose to a treatment range |
| WO2014035570A2 (en) * | 2012-08-30 | 2014-03-06 | Medtronic Minimed, Inc. | Safeguarding measures for a closed-loop insulin infusion system |
| CN104667379A (en) * | 2015-03-06 | 2015-06-03 | 上海交通大学 | Insulin pump with dynamic closed-loop control |
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| CN106295184A (en) * | 2016-08-10 | 2017-01-04 | 深圳先进技术研究院 | Intelligent wearable device for emotion rehabilitation |
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| CN109804434B (en) * | 2016-10-06 | 2022-11-29 | 美敦力迷你迈德公司 | Infusion system and method for automatically mitigating motor effects |
| CN106860955A (en) * | 2017-01-21 | 2017-06-20 | 广东食品药品职业学院 | Method based on fuzzy self-adaption proportional integral derivative control insulin pump closed loop infusion |
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| CN115297913A (en) * | 2020-03-23 | 2022-11-04 | 欧弗洛有限公司 | Chemical injection control method and computer program |
| CN114099846A (en) * | 2020-08-26 | 2022-03-01 | 上海移宇科技股份有限公司 | Closed-loop artificial pancreas insulin infusion control system |
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| CN112023191A (en) * | 2020-09-14 | 2020-12-04 | 广州大麦生物科技有限公司 | Biological electronic equipment |
| CN112402732A (en) * | 2020-10-10 | 2021-02-26 | 广东食品药品职业学院 | Insulin infusion amount control method based on adaptive control weighting factor strategy |
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