Functional mathematical model of automated non-invasive glukometers | Статья в журнале «Молодой ученый»

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Рубрика: Медицина

Опубликовано в Молодой учёный №15 (149) апрель 2017 г.

Дата публикации: 13.04.2017

Статья просмотрена: 27 раз

Библиографическое описание:

Турапов, У. У. Functional mathematical model of automated non-invasive glukometers / У. У. Турапов, Ш. Н. Турапов. — Текст : непосредственный // Молодой ученый. — 2017. — № 15 (149). — С. 166-172. — URL: https://moluch.ru/archive/149/41080/ (дата обращения: 26.04.2024).



This article presents some results of many years in scientific research on a new method of non-invasive blood glucose measurement (determination without the blood) by studying biophysical parameters of biologically active points. Authors have proposed and substantiated concept-creating models on automated system of non-invasive measurement of blood glucose by the electrical resistance of the skin in the informative biologically active points. A functional diagram outlines the technical means to implement and is described in detail the method work creating automated system of non-invasive measurement of blood glucose levels.

Key words: non-invasive method, functional scheme, informative, biologically active points, adequate

Diabetes mellitus (DM) illness is caused by the shortage of insulin in the body and metabolism disorder. According to the World health care organization, the number of patients suffering DM increased 499 million in 2016, it makes up the 6–8 % of the total population. By 2025, 1.5 or 2 times increase of this number is predicted. Currently, the number of DM patients is increasing by one in each 5 seconds, and each 7 seconds one patient dies, this index comprises 3 million people by the year. At present, this index reached 9.6 million in Russia, 43.2 million in China, 50.8 million in India, 7.1 million in Japan and 1.6 million in Uzbekistan respectively. According to the experts, every third of DM patients in USA dies as a result of illness complication. The number of patient suffering from DM makes up 2.3 million people in Russia in 2015, and 16 000 of them are minors and 8 500 of them are adult teenagers. According to the information from 2016 as a result of DM, following increases are observed:

‒ the number of patients suffering from heart diseases or stroke to 2–3 %;

‒ losing eyesight of a patient to 10 %;

‒ nephropathy patients to 15 %;

‒ the number of amputated patients in gangryne of leg joints to 20 %.

In European Union in order to prevent DM, to fund the scientific research in this direction is considered to be the beginning of a new era. According to the data taken from 2016, it was found out that 475 billion US dollars are spent for treating DM patients. 123 billion US dollars are spent in Russia as well. Though, this index comprises 10–15 % of total budget of European Union, it is predicted that it will reach 18,5 % by 2020.

In 2016 the international consortium against DM, aimed to carry out scientific cooperation at international scale by treatment mechanisms research of DM and announced the 7th April, the day of “Struggle against diabetes”.

As a result of abnormal increase of glucose ammount (glycemia) in blood, hyperglycemia appears and it is considered to be one of its features. In order to cure diabetes and identify glycemia amount dynamics, it is necessary to take a blood 7 times a day. As a result of applying a biochemical method by the Healthcare Ministry, and in order to prevent the infection of AIDS, hepatitis and other infectious diseases in blood, this biochemical analysis is prescribed to be taken 2 times a day.

DM illness is known in East folk medicine for a long time. Abu Ali Ibn Sino is described this illness as following: “ In DM, sugar amount in blood increases suddenly and goes out with urine (sugar amount is found in urine) and as a result of it, thirst, weight loss, weakness, itching and other signs are observed.”

DM is the lifelong illness and it is necessary to treat it during the whole life. In patients who have not been treated properly or the patients who have high amount of glucose in blood for a long time face with vein complications (macro and micro angiopathy).

There are two types of DM: insulin related (the I type of diabetes) and not related to insulin (the II type of diabetes). The main purpose of treating both types of diabetes is to decrease the ammount of sugar to the index of healthy people, that is to achieve the compensation (normal condition). It is required to identify the amount of glucose in blood very often. Eventually, based on the requirements and offers, to create glucometer on the basis of invasive and non-invasive methods is the main purpose.

To create non-invasive methods in order to prevent mainly from AIDS, hepatitis and other infectious diseases through the blood of patients becomes one of the main problems in the world nowadays.

As a result of rapid entry and usage of computers, information communication technologies and the methods of mathematic modeling, there is a possibility to create a new method of evaluating the glucose amount in blood- non-invasive functional mathematic model of glucometer (NFMMG). To develop the effective methods of software and algorithm complex for the steps of creating NFMMG and to put it into practice gives opportunity to create new NFMMG method, which is the collection of scientifically capacious multiple calculating blood analysis and to develop the technologies of transferring them into computers. Also, it gives the chance of creating therapeutic and diagnostic electronic devices that have scientific basis in the sphere of information technologies in treatment and prevention of DM.

The algorithms of mathematical models evaluating glycemia ammount by non-invasive method were developed in 60- 70th years and they are the algorithms of Albisser, Bolye, Craygen, Biostater I and II, Kovamori, Fisher, Y. G. Antomonov and S. I. Kiferenko. At present, a lot of different types of invasive glucometer equipment are developed on the basis of theses algorithms, such as: (“Accu-Chek active”,” One Touch”, “On call Plus”, “Dexcom G-4”, “Accucher Active”, “Accucher Performa”, “TC Bayer”, “Countour”, “Omron” and others. (They are described in the first figure).

Non-invasive metod (this is the method of determining glucose ammount in blood without taking blood from vein or finger) is the method of evaluating the glucose ammount in blood and the main difference of this method is that it can determine the result in a very short time, without hurting and it is secure and very convinient.

Figure 1. Types of invasive glucometers

This method is a product of mathematical model that was not created to evaluate other parameters of glucose amount in blood and it is adopted to evaluate adequately. When the product of mathematical model considered being qualitative? It is necessary to collect the possibilities of glucometer, the high level and accuracy of blood analysis evaluation, the convenience of glucometer, the prevention from AIDS and other infectious diseases, no harm to the patient and other conveniences in one. Currently most of the glucometers are created by non-invasive method (Figure 2) and it is possible to choose them by their quality, for instance: «Gluco Track», «Simfoniya TCGM». «Sugar Senz»,«Gluco Track DF», «Omelion-А1», «Google» and other types.

Figure 2. Types of non-invasive glucometers

The possibility of created invasive and non-invasive glucometers is increasing and they are chosen according to the high possibility of determining the glucose amount in blood or according to their quality. But there is a disadvantage along with advantages of existing glucometers, for example: invasive and non-invasive glucometers carries out only the task of determining glucose ammount in blood.

The glucometer that we want to create would be able to execute 3 tasks at the same time and patient would have a chance to control it with the personal computer or cell phone:

1. It will find BAP in human body.

2. The glucose ammount in blood will be determined by created functional mathematical model of non-invasive glucometer (FMMNG).

3. There will be the possibility to provide the correction manipulation of glucose ammount in blood using the electopucture treatment method (ETM) and acupuncture of informative BAP in FMMNG. Taken results will be downloaded to doctors and patients database in computer. The dynamics of data will be appeared and thus it will be possible to analyze according to the results. Widely using the computer technologies and based on scientific and practical experiment results of many years, to evaluate automated glucose ammount in blood on the basis of ER in informative BAP in unclear complex environment and to solve the problem of hyperglycemia treatment system complex and creating its hardware are the main aim.

Since 2014, In Tashkent University of Information Technologies, the plan of scientific research devoted to the number of works in creating automated complicated diagnostics and treatment system complex (ACDTSC) is elaborated.

In this article the global problem is to create the first stage of ACDTSC- the functional mathematic model of automated non-invasive glucometer and the collection of its hardware involves following 6 steps:

  1. Static processing of all input and output parameters.
  2. To use dispersion method between two biochemical methods in order to find out the most suitable one.
  3. The stage of identification of informative meridians on the basis of 7th local criteria and new multi criteria.
  4. To build adequate model by removing law connection parameters by the multi coefficient correlation method.
  5. The stage of creating criteria of a model according to the results of spline methods and correlation connection of informative BAP of glucose amount in blood among all types of models through ER.
  6. There are stages of identification the border difference of connection by objects between “three sigma” method and FMMNG.

The main issue of building FMMNG model is the identification of informative meridians local criteria and new multi criteria method is created on this basis. The local criteria in above mentioned figure 4 conists of the following: -Ryidoraku- local method; Student-T criteria; — the third type of Coefficent correlation method; — random searching algorithm of adapted evaluating of informative parameters; — the identification of informative parameters and analytical method of classification; — new spline methods; — new multi criteria dispersion method. Informative color according to informativeness of parameters is created using these methods.

The main purpose of mathematic modeling in unclear environment is to create a model similar to output parameters on the basis of input parameters and as a result the following formula comes out:

, (1)

Here С — the vector of unknown parameters and it is determined in the process of creating and identification of mathematic model. F- is the structure of model and it is determined through the adequacy of linear, non-linear, logarithmic, parabolic, exponential and other model classes. The unknown — C parameter is determined as a result of minimizing our function.

.(2)

From the following (2) formula, the real and the difference of model cost value is determined by calculating residual dispersion. The following formula comes out as a result.

, (3)

The adequacy possibility of F- structure, we will determine by multi coefficient correlation method.

(4)

Here, — full dispersion is:

(5)

It calls full (4) dispersion of formulae (4) and has constant value and as a result multi coefficient correlation Rm (4) value will be connected to the residual dispersion (3) change.

In order to create FMMNG, multi coefficent correlation’s highest value should reach RM =1 (4) and (3). As a result, the process of minimizing the value and model value should be equal to .

The stages of building adequate model is tested for adequcy when each of the informative parameters added and etc. In our task, on the basis of left and right sights of 5 informative BAP, according to 1 and 2 type od DM, FMMNG linear mathematical model is built (see the1-table):

Table 1

The results of development the informative DM BAP complex

BAP in treatment of DM

Informative BAP chosen with the help of static methods

The most used BAP in building FMMNG

1.

Tai-yuan, Xe-gu, Chun-yan, Tai-Bai, Shen-men, Czin-Gu, Tai-Si, Da-lin, Yan-chi, Syu-syuy, Tai-chun, Van-gu, San-Czan, Pi-shu, Le-szu, Gun-sun, Chjao-xay, Szu-san-li, Chi-sze.

Tai-yuan, Xe-gu, Chun-yan, Tai-Bai, Shen-men, Tai-Si, Da-lin, Yan-chi, Syu-syuy, Tai-chun, Pi-shu, Gun-sun, Szu-san-li, Czin-Gu.

Tai-Bai, Shen-men, Tai-Si, Da-lin, Pi-shu, Gun-sun, Szu-san-li, Czin-Gu.

2

Total:19 та БФН

Total: 14 BAP

Total:8 BAP

In applying FMMNG in clinical process, the experiment on 96 patients I and II type of DM in endocrinology department at Tashkent Medical Academy 1-clinic is carried out, at the same time the glucose amount in blood by biochemical method is determined and ER in informative BAP is measured concurrently. In comparison process of FMMNG with biochemical method, our model comprised 92.2 % proximity and it is given in the 2- table.

Table 2

The comparison results of data taken from FMMNG and biochemical method for Iand II type of DM

Biochemical method

Model value results

The difference between%-percentages

The results of biochemical analysis

Modelvalue results

The difference between%-percentages

1

117.0

124.39

0.0632

1

117.00

118.13

0.009

2

117.0

117.24

0.0020

2

108.00

108.80

0.007

3

117.0

115.03

0.0168

3

112.00

109.63

0.021

4

117.0

116.65

0.0030

4

114.00

119.87

0.047

5

120.0

129.57

0.0798

5

117.00

119.13

0.017

6

130.0

131.36

0.0105

6

120.00

114.59

0.045

7

130.0

127.41

0.0199

7

122.00

114.81

0.062

8

130.0

131.50

0.0116

8

122.00

119.63

0.022

9

130.0

132.99

0.0230

9

125.00

127.00

0.020

10

144.0

136.44

0.0525

10

126.00

127.35

0.010

11

144.0

141.70

0.0160

11

128.00

121.14

0.058

12

144.0

136.64

0.0511

12

130.00

123.11

0.059

13

144.0

133.90

0.0701

13

140.40

134.37

0.042

14

144.0

146.38

0.0165

14

150.00

151.79

0.011

15

144.0

144.22

0.0015

15

153.00

158.52

0.036

16

144.0

146.43

0.0140

16

154.20

156.99

0.018

17

153.0

145.12

0.0515

17

162.00

161.42

0.003

18

153.0

155.91

0.0190

18

180.00

184.78

0.026

19

153.0

149.20

0.0249

19

180.00

175.99

0.022

20

153.0

160.33

0.0479

20

180.00

170.27

0.054

21

153.0

158.23

0.0342

21

180.00

181.36

0.007

22

154.0

153.50

0.0046

22

180.00

173.59

0.035

23

154.0

158.26

0.0263

23

189.00

188.10

0.004

24

154.0

154.79

0.0038

24

196.20

197.50

0.007

25

154.0

169.48

0.0089

25

198.00

203.22

0.026

26

171.0

170.49

0.0030

26

198.00

202.93

0.024

27

171.0

171.62

0.0036

27

211.20

204.64

0.031

28

171.0

171.25

0.0014

28

225.00

212.42

0.055

29

171.0

159.38

0.1146

29

226.00

228.99

0.013

30

180.0

180.95

0.0053

30

228.60

238.15

0.041

31

180.0

185.25

0.0291

31

233.80

241.59

0.033

32

180.0

192.00

0.0207

32

235.00

246.48

0.048

33

189.0

191.93

0.0155

33

253.80

257.55

0.014

34

189.0

202.28

0.0310

34

253.80

262.76

0.035

35

196.0

208.45

0.0528

35

270.60

275.54

0.018

36

198.0

206.80

0.0444

36

288.00

292.10

0.014

37

211.0

211.98

0.0037

37

306.00

306.22

0.007

38

211.0

219.96

0.0415

38

306.90

297.71

0.029

39

232.0

222.97

0.0389

39

326.00

315.49

0.026

40

216.0

222.35

0.0294

40

342.00

344.99

0.087

41

225.0

221.48

0.0156

41

360.00

348.45

0.032

42

226.0

223.38

0.0112

42

389.00

377.80

0.028

43

216.0

214.83

0.0054

43

412.00

397.25

0.035

44

228.0

226.15

0.0107

44

412.00

403.87

0.019

45

233.0

229.28

0.0185

45

430.00

439.70

0.022

46

270.0

257.35

0.0469

46

496.00

485.28

0.021

To conclude, following results may be obtained using FMMNG: total evaluating time of the glycemia amount in blood using FMMNG makes up 4 minutes; the number of medical personnal decreases 2 times and makes up one person; -the patient would not be anxious and would not feel any pain when FMMNG is applied and there is no traumatic effect to a patient; FMMNG can evaluate glucose amount in blood immediately at any time; — FMMNG method is adopted always to evaluate adequately; — it eliminates the infection of AIDS and other infectious diseases totally.

The novelty of research to create AFMMNG that evaluates glycemia amount in blood of healthy people and patients of I and II type of DM and consist of following scientific novelty:

  1. ER ammount in BAP automated functional mathematical model of non-invasive glucometer is created for the first time.
  2. The high level of correlation connection between glucose amount change in blood in DM and ER amount in BAP is proved for the first time.
  3. Local criteria in the development of informative parameters complex is applied for the first time and multi criteria method on the basis of local criteria is created.
  4. Functional scheme of creating automated complicated diagnostics and treatment system complex (ACDTSC) is created.
  5. Summary data software (SDS) in C++ for all stages of modeling is developed.
  6. In creating AFMMNG spline method is used for the first time.
  7. Besides numerical regularity of the glycemia amount in blood of healthy and patient, it was defined that there is a periodical change and peculiarity of unclear movement when patient is anxious.
  8. Mutual quantitative relations of ER parameters in BAP and the adequate evaluation of mathematical model in estimating glycemia amount in blood, testing and results of comparing criteria are chosen.
  9. Patients suffering DM and who are inclined to the change of ER amount in BAP and when treatment of this BAP with EAP method is applied, it is observed that the amount of glucose in blood and urine is normalized.
  10. When FMMNG that was created by non-invasive method is applied to clinical process, it is proved that provided biochemical results of orthotoliudin method proximity makes up 92.3- %.
  11. Using the table of the first symptoms of “Ryodaraku” system and M. D. Hyodo, the mathematical model of evaluation diagnosis of meridians misbalance for all illnesses and its software are elaborated.
  12. The 100 % accuracy is achieved in identification process of human face from database when using the dispersion, coefficent correlation and multi-criteria method.
  13. On the basis of created algorithm of developing mathematical model and its software, it is proved that it is possible to create identification model of colored metals provision.
  14. Using ER amount taken from informative BAP by spline method, it is proved that it is possible to increase the probability of evaluating glucose amount in blood.

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Основные термины (генерируются автоматически): BAP, FMMNG, AIDS, ACDTSC, NFMMG, AFMMNG, EAP, ETM, SDS, Прикладная статистика.


Ключевые слова

Неинвазивный метод, Функциональная схема, информативный, Биологически активные точки, адекватный, non-invasive method, functional scheme, informative, biologically active points, adequate

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