CN105078474A - Blood glucose and blood pressure monitoring and control system - Google Patents
Blood glucose and blood pressure monitoring and control system Download PDFInfo
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Abstract
The present invention discloses a blood glucose and blood pressure monitoring and control system. The blood glucose and blood pressure monitoring and control system comprises a wearable mobile device, an APP software terminal based on the wearable mobile device, a database, a blood glucose and blood pressure measuring device, and experts; the wearable mobile device is used for recording motion indexes such as calories consumed by motion during the patient motion process; the APP software terminal is used for establishing a prediction model of blood glucose and blood pressure indexes; the database is used for recording patient information such as personal information, the motion indexes and the blood glucose and blood pressure indexes after each motion period is finished; the blood glucose and blood pressure measuring device is used for measuring the blood glucose and blood pressure indexes of the patient after each motion period is finished; and the experts are medical personnel in the field, and the experts can find out motion amount satisfying ideal blood glucose and blood pressure indexes according to the prediction model of blood glucose and blood pressure indexes established by the APP with expert experience, and provide the patient with clear motion suggest so as to prevent blind motion of the patient.
Description
Technical field:
The present invention relates to a kind of blood glucose and analysis of blood pressure monitor and forecast system, be specifically related to a kind of blood glucose based on nonlinear system modeling and analysis of blood pressure monitor and forecast system.
Background technology:
The metabolic disease of diabetes to be one group with hyperglycemia be feature.Hyperglycemia be then due to defect of insulin secretion or its biological agent impaired, or both have concurrently and cause.Long-standing hyperglycemia during diabetes, causes various tissue, particularly eye, kidney, heart, blood vessel, neural chronic lesion, dysfunction.Statistics shows, the current diabetics number of China is up to 1.14 hundred million, and every three to four diabeticss in the average whole world just have one from China.Along with the living standard of the people and the raising of health perception, diabetes also receive concern and the attention of more and more people.But diabetes there is no the effective means of thoroughly radical cure at present.In addition, clinically diabetes more with hypertension; Many hypertensive patients, also frequent with diabetes.Both are called as homology disease.Diabetes and hypertension two kinds of diseases are causes of disease, interacting or endangering all exists intercommunity, therefore usually merges outbreak, form Diabetes with Hypertension.The treatment suggestion that expert provides for potential diabetes and Hypertensive Population and existing diabetes and hyperpietic mainly comprises self-monitoring of blood glucose blood pressure, Diet Therapy, exercise therapy and Drug therapy, and these means are prevention and corntrol diabetes and hypertensive key.But, only with regard to exercise therapy, it is on the impact by many factors of diabetes or hypertensive action effect, and Activity, exercise intensity, exercise frequency (motion density), movement time, motion mode all can produce the treatment of diabetes (or hypertension) patient different affects result.But do not form quantitative relationship between the movement effects that various forms of motion brings and blood glucose (or blood pressure) parameter index, diabetes (or hypertension) patient is difficult to define on the impact that motion produces, and is also difficult to more good utilisation motor control blood glucose (or blood pressure).Meanwhile, doctor also not easily makes further Clinics and Practices according to the motion conditions of sufferer and health present situation.Which increase the difficulty to prevention and corntrol diabetes (or hypertension).
Summary of the invention:
Cannot learn that the difference of kinematic parameter defines the present situation of the kinematic parameter of oneself to the impact of oneself blood glucose and blood markers for current diabetes (or hypertension) patient, the object of the invention is to have supplied the system of a kind of blood glucose, monitoring of blood pressure and control.Wherein, by developing APP terminal on key component, blood glucose (blood pressure) index of user can be doped than existing, and system construction is simple, use flexibly, only need make secondary development on existing equipment can reach object of the present invention.
For achieving the above object, according to the present invention, provide a kind of blood glucose, monitoring of blood pressure and control system, it is characterized in that, comprise Wearable mobility device, based on the APP software terminal of Wearable mobility device, data base, blood glucose, blood pressure measurement device, Medical Technologist;
The motion index such as the calory count that described removable wearable device consumes when being used for real time record patient moving;
Described data base is used for the personal information of record patient, as sex, and age, the calory count of a period of motion internal consumption, the blood glucose after this period of motion terminates, blood markers etc.;
Described blood glucose, blood pressure measurement device are used for patient per and have carried out blood glucose, the blood markers that a period of motion Hou Qu hospital remeasures oneself;
The described APP software terminal based on Wearable mobility device is developed is for setting up the forecast model between the personal information of patient and blood glucose blood markers, so that healthcare givers carries out the momental suggestion of next cycle according to this model.Wherein personal information comprises the age of patient, sex, the parameters such as the course of disease;
Described expert is the healthcare givers in blood glucose blood pressure field, can in conjunction with the expert's medical experience of self and forecast model for patient offers an opinion.
As present invention further optimization, described removable wearable device has the data exporting interface of USB, and can carry out wireless telecommunications with data base.
As present invention further optimization, described data base can receive data and the forecast model of the patient moving index of Wearable mobility device transmission by wireless telecommunications, also can import these data by artificial.
As present invention further optimization, the training data when blood glucose after each period of motion, blood markers data can be set up as next step forecast model, ensures that model constantly can change with the change of the period of motion.
The present invention wherein can calculate heart rate based on existing on market, the removable wearable device of calory count measures the kinematic parameter of sufferer inside some time cycles (consuming calory count etc.), and by blood glucose, blood markers data feedback be entered into removable wearable device and hospital database while regularly going to hospital to do to check.APP based on Wearable mobility device exploitation utilizes these data to set up forecast model between patient moving parameter and blood glucose (or blood pressure) index, then proposes more clearly concrete medical advice (as controlled blood glucose, blood pressure level needs how many quantity of motion) by doctor for this forecast model.Than existing, the calory count that diabetes (or hypertension) patient of all kinds of different situation can be allowed to consume according to quantity of motion associates with corresponding blood glucose (or blood pressure) index, be convenient to motion frequency and exercise intensity that they grasp self at any time, better control blood glucose (or blood pressure) index.
The present invention compared with prior art, has the following advantages:
1.APP software terminal can set up the forecast model of corresponding own situation to each patient, pointed.The related datas such as the blood glucose (blood pressure) of a large amount of patient of database purchase, blood glucose (blood pressure) index utilizing APP software terminal and a large amount of patient datas to draw to be adapted to concrete patient associates mathematical model with motion index.
2. the motion that patient can be purposive.Utilize this mathematical model, blood glucose (blood pressure) index certain movement amount next but one cycle patient can be predicted.Doctor can in conjunction with the expertise of self, the model utilizing APP terminal to set up learn patient to reach a certain blood glucose (blood pressure) index under required quantity of motion, and to patient's suggestion, this avoid patient's motion blindly.Provide reference also to the suggestions such as doctor's medication, diet.
3. provide reference to the prevention of doctor or therapeutic scheme.As described in 3, doctor can predict blood glucose (blood pressure) index of patient under certain movement amount, thus can provide the suggestions such as the quantitative motion of patient, medication, diet and the stronger treatment of specific aim and control program with reference to this index.
4. blood glucose (blood pressure) the index prediction model of patient constantly can change along with the change of the period of motion, can draw blood glucose (blood pressure) index of patient more exactly.To adopt neural network algorithm, the data of the period of motion each time all can input database, and some can become random training data, and the model obtained can be changed along with time variations, more press close to the situation of patient's reality, make prediction index result can be more accurate.
5. related data and the corresponding model of the magnanimity patient stored in data base can make the reference of the measure such as statistics, analysis, regulation and control of macroscopic view to this area's diabetes and hyperpietic as medical institutions of this area.From the angle of large data, the data of these magnanimity and model are most valuable, find that as contributed to Different age group, different sexes, Activity etc. are on the impact of patient and hiding relation, these preventions being disease, monitoring, treatment both provide effective advisory opinion, extremely have meaning.
Accompanying drawing illustrates:
Fig. 1 is theory diagram of the present invention
The algorithm flow that Fig. 2 adopts for software terminal
Fig. 3 is the network model that software terminal adopts algorithm
Description of reference numerals:
1-blood glucose, blood pressure measurement device; 2-APP software terminal;
3-Wearable mobility device; 4-data base; 5-expert.
Detailed description of the invention:
In order to make object of the present invention, technical scheme and advantage clearly understand, once by reference to the accompanying drawings and embodiment, the present invention is further elaborated.Should be appreciated that specific embodiment described herein only in order to explain the present invention, be not intended to limit the present invention.
Embodiment 1
Patient starts to perform physical exercise after receiving the suggestion that doctor does more physical exercises, meanwhile, and movable equipment 3 on wearing.In daily motion exercise, the kinematic parameters such as the calorie that equipment 3 recording individual consumes.After a period of motion (as two days), patient accepts detection in mechanisms such as hospitals, blood glucose, blood markers measurement device 1 record blood glucose, the blood markers of patient, are stored in data base 4, and this information are input in Wearable mobility device 3.After several periods of motion (supposed i-th time motion after), the kinematic parameter, personal information etc. of this individual patients and the mathematical model of blood glucose, blood markers can be set up by APP software terminal 2 according to the data of first i time.After this, the mathematical model that expert 5 can be set up by this APP, calculates the quantity of motion needed for blood glucose that next period of motion patient will reach desirable, blood markers level in conjunction with the current blood glucose of patient, blood markers horizontal forecast.And can with this model for foundation, give patient and have more blood glucose, the blood markers that treatment suggestion targetedly controls patient, as momental how much, forms of motion etc., be unlikely to provide wide in range suggestion and cause the motion of patient's blindness.And after this, often through a period of motion, after this period of motion, the kinematic parameter of patient, blood glucose, blood markers all can participate in modeling, may be random as training data, model can be changed, more the situation of closing to reality along with the change of the period of motion.
APP terminal algorithm flow process in above-mentioned Wearable mobility device 3 is as follows: due to the blood sugar concentration of human body and the heat (in calory count) of human consumption closely related, and the calory count of human consumption is subject to the impact of several factors, comprise basal metabolism, motion consumes, physical exertion, food heat effect etc., these factors all vary with each individual, relation is had with the factor such as age, sex, dietary habit of people, it is a complicated nonlinear system, this system state equation is complicated, is difficult to mathematically modeling.Putting before this, regarding a black box as by consuming nonlinear system complicated between the output parameters such as input parameter and blood sugar concentration such as calory count, age, sex.First by this "black box" inputoutput data training BP neutral net, enable network express this unknown function, then predict the indexs such as the blood glucose of sufferer is dense by the BP neutral net trained.
Make an agreement herein, motion consume calory count think after (n-1)th blood count sugar to before n-th blood count sugar the calory count of consumption of taking exercises.Examine rear blood sugar concentration for n-th time and think that sufferer is after the motion in the n-th cycle, blood glucose concentration value measured after having tested blood glucose for n-th time.
1. determine training sample and forecast sample.Sample comes from the related data of sufferer within a front n cycle, and the motion recorded as removable wearable device (watch etc.) consumes calory count, the blood sugar concentration in hospital database measured by sufferer, the age of sufferer, sex, diabetic duration etc.By these data importings to software terminal, if sufferer 2 days is moved for one-period, then remove hospital inspection blood glucose, then can obtain about 90 groups of data within half a year.With 70 groups for training sample, 20 groups of data are forecast sample.
2. numerical value normalized.Referring to of normalized is normalized to variate-value in interval [-1,1], and because the codomain of nonlinear transfer function in BP neutral net is generally in [-1,1], therefore the value of input and output variable is all better interval at this.In addition, the interval that normalization can also make input value drop on sigmoid transfer function to change greatly, make network training fastest, the performance of network also improves.
3. network design.Output layer and input layer all arrange one deck, and input layer variable has 7, and output layer neuron variable is 2.Hidden layer neuron number meets
wherein l is hidden layer neuron number, and m, n are respectively input layer number, output layer neuron number, and a is the constant in [0,10] interval.So, l is taken as 4 temporarily.
4., by training data training BP neutral net, this network is exported above-mentioned nonlinear function and has predictive ability, optimum configurations can be arranged frequency of training is 1000, and learning rate is 0.1, and training objective is 0.01.
5. export with the BP neural network prediction nonlinear function trained, and the error of fitting of BP neutral net is analyzed by the output of BP neural network prediction and desired output, and change the neuron number of hidden layer, come back to the 3rd step, [4,14] hidden layer neuron number is changed successively between, down perform 4,5, and observe prediction when changing each time and export and the error of desired output, automatic relative error and choose error minimum time hidden layer neuron number as the value of final l.
Above-mentioned BP neural network algorithm is only the one citing in the present invention in APP algorithm, not makes any restriction to modeling algorithm wherein.
The above; it is only preferred embodiment of the present invention; not the present invention is imposed any restrictions, every above embodiment is done according to the technology of the present invention essence any simple modification, change and equivalent structure transformation, all still belong in the protection domain of technical solution of the present invention.
Claims (4)
1. blood glucose and monitoring of blood pressure and a control system, is characterized in that, comprise and it is characterized in that, comprise Wearable mobility device, based on the APP software terminal of Wearable mobility device, and data base, blood glucose, blood pressure measurement device, Medical Technologist;
The motion index such as the calory count that described removable wearable device consumes when being used for real time record patient moving;
Described data base is used for the personal information of record patient, as sex, and age, the calory count of a period of motion internal consumption, the blood glucose after this period of motion terminates, blood markers etc.;
Described blood glucose, blood pressure measurement device are used for patient per and have carried out blood glucose, the blood markers that a period of motion Hou Qu hospital remeasures oneself;
The described APP software terminal based on Wearable mobility device is developed is for setting up the forecast model between the personal information of patient and blood glucose blood markers, so that healthcare givers carries out the momental suggestion of next cycle according to this model.Wherein personal information comprises the age of patient, sex, the parameters such as the course of disease;
Described expert is the healthcare givers in blood glucose blood pressure field, can in conjunction with the expert's medical experience of self and forecast model for patient offers an opinion.
2. blood glucose monitoring of blood pressure as claimed in claim 1 and control system, described removable wearable device has the data exporting interface of USB, and can carry out wireless telecommunications with data base.
3. blood glucose monitoring of blood pressure as claimed in claim 1 and control system, described data base can receive data and the forecast model of the patient moving index of Wearable mobility device transmission by wireless telecommunications, also can import these data by artificial.
4. blood glucose monitoring of blood pressure as claimed in claim 1 and control system, the training data when blood glucose after each period of motion, blood markers data can be set up as next step forecast model, ensures that model constantly can change with the change of the period of motion.
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105653865A (en) * | 2015-12-31 | 2016-06-08 | 中国科学院深圳先进技术研究院 | Blood glucose monitoring method, device and system |
| CN107019499A (en) * | 2016-01-29 | 2017-08-08 | 佛山市顺德区顺达电脑厂有限公司 | Contactless health evaluating and suggesting system for wearing and its method |
| CN108882873A (en) * | 2016-04-15 | 2018-11-23 | 欧姆龙株式会社 | Biont information analytical equipment, system and program |
| CN108968975A (en) * | 2018-07-20 | 2018-12-11 | 深圳市漫牛医疗有限公司 | The measurement method and equipment of blood glucose value based on artificial intelligence |
| CN109350027A (en) * | 2018-10-26 | 2019-02-19 | 广州华见智能科技有限公司 | A kind of blood pressure forecasting system based on facial image |
| CN111192681A (en) * | 2019-12-25 | 2020-05-22 | 新绎健康科技有限公司 | Method and system for acquiring target blood glucose characteristics |
| CN111728600A (en) * | 2020-06-29 | 2020-10-02 | 北京凤凰医联科技有限公司 | Blood pressure and blood glucose monitoring system |
| CN113936771A (en) * | 2021-12-17 | 2022-01-14 | 北京因数健康科技有限公司 | Iterative generation method and device of health index target |
| CN115868977A (en) * | 2022-11-15 | 2023-03-31 | 爱多特大健康科技有限公司 | Information generation method for blood sugar control and first user terminal |
| CN118366595A (en) * | 2024-05-06 | 2024-07-19 | 盐城市大丰区疾病预防控制中心 | Integrated comprehensive management system for diabetics |
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| CN103565521A (en) * | 2012-07-20 | 2014-02-12 | 数伦计算机技术（上海）有限公司 | Diabetes and cardiovascular and cerebrovascular disease monitoring and treatment system |
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2015
- 2015-08-21 CN CN201510526244.8A patent/CN105078474A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN103565521A (en) * | 2012-07-20 | 2014-02-12 | 数伦计算机技术（上海）有限公司 | Diabetes and cardiovascular and cerebrovascular disease monitoring and treatment system |
Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105653865B (en) * | 2015-12-31 | 2018-06-05 | 中国科学院深圳先进技术研究院 | Blood sugar monitoring methods, apparatus and system |
| CN105653865A (en) * | 2015-12-31 | 2016-06-08 | 中国科学院深圳先进技术研究院 | Blood glucose monitoring method, device and system |
| CN107019499A (en) * | 2016-01-29 | 2017-08-08 | 佛山市顺德区顺达电脑厂有限公司 | Contactless health evaluating and suggesting system for wearing and its method |
| US11246501B2 (en) | 2016-04-15 | 2022-02-15 | Omron Corporation | Biological information analysis device, system, and program |
| CN108882873A (en) * | 2016-04-15 | 2018-11-23 | 欧姆龙株式会社 | Biont information analytical equipment, system and program |
| US11617516B2 (en) | 2016-04-15 | 2023-04-04 | Omron Corporation | Biological information analysis device, biological information analysis system, program, and biological information analysis method |
| CN108968975A (en) * | 2018-07-20 | 2018-12-11 | 深圳市漫牛医疗有限公司 | The measurement method and equipment of blood glucose value based on artificial intelligence |
| CN109350027A (en) * | 2018-10-26 | 2019-02-19 | 广州华见智能科技有限公司 | A kind of blood pressure forecasting system based on facial image |
| CN111192681A (en) * | 2019-12-25 | 2020-05-22 | 新绎健康科技有限公司 | Method and system for acquiring target blood glucose characteristics |
| CN111728600B (en) * | 2020-06-29 | 2021-01-19 | 北京凤凰医联科技有限公司 | Blood pressure and blood glucose monitoring system |
| CN111728600A (en) * | 2020-06-29 | 2020-10-02 | 北京凤凰医联科技有限公司 | Blood pressure and blood glucose monitoring system |
| CN113936771A (en) * | 2021-12-17 | 2022-01-14 | 北京因数健康科技有限公司 | Iterative generation method and device of health index target |
| CN113936771B (en) * | 2021-12-17 | 2022-04-15 | 北京因数健康科技有限公司 | Iterative generation method and device of health index target |
| CN115868977A (en) * | 2022-11-15 | 2023-03-31 | 爱多特大健康科技有限公司 | Information generation method for blood sugar control and first user terminal |
| CN118366595A (en) * | 2024-05-06 | 2024-07-19 | 盐城市大丰区疾病预防控制中心 | Integrated comprehensive management system for diabetics |
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