Review Artificial Pancreas Control Strategies Used for Type 1 Diabetes Control and Treatment: A Comprehensive Analysis
Sohaib Mehmood 1,* , Imran Ahmad 1, Hadeeqa Arif 1, Umm E Ammara 2 and Abdul Majeed 3 1 Department of Electrical and Computer Engineering, COMSATS University, Islamabad 45550, Pakistan; [email protected] (I.A.); [email protected] (H.A.) 2 School of Electrical Engineering and Computer Science, National University of Science and Technology (NUST), Islamabad H-12, Pakistan; [email protected] 3 School of Information and Electronics Engineering, Korea Aerospace University, Deogyang-gu, Goyang-si, Gyeonggi-do 412-791, Korea; [email protected] * Correspondence: [email protected]; Tel.: +92-302-8179496
Received: 1 May 2020; Accepted: 10 July 2020; Published: 28 July 2020
Abstract: This paper presents a comprehensive survey about the fundamental components of the artificial pancreas (AP) system including insulin administration and delivery, glucose measurement (GM), and control strategies/algorithms used for type 1 diabetes mellitus (T1DM) treatment and control. Our main focus is on the T1DM that emerges due to pancreas’s failure to produce sufficient insulin due to the loss of beta cells (β-cells). We discuss various insulin administration and delivery methods including physiological methods, open-loop, and closed-loop schemes. Furthermore, we report several factors such as hyperglycemia, hypoglycemia, and many other physical factors that need to be considered while infusing insulin in human body via AP systems. We discuss three prominent control algorithms including proportional-integral- derivative (PID), fuzzy logic, and model predictive, which have been clinically evaluated and have all shown promising results. In addition, linear and non-linear insulin infusion control schemes have been formally discussed. To the best of our knowledge, this is the first work which systematically covers recent developments in the AP components with a solid foundation for future studies in the T1DM field.
Keywords: type-1 diabetes mellitus; insulin; closed loop and open loop schemes; artificial pancreas; PID controller; β-cells; model predictive controller; and fuzzy logic controller
1. Introduction
1.1. What Is Diabetes? Diabetes is a metabolic disease in which one’s blood sugar, or blood glucose (BG), levels are very high. Glucose comes from the foods one eats. Insulin is a hormone that helps the glucose enter human cells to provide them with energy, and it helps in maintaining the homeostatic BG levels. Insulin is produced by the specialized type of cells of the pancreas known as beta-cells (β-cells), which are necessary to exploit glucose as a source of energy from the digested food. Chronic hyperglycemia (high blood glucose concentration (BGC)) can lead to further complications such as microvascular and macrovascular damage leading to kidney disease, neuropathy, amputations, cardiac disease, stroke and retinopathy. Hence, diabetes includes a broad range of heterogeneous diseases [1]. Diabetes has been classified in to three major types based on the presumed etiology which are explained below: Type 1 diabetes mellitus (T1DM) is a chronic autoimmune disease in which the human body does not produce enough insulin while insulin inoculations are required on a daily basis. T1DM
Appl. Syst. Innov. 2020, 3, 31; doi:10.3390/asi3030031 www.mdpi.com/journal/asi Appl. Syst. Innov. 2020, 3, 31 2 of 36
was further classified into two subgroups: immune mediated and idiopathic by the American Diabetes Association (ADA) in 2007. Meanwhile, the idiopathic type-1 diabetes is considered to be type-2 diabetes by several researchers and clinicians. Patients of T1DM become entirely dependent on externally administered insulin, and it is the only treatment available in medicine. However, the daily dose of insulin varies and depends heavily on a range of other factors including age, gender, daily exercise, and physique. However, an average daily dose is about 1-unit of insulin per kg weight per day [2]. Type 2 diabetes mellitus (T2DM) also known as non-insulin dependent diabetes mellitus (NIDDM), it is characterized by the defect in both insulin secretion and insulin resistance. High levels of BG are managed with the reduced food intake, improved physical activity, and ultimately oral medications or insulin [3]. Gestational diabetes (GD) can occur temporarily during pregnancy, and recent findings suggest that it can occur in 2~10% of the all pregnancies. During pregnancy, significant hormonal changes can lead to the blood sugar elevation in genetically predisposed individuals which is known as gestational diabetes (GD).
1.2. What Causes Diabetes in the Human Body? The common causes of diabetes are: insufficient production of the insulin (either absolutely or relative to the body’s requirements), production of the defective insulin (which is uncommon in a human body), or the inability of cells to use insulin properly and efficiently leading to hyperglycemia. It can also occur due to the flaw in the insulin secretion or insulin action or both. There can be multiple causes for each diabetes type outlined earlier. The causes for each diabetes are summarized below:
T1DM diabetes causes are not as well documented compared to T2DM. Family history is a known risk factor for the T1DM. Other risk factors can include having certain infections or diseases of the pancreas. T1DM is primarily characterized as an autoimmune disease resulting in damage of the insulin-producing β-cells in the pancreas by T-cells (CD4+ and CD8+), and macrophages penetrating the islets. Both genetic as well as environmental factors as yet unclear trigger autoimmune responses against β-cells and destroy them, thus significantly proliferating the disease in humans [4]. According to the latest studies, genetic factors are becoming more evident in causing T1DM disease [5–7]. T2DM develops when the body becomes resistant to insulin or when the pancreas is unable to produce enough insulin. The main cause of this is as yet unknown, although genetics and environmental factors, such as being inactive, and overweight seem to be main causes for the T2DM disease. GD can occur due to the significant hormonal changes during the pregnancy period, and blood sugar elevation in genetically predisposed individuals.
The morbidity and mortality rates of diabetes mellitus have increased throughout the world in recent years. Diabetes has influenced 463 million people around the globe [8]. Furthermore, the World Health Organization (WHO) predicts that the number of patients can soar to 552 million approximately worldwide by 2030, which is approximately a 19.2% increase in the current patients [9].
1.3. Current Treatment Modalities Available for Diabetes in Medicine The ensemble learning technique has been used to forecast the early outset of the diabetes. The main purpose of these techniques is two-fold: (i) whether the person has a possibility of contracting diabetes in near future or not, and (ii) the risk probability of having diabetes linked with the person. These findings help to train the model itself for the prediction of the diabetes [10]. People affected by T1DM require day-to-day management of exogenous insulin with firsthand help or by using an insulin pump. A stability inspection is carried out and the dynamics of glucose are demonstrated by a simulation using different parameters [11]. Artificial neutral networks (ANNs) are promising machine-learning algorithms that are very beneficial in figuring out the complicated patterns, and classification markers Appl. Syst. Innov.2020, 3, x FOR PEER REVIEW 3 of 35 Appl. Syst. Innov. 2020, 3, 31 3 of 36 a simulation using different parameters [11]. Artificial neutral networks (ANNs) are promising machine-learning algorithms that are very beneficial in figuring out the complicated patterns, and without making any presumptions. The formally approved current treatment modalities used for the classification markers without making any presumptions. The formally approved current treatment T1DM treatment and diagnosis are summarized in Figure1. modalities used for the T1DM treatment and diagnosis are summarized in Figure 1.
Figure 1. Current treatment modalities used for type 1 diabetes mellitus treatment and diagnosis. Figure 1. Current treatment modalities used for type 1 diabetes mellitus treatment and diagnosis.
FariasFarias et et al. al. [12 [12]] devised devised a a longlong short-termshort-term memorymemory (LSTM) (LSTM) ANN ANN to to identify identify T1DM T1DM patients. patients. TheThe auto auto antibodies antibodies have have been been used used forfor thethe clinicalclinical diagnosis of of the the T1DM. T1DM. Auto Auto antibodies antibodies against against insulin,insulin, glutamic glutamic acid acid decarboxylosedecarboxylose (GAD), (GAD), and and in insulinomasulinoma linked linked protein-2 protein-2 (IA-2) (IA-2) are stable are stable in the in T1DM panels. Both predictive and screening T1DM requires sensitive detection techniques [13]. An the T1DM panels. Both predictive and screening T1DM requires sensitive detection techniques [13]. automated insulin delivery system is designed to roll together consistently the glucose levels of the An automated insulin delivery system is designed to roll together consistently the glucose levels of the patients, insulin dosing, and food intake and then calculate how much an insulin pump should patients, insulin dosing, and food intake and then calculate how much an insulin pump should deliver deliver to maintain the BG level at normal range while giving a clear, precise report [14]. An to maintain the BG level at normal range while giving a clear, precise report [14]. An Android game Android game has been developed for the T1DM to check their BG level and keep updated about the hashealth been of developed child while for playing the T1DM the togame check and their also BGnotify level them and through keep updated the game about to inject the health insulin of and child whilealso playing about the the food game which and also is suitable notify them for the through child thebody game [15]. to The inject MyDi insulin framework and also is about presented the food whichwhich is suitableintegrates for a smart the child glycemic body diary [15]. Thefor Androi MyDid framework users, which is presentedautomatically which records integrates the activity a smart glycemicof patients diary via for pictures Android and users, deep learning-based which automatically technology records which the monitor activity their of patients meals and via sports pictures andvia deep pictures learning-based and store them. technology The proposed which method monitor is theirhelpful meals to predict and sports the diabetic via pictures patients and using store them.smart The technology proposed [16]. method Zhang is et helpful al. [17] toproposed predict an the Internet-of-things diabetic patients (IoT)-based using smart self-management technology [16 ]. Zhangtechnique et al. [named17] proposed MyDay an tool Internet-of-things for the T1DM control (IoT)-based and self-managementtreatment. This tool technique fuses heterogeneous named MyDay tooldata for sources the T1DM for diabetes control self-management and treatment. Thispatterns tool analysis fuses heterogeneous and promotes datadata sharing sources of for diabetic diabetes self-managementpatients in real patternstime. Wei analysis et al. [18] and promotesproposed dataa reinforcement sharing of diabeticlearning-based patients algorithm in real time. for Weithe et al.control [18] proposed of BG level a reinforcement in the T1DM’s learning-based patients. The algorithm main purpose for the of controlthe proposed of BG levelmodel in is the to T1DM’sinject patients.insulin, The and main its performance purpose of thewas proposed verified through model is simulations to inject insulin, on the and aggregation its performance of the wasminimum verified throughmodel, simulationsand part of the on Hovorka the aggregation model. Cescon of the et minimum al. [19] proposed model, a and model part for of once the a Hovorka day dosing model. of Cesconlong acting et al. [ 19insulin] proposed using aiterative model forlearning once acontrol. day dosing With ofthe long help acting of this insulin model, using insulin iterative can act learning for a control.longer With time therather help than of this being model, injected insulin multiple can act times for ain longer a single time day. rather than being injected multiple A growing body of literature has explained the various control strategies based on model times in a single day. predictive control (MPC) strategy for the T1DM’s treatment and control [20,21]. MPC uses a model A growing body of literature has explained the various control strategies based on model predictive to predict and augment future process behavior. In each time step, an optimization problem is control (MPC) strategy for the T1DM’s treatment and control [20,21]. MPC uses a model to predict solved to obtain an ideal control sequence that reduces a cost function and accomplishes constraints and augment future process behavior. In each time step, an optimization problem is solved to obtain as the system progresses. Furthermore, the stability of the MPC can be guaranteed by accumulating ana ideal terminal control cost sequenceand a terminal that constraint, reduces a costor by function extension and of the accomplishes prediction hori constraintszon [22]. Sinclair as the systemet al. progresses.[23] explained Furthermore, various recommendations the stability of in the the MPC areas can of: clinical be guaranteed diagnosis, by establishing accumulating management a terminal costplans and and a terminal glucose constraint,regulation, ordiabetes by extension self-management of the prediction education, horizon nutritional [22]. therapy, Sinclair physical et al. [23 ] explainedactivity, variousexercise and recommendations lifestyle modification, in the areasinsulin of: treatments clinical diagnosis,and regimens, establishing use of technology management in plansdiabetes and management, glucose regulation, hypoglycemia, diabetes managing self-management cardiovascular education, risk, manage nutritionalment of therapy, microvascular physical activity,risk, and exercise inpatient and management lifestyle modification, of T1DM and insulin ketoacidosis. treatments A comprehensive and regimens, guideline use of technology for dealing in diabeteswith glucose-related management, emergencies hypoglycemia, in T1DM managing are summarized cardiovascular by Dhatariya risk, management et al. [24]. of microvascular risk, andThe inpatient challenges management involved in ofdiagnosing T1DM and T1DM ketoacidosis. in older adults A comprehensive are explained by guideline Jones1 et for al. dealing [25]. withAndrej glucose-related et al. [26] summarized emergencies various in T1DM treatment are summarized algorithm by for Dhatariya T1DM, and et al.diagnostic [24]. criteria for T1DMThe challengesin adults. Singh involved et al. in[27] diagnosing explained T1DMserological, in older biochemical, adults are and explained genetic byaspects Jones1 related et al. to [25 ]. Andrej et al. [26] summarized various treatment algorithm for T1DM, and diagnostic criteria for T1DM in adults. Singh et al. [27] explained serological, biochemical, and genetic aspects related to gene Appl. Syst. Innov. 2020, 3, 31 4 of 36
HLA-DQB1 and its association with the T1DM. Nadia et al. [28] explained the paradigm shift in treating T1DM by coupling inflammation to islet regeneration. Buzzetti et al. [29] comprehensively explained the role of obesity in the increasing incidence of T1DM around the globe. Dayal et al. [30] discussed the possible risks to children and adolescents with T1DM during the current pandemic and the special considerations in management in those affected with COVID-19. Anna et al. [31] presented a study focusing on adults with congenital heart disease (CHD) who also develop T1DM disease. The study reported that increasing number of adults with CHD will significantly affect cardiologist practice in the coming years. Cobelli et al. [32] presented a comprehensive review about artificial pancreas (AP) systems and their components. They also discuss the improvements needed in the AP systems for better monitoring of T1DM.
1.4. Manuscript Contribution in the Field of Study The contributions of this research in the field of T1DM treatment and control can be summarized as follows: (i) it explains relevant details about the diabetes concept, different types of diabetes, causes of the diabetes, and practical control strategies used in the T1DM treatment and diagnosis; (ii) it summarizes various factors with sufficient details that need to be considered in AP systems for insulin delivery in a human body; (iii) it describes various insulin delivery and administration methods used for T1DM patients; (iv) it explains three advanced controller and strategies used in the AP for BG regulation in a human body; (v) it provides a comparison of the different controllers used for T1DM assessment and control; and (vi) to the best of our knowledge, this is the first survey that systematically covers recent strategies used in T1DM treatment and control with AP systems.
1.5. Manuscript Organization The rest of the paper is structured as follows: Section2 explains the physiological methods of insulin delivery. Section3 discusses the open loop administration of insulin and Section4 presents the closed loop administration of insulin. Section5 comprehensively explains the proportional integral derivative (PID) controller. Section6 explains about the linear and non-linear insulin infusion control schemes. Section7 explains about the most widely used MPC strategy in the T1DM therapy. Section8 discusses the glucose measurement (GM), and latest approaches. The assimilation of data from other groups and our own synthesis on the subject matter (i.e., control algorithms) are presented in Section9. Finally, conclusions and promising future directions are offered in Section 10.
2. Physiological Methods of Insulin Delivery This section presents the physiological methods of the insulin delivery in the human body. The β-cell response to the glucose system is explained which is very important, as it highlights how an artificial system should behave in practice/real-world scenarios [33]. There are two phases “first” and “second” phase responses of the β-cell [33]. Both phases are briefly summarized in Section 2.1.
2.1. Significance of First and Second Phase Insulin Secretion in Human Body The immediate release of insulin after a meal is known as “first-phase insulin release”. The first-phase insulin secretion has a major effect on extinguishing hepatic glucose production [34]. Small change in the plasma insulin can have a significant effect on the hepatic glucose output [34]. Normally, insulin production in an early phase is actually less than the total insulin needed to yield a similar area under the glucose curve [33,35]. Improving first-phase response is related to glucose tolerance [36]. A person whose system is insulin-resistant without the variation in the insulin secretion becomes diabetic. Meanwhile, a person’s system which maintains the required level of glucose tolerance by adopting the “control gain” is regarded as a non-diabetic individual [33]. The first and second phases of insulin secretion occur all the time in the body. However, the second phase insulin secretion has a major effect on the glucose production as well as its utilization in a human body [34]. The importance of second phase insulin secretion cannot be ignored as it is necessary to maintain Appl. Syst. Innov. 2020, 3, 31 5 of 36
Appl. Syst. Innov.2020, 3, x FOR PEER REVIEW 5 of 35 plasma glucose at a set point (i.e., normal range) [33]. In addition, the loss of first phase insulin secretionnecessary is theto maintain first indicator plasma of glucose the development at a set point of T2DM(i.e., normal in a human range) body[33]. In [37 addition,]. the loss of first phase insulin secretion is the first indicator of the development of T2DM in a human body [37]. 2.2. Hyperglycemia and Hypoglycemia 2.2.Insulin Hyperglycemia cannot beand infused Hypoglycemia until the BG level exceeds 180–200 mg/dL. This condition is referred as hyperglycemiaInsulin cannot [38 be]. infused The condition until the of BG hyperglycemia level exceeds 180–200 is found mg/dL. to be This common condition in intensive is referred care unitsas hyperglycemia (ICU) [37]. According [38]. The to condition existing surveysof hyperglycemia presented is by found Krinsley to be et al.common [39], even in intensive a small levelcare of hyperglycemiaunits (ICU) [37]. can According lead to an to increasedexisting surveys rate of presen hospitalted mortalityby Krinsley in et ICUs al. [39], [39 even]. Sugar a small level level control of withhyperglycemia insulin infusion can lead has to a riskan increased of hypoglycaemia. rate of hospital Sugar mortality level whichin ICUs is [39].<50 Sugar mg/dL level is thecontrol called hypoglycemia.with insulin infusion The hypoglycemia has a risk of canhypoglycaemia. be diagnosed Sugar by the level Whipple’s which is triad,<50 mg/dL with threeis the steps.called (i) neuroglycemiahypoglycemia. symptoms, The hypoglycemia (ii) immediate can be glucose diagnosed of < 40by mg the/dL, Whipple’s and (iii) triad, symptoms with three of the steps. relief (i) after glucoseneuroglycemia intake [40 symptoms,]. (ii) immediate glucose of <40 mg/dL, and (iii) symptoms of the relief after glucose intake [40]. 2.3. Biological Perspective on How β-Cell Achieves Glucose Control and Energy Metabolism in Type 1 Diabetes Mellitus2.3. Biological (T1DM) Perspective on How β-Cell Achieves Glucose Control and Energy Metabolism in Type 1 Diabetes Mellitus (T1DM) The biological perspective on how a β-cell achieves glucose control can be summarized in four steps as:The (i) biological after a person perspective takes on a meal, how a the β-cell small achieves intestine glucose absorbs control glucose can be from summarized the digested in four food. Consequently,steps as: (i) after the a BG person levels takes rise; a (ii)meal, increase the small in BGintestine levels absorbs stimulate glucose the βfrom-cells the in digested the pancreas food. to produceConsequently, insulin; (iii)the afterBG levels that, rise; insulin (ii) triggersincrease liver,in BG muscle, levels stimulate and fat tissue the β cells-cells to in absorb the pancreas the glucose, to whereproduce it is stored.insulin; As (iii) glucose after that, is absorbed insulin intriggers the related liver,parts, muscle, the and BG levelsfat tissue fall; (iv)cellsOnce to absorb the glucose the levelsglucose, drop where below it a certainis stored. threshold, As glucose there is absorbed is no longer in the a su relatedfficient parts, stimulus the forBG insulinlevels fall; release, (iv) Once and the β-cellsthe glucose stop releasing levels drop further below insulin. a certain The threshold, conceptual there overviewis no longer of a thesufficient whole stimulus process for is showninsulin in release, and the β-cells stop releasing further insulin. The conceptual overview of the whole process Figure2. Due to the synchronization of the insulin release with the β-cells, basal insulin concentration is shown in Figure 2. Due to the synchronization of the insulin release with the β-cells, basal insulin oscillates in the blood following a meal. The oscillations are clinically important, since they are believed concentration oscillates in the blood following a meal. The oscillations are clinically important, since to help maintain sensitivity of insulin receptors in the target cells. The key role of the β-cells is to they are believed to help maintain sensitivity of insulin receptors in the target cells. The key role of sense the BG levels, and regulate insulin accordingly. For example, when the BG increases following the β-cells is to sense the BG levels, and regulate insulin accordingly. For example, when the BG food intake, β-cells sense this change in concentration, and subsequently secrete insulin into the blood. increases following food intake, β-cells sense this change in concentration, and subsequently secrete Oninsulin the other into hand, the blood. when On blood the glucoseother hand, levels when are blood low, such glucose as following levels area low, prolonged such asfasting following period, a theprolonged release of fasting insulin period, from β the-cells release is inhibited of insulin [41 from]. β-cells is inhibited [41].
FigureFigure 2. 2.Conceptual Conceptual overview overview of of thethe biologicalbiological perspective on on how how a aββ-cell-cell achieves achieves glucose glucose control. control.
DoctorsDoctors have have tried tried to helpto help patients patients of T1DMof T1DM to maintain to maintain their their glucose glucose values values as close as close to the to normal the rangenormal as possible range as to delaypossible the onsetto delay and the slow onset the progressionand slow the of long-termprogression diabetes of long-term complications diabetes such ascomplications renal disease, such retinopathy, as renal disease, neuropathy, retinopathy, and heart neuropathy, disease. and Monitoring heart disease. glucose Monitoring levelsis glucose vital for achievinglevels is desirablevital for achieving glycemia anddesirable avoiding glycemia hypoglycemia. and avoiding Continuous hypoglycemia. Glucose Continuous Monitoring Glucose (CGM) is aMonitoring recent glucose (CGM) monitoring is a recent glucose device monitoring that assists device to achieve that assists these to aims. achieve CGM these has aims. been CGM shown has to improvebeen shown glycemia to improve without glycemia an increase without in the an hypoglycemia increase in the for hypoglycemia adults with T1DMfor adults who with wear T1DM it most dayswho [42 wear–44]. Furthermore,it most days studies[42–44]. haveFurthermore, reported thestudies positive have psychosocial reported the changes positive such psychosocial as decreased partners’changes anxiety, such as vigilance decreased and partners’ negative anxiety, experiences vigilance surrounding and negative hypoglycemia, experiences andsurrounding improved patients’hypoglycemia, mood and and general improved quality patients’ of life mood [45,46 and]. Currently, general quality flash glucoseof life [45,46]. monitoring Currently, is emerging flash glucose monitoring is emerging as an innovative technology, it enables self-monitoring of blood
Appl. Syst. Innov. 2020, 3, 31 6 of 36 Appl. Syst. Innov.2020, 3, x FOR PEER REVIEW 6 of 35 asglucose an innovative [47]. With technology, the help itof enablesCGM and self-monitoring other related oftechnologies, blood glucose doctors [47]. and With clinicians the help are of CGM able to andgain other more related insight technologies, into the glucose doctors variability, and clinicians temporarily are able to improved gain more sense insight of intocontrol, the glucose reduced variability,distress and temporarily reduced improved dependency sense on of the control, others reduced physical distress devices. and reducedHowever, dependency some participants on the othersexperienced physical confrontation devices. However, with somethe CGM participants output experiencedas intrusive,confrontation whereas others with reported the CGM frustration output asdue intrusive, to the whereas technical others failures reported and frustration difficulty due toin thetrusting technical the failures devices. and diActivefficulty and in trusting passive theself-management devices. Active behaviours and passive were self-management reported by the behaviours participants, were mirroring reported individual by the participants, differences in mirroringattitudes individual and coping di stylesfferences [48]. in attitudes and coping styles [48]. InsulinInsulin making making and and subsequent subsequent release release from thefromβ-cells the isβ controlled-cells is controlled by multiple by players, multiple including players, glucose,including peptide glucose, hormones, peptide neurotransmitters, hormones, neurotransmitters, and other related and compounds other related [49, 50compounds]. Briefly, the [49,50]. rise inBriefly, the BG the levels rise that in the follows BG levels food that intake follows is sensed food intake by the isβ -cells,sensed which by the subsequently β-cells, which take subsequently glucose uptake from glucose the blood, up andfrom metabolize the blood, it and to more metabolize fuel for theit to mitochondria more fuel for to shuntthe mitochondria towards adenosine to shunt triphosphatetowards adenosine (ATP) production, triphosphate increased (ATP) production, levels of which increased result levels in the of inhibition which result of thein the cell’s inhibition KATP channels.of the cell’s This K ultimatelyATP channels. leads This to ultimately depolarization leads at to the depolarization plasma membrane at the plasma (PM), an membrane electrical change(PM), an 2+ 2+ thatelectrical functions change to activate that functions the L-type to activate Ca channels, the L-type which Ca2+ allows channels, an influxwhich of allows Ca aninto influx the β of-cell. Ca2+ 2+ Finally,into the this β-cell. wave Finally, of Ca thistriggers wave the of Ca release2+ triggers of secretory the release granules of secretory containing granules insulin, containing to be released insulin, fromto be the released cell by from exocytosis. the cell Theby exocytosis. conceptual The overview conceptual of the overview whole process of the whole is depicted process in is Figure depicted3. Thein flowFigure is marked3. The flow with is red-arrowsmarked with in Figurered-arrows3 for clarity.in Figure 3 for clarity.
FigureFigure 3. Conceptual3. Conceptual overview overview of theof the glucose-stimulated glucose-stimulated insulin insulin secretion secretion (GSIS) (GSIS) and and brief brief excerpt excerpt ofof glucose glucose sensing, sensing, oxidation oxidation into into adenosine adenosine triphosphate triphosphate (ATP) (ATP) energy energy equivalents, equivalents, potassium-ATP potassium-ATP (K(KATPATP) channels) channels working working together, together, leading leading to to calcium calcium entry entry and and insulin insulin exocytosis exocytosis in in the the pancreatic pancreatic β-cellsβ-cells (shown (shown with with red red arrow arrow flow). flow). (Adopted (Adopted from from [41 [41]).]). 3. Open Loop Administration of an Insulin 3. Open Loop Administration of an Insulin The requirement/need of an automated AP system has been present since 1921, the time when The requirement/need of an automated AP system has been present since 1921, the time when insulin was discovered first time [33]. The produced insulin needs definition in terms of prehepatic insulin was discovered first time [33]. The produced insulin needs definition in terms of prehepatic insulin as well as portal insulin concentration in order to work as closely in a non-diabetic state [51]. insulin as well as portal insulin concentration in order to work as closely in a non-diabetic state [51].
3.1. Timing of Insulin Delivery With the increase in the demand of the insulin infusion and its mechanism, it is recommended to take the dose with almost every meal [52]. However, one major concern is the timing of insulin
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3.1. Timing of Insulin Delivery With the increase in the demand of the insulin infusion and its mechanism, it is recommended Appl. Syst. Innov.2020, 3, x FOR PEER REVIEW 7 of 35 to take the dose with almost every meal [52]. However, one major concern is the timing of insulin deliverydelivery [53[53].]. DependingDepending on on the the type type of of insulin, insulin, rapid-acting rapid-acting insulin insulin should should be be infused infused 15 min15 minutes before thebefore meal. the Short-acting meal. Short-acting or regular or insulinregular caninsulin be infused can be 30infused min before 30 minutes the meal. before Having the meal. food activityHaving straightfood activity away straight after regular away insulin after regular can cause insulin hypoglycemia can cause hypoglycemia (i.e., low sugar (i.e., level) low [53 sugar]. Changing level) [53]. the intervalChanging between the interval insulin infusion between and insulin meal shows infusion remarkable and meal effect shows in the postprandialremarkable hyperglycemiaeffect in the inpostprandial insulin dependent hyperglycemia patients. in Recent insulin studies dependent show patients. that a near-normal Recent studies glucose show level that can a benear-normal achieved onlyglucose when level patient can be had achieved their insulin only when administered patient had 60 mintheir beforeinsulin the administered meal [52]. Results60 minutes infer before that adjustingthe meal the[52]. time Results and infer the amount that adjusting of insulin the can time be and helpful the inamount the management of insulin can of thebe helpful diabetes in [ 41the]. Asmanagement shown in Figure of the4 ,diabetes delayed [41]. insulin As infusionshown in before Figure meals 4, delayed can be insulin linked toinfusion greater before hyperglycemia meals can up be tolinked three to hours greater after hyperglycemia the meal [54]. up to three hours after the meal [54].
FigureFigure 4.4. ComparisonComparison ofof delayeddelayed andand standardstandard insulininsulin deliverydelivery withwith thethe mealmeal (adopted(adopted fromfrom[ 38[38]).]). 3.2. Manual Administration of the Insulin 3.2. Manual Administration of the Insulin The injection technique is the most common and early cure for a diabetic patient. Dosage is The injection technique is the most common and early cure for a diabetic patient. Dosage is different for different individuals. People with T1DM do not produce enough insulin to meet the different for different individuals. People with T1DM do not produce enough insulin to meet the glucose level of a normal person so they need an external insulin. Most of the T2DM patients do not glucose level of a normal person so they need an external insulin. Most of the T2DM patients do not require external insulin. The timing of the insulin injection depends on the glucose level, and various require external insulin. The timing of the insulin injection depends on the glucose level, and various other factors [53]. Injection site selection is important to yield appropriate results. Insulin can be other factors [53]. Injection site selection is important to yield appropriate results. Insulin can be injected into subcutaneous tissue of the upper arm or the anterior aspect of thighs and buttocks [54]. injected into subcutaneous tissue of the upper arm or the anterior aspect of thighs and buttocks [54]. 3.3. Subcutaneous Versus Inhaled Insulin 3.3. Subcutaneous Versus Inhaled Insulin Inhaled insulin has been proven way more effective and reliable in the T1DM and T2DM. Infusion of regularInhaled insulin insulin through has lungs been by proven inhalation way has more shown effective insulin and absorption reliable and in loweringthe T1DM of and the BGT2DM. [55]. AsInfusion shown of in regular Figure5 insulin, the maximum through insulinlungs by concentration inhalation has is moreshown rapid insulin in case absorption of inhaled and insulin lowering as comparedof the BG to[55]. the subcutaneousAs shown in Figure (SC) injection 5, the [maximum56]. In subcutaneous insulin concentration insulin (SCI), is the more short-acting rapid in insulincase of driveninhaled by insulin a mechanical as compared force and to deliveredthe subcutaneous via a needle (SC) or injection soft cannula [56]. under In subcutaneous the skin is undertaken insulin (SCI), on athe continuous short-acting and insulin constant driven basis [57by]. a Although mechanical SCI force is expensive, and delivered but it provides via a needle greater or flexibilitysoft cannula for theunder individuals the skin havingis undertaken diabetes on in a managingcontinuous their and condition, constant basis and it [57]. allows Although more precise SCI is insulinexpensive, dosing but thanit provides multiple greater daily flexibility injections for (MDI) the [individuals58]. According having to systematic diabetes in reviews, managing potential their condition, benefits of and SCI it includeallows improvedmore precise glycaemic insulin control, dosing reduction than inmultiple the hypoglycaemia daily injections unawareness, (MDI) [58]. lower According insulin doses, to highsystematic absorption, reviews, and potential a lower frequencybenefits of of SCI severe include hypoglycaemia improved glycaemic [59–61]. Duecontrol, to the reduction development in the ofhypoglycaemia sensor augmented unawareness, insulin therapy lower insulin with or doses, without high suspend absorption, functions and a [lower62,63], frequency the T1DM of control severe andhypoglycaemia quality of life [59–61]. for patients Due haveto the significantly development enhanced of sensor [64, 65augmented]. Moreover, insulin SCI is therapy most successful with or without suspend functions [62,63], the T1DM control and quality of life for patients have significantly enhanced [64,65]. Moreover, SCI is most successful in individuals motivated to manage their condition and supported by a multidisciplinary team with expertise in the delivery of SCI [66]. In contrast, inhalable insulin is a powdered form of insulin, delivered with an inhaler into the lungs where it is absorbed [67].
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In general, inhaled insulins absorb more rapidly than SCI insulin, with faster peak concentration in serum and more rapid metabolism [68]. Sanofi-Aventis developed the first commercial inhaled insulin product (Exubera), which was approved by the Food and Drug Administration (FDA) and European Medicines Agency (EMA) in 2006 and marketed by the Pfizer [69]. Although Exubera offered the advantage of painless insulin administration by the pulmonary route of administration, its pharmacokinetics (PK) and pharmacodynamics (PD) (i.e., PK/PD) characteristics were similar to the SCI injected rapid-acting insulin analogs (aspart, glulisine, and lispro) and, thus, offered no additional clinical benefit in postprandial glycemic control [70]. Furthermore, the inhaler device was large and the handling procedure for insulin administration was cumbersome [71,72]. Afrezza, an inhaled insulin with ultra-rapid PK/PD properties that enable improved postprandial glycemic control in adults with T1DM or T2DM has been suggested as a promising tool [73]. Improvements in the PK/PD characteristics of today’s SC insulins provide more physiological coverage of basal and prandial insulin requirements than inhaled insulin, that why SC is most widely used. Furthermore, the treatment with SC offers a safe and efficacious option for managing diabetes in patients with T1DM and T2DM [74]. The inhaled insulin delivery may cause safety issues in lungs. We refer interested readers for more detailed understanding about both these two insulin methods to the latest findings in recent studies [75–80]. Pharmacokinetics deals with the absorption and distribution process of the insulin in a human body. Insulin is absorbed into the
Appl. Syst.blood Innov. stream2020, 3directly, 31 [81]. The rate of the absorption truly depends on the state of insulin, 8volume of 36 of the injection, and rate of the blood flow. It has been reported in literature that the absorption rate decreases with an increase in the concentration and the volume. Existing studies demonstrated that in individualsinhaled insulin motivated can toabsorb manage faster their in conditionthe human and body supported [82]. Pharmaco by a multidisciplinarydynamics deals team with with effect of expertiseinsulin in theon the delivery human of body. SCI [ 66It ].is basically In contrast, called inhalable the euglycaemic insulin is clamp a powdered study, formand glucose of insulin, infusion deliveredrate is with used an to inhaler represent into the the phar lungsmacodynamics where it is absorbed of an insulin [67]. [83].
Figure 5. Comparison of the inhaled insulin with the subcutaneous (SC) injection [45].
In general, inhaledFigure 5. insulins Comparison absorb of the more inhaled rapidly insulin than with SCI the insulin, subcutaneous with faster (SC) peak injection concentration [45]. in serum and more rapid metabolism [68]. Sanofi-Aventis developed the first commercial inhaled insulin3.4. product Multiple (Exubera), Daily Insulin which Therapy was approved by the Food and Drug Administration (FDA) and EuropeanThe Medicines most renowned Agency (EMA)method in of 2006insulin and therapy marketed consists by the of the Pfizer regular [69]. periodic Although injection Exubera of basal offered(baseline) the advantage insulin of painlessmultiple insulin times administrationin a day—known by the pulmonaryas multiple route daily of administration, insulin injections its pharmacokinetics(MDI)—supported (PK) by and the pharmacodynamics additional insulin (PD) doses (i.e., PK(boluses),/PD) characteristics and oral gl wereucose similar or glucagon to the as SCI injectedrequired rapid-acting to maintain insulin normoglycemic analogs (aspart, conditions glulisine, (e.g., and lispro)at mealtimes) and, thus, [84]. offered While no additionalcalculating the clinicalrequired benefit inbasal postprandial and bolus glycemic insulin control doses, [70 practical]. Furthermore, guidelines the inhaler need deviceto be wasfollowed. large andDue the to the handlingsignificant procedure complications, for insulin administrationthere is now an was array cumbersome of options/factors [71,72]. that Afrezza, allow anfor inhaled the personalization insulin with ultra-rapidand situational PK/PD evaluation properties of that the enable treatments improved [84]. postprandial MDI using glycemic short- and control long-acting in adults withdoses are T1DM or T2DM has been suggested as a promising tool [73]. Improvements in the PK/PD characteristics of today’s SC insulins provide more physiological coverage of basal and prandial insulin requirements than inhaled insulin, that why SC is most widely used. Furthermore, the treatment with SC offers a safe and efficacious option for managing diabetes in patients with T1DM and T2DM [74]. The inhaled insulin delivery may cause safety issues in lungs. We refer interested readers for more detailed understanding about both these two insulin methods to the latest findings in recent studies [75–80]. Pharmacokinetics deals with the absorption and distribution process of the insulin in a human body. Insulin is absorbed into the blood stream directly [81]. The rate of the absorption truly depends on the state of insulin, volume of the injection, and rate of the blood flow. It has been reported in literature that the absorption rate decreases with an increase in the concentration and the volume. Existing studies demonstrated that inhaled insulin can absorb faster in the human body [82]. Pharmacodynamics deals with effect of insulin on the human body. It is basically called the euglycaemic clamp study, and glucose infusion rate is used to represent the pharmacodynamics of an insulin [83].
3.4. Multiple Daily Insulin Therapy The most renowned method of insulin therapy consists of the regular periodic injection of basal (baseline) insulin multiple times in a day—known as multiple daily insulin injections (MDI)—supported by the additional insulin doses (boluses), and oral glucose or glucagon as required to maintain normoglycemic conditions (e.g., at mealtimes) [84]. While calculating the required basal and bolus Appl. Syst. Innov. 2020, 3, 31 9 of 36 insulin doses, practical guidelines need to be followed. Due to the significant complications, there is now an array of options/factors that allow for the personalization and situational evaluation of the treatments [84]. MDI using short- and long-acting doses are currently the main strategies of the insulin administration in this population. Depending upon the scenarios, some injections are developed as a mix of rapid acting (i.e., quick onset and peak times with short duration) and long acting (i.e., delayed onset time, low or no peak, and long duration) insulin to provide both basal and bolus action from a single injection, thereby reducing the number of injections required per day [85,86]. In addition, in some cases, it may be helpful to perform islet transplantation or that of the pancreas, in place of insulin therapy to significantly lower the treatment costs [85]. Generally, MDI comprise of three or more injections per day. It contains one injection of long-acting (LA) insulin in the evening, and an injection of the short-acting (SA) insulin ahead of every meal. LA insulin is drafted in such a way that it delivers insulin steadily and remains in the body for around 24 h. Meanwhile, the SA insulin needs to be adjusted to match the meal using the insulin-to-carbohydrate ratio [87]. The presentation of MDI and its use in diabetes control and complications trials (DCCT) study has been the ideal case to protect the patients with T1DM. The recent evolution of automated bolus calculations for the MDI is available to help patients to perform complex calculations that are required for functional insulin therapy (FIT) [88,89]. But there are some limitations of MDI to be considered: those patients who use very small amount of insulin doses or are insulin-sensitive may conflict with the MDI as it comes up with the limitations and accuracy’s issues. Similarly, for patients who require large doses, the use of continuous subcutaneous insulin infusion (CSII) may be very helpful from the pharmacodynamics aspect. Continuous infusion works better on delivery of basal insulin rather than using a large subcutaneous depot. MDI is not very effective on those who eat frequently or living soft lifestyle, demanding a large number of injections of the SA insulin, and it becomes difficult to manage through MDI [88]. The Hypo-Ana research study shows that using an analogue-based regimen decreases the severe hypoglycemia in patients with impaired knowledge of hypoglycemia [88,89]. Data also suggests it is being taught already as a way of adjusting the insulin, but many patients ignore the fact and underestimate the insulin doses face difficulty while calculating appropriate amount of insulin adjustments and which acts like a barrier. In early study, the use of bolus calculator recommended reduced errors of insulin and fear hypoglycemia [90,91]. The use of a bolus automated calculator is linked with revised Hba1c and reduced glycemic fluctuations even in the younger patients with T1DM on MDI [92]. The list of distinct categories of the insulin available in medicine (adopted from [93]) is summarized in Table1.
Table 1. Description about distinct types of the insulin available in medicine for T1DM treatment.
Type of Insulin Time Action Profile Dose Begins from the 30-min after the subcutaneous 3 times in a day, 30 min before Short acting with reaching peak action in 2–4 h taking a meal Once daily subcutaneous, at the Long acting Beyond 24 h and up to 36 h same time with at least 8h interval between consecutive doses Generally, 4–20 min after subcutaneous injection Three times a day up to 15 min Rapid acting with peak at 20–30 min. before food intake Peak onset from 4–6 h, with the duration of action Intermediate acting 1 or 2 time daily subcutaneous until 14–16 h
3.5. Continuous Subcutaneous Insulin Therapy Insulin pump therapy also known as continuous subcutaneous insulin infusion (CSII) is a way of providing intensive insulin therapy which consistently leads to enhances glucose and reduced hypoglycemia. CSII was developed about 40 years ago. CSII systems are portable pump therapy devices that are generally constructed as a combination of an onboard insulin reservoir, an infusion apparatus Appl. Syst. Innov. 2020, 3, 31 10 of 36
Appl. Syst. Innov.2020, 3, x FOR PEER REVIEW 10 of 35 (tubing and cannula), and an electromechanical infusion pump [94,95]. According to numerous studies, devices that are generally constructed as a combination of an onboard insulin reservoir, an infusion these systems can be operated easily using the synthetic human insulin or rapid-acting insulin analogs apparatus (tubing and cannula), and an electromechanical infusion pump [94,95]. According to (RAIA),numerous with studies, the help these of RAIA, systems it provides can be superioroperated performance easily using tothe the synthetic synthetic human human insulin insulin or [94 ]. Inrapid-acting most cases, CSIIinsulin uses analogs the same (RAIA), basal with dosage the help as MDI,of RAIA, with it theprovides basal supe insulinrior dosage performance applied to the more consistentlysynthetic human over the insulin day in [94]. CSII In [most95]. cases, CSII uses the same basal dosage as MDI, with the basal insulinThe CSIIdosage isan applied efficient more self-management consistently over tool the forday T1DM in CSII patients. [95]. It is recommended that insulin therapyThe should CSII initiateis an efficient at the self-management start of the week, tool it isfo becauser T1DM patients. patient has It is access recommended to the clinical that insulin help for thetherapy rest of should the week initiate [96]. at In the fact, start across of the Europe,week, it is there because are lesspatient than has 30% access T1DM to the patients clinical whichhelp for are usingthe rest insulin of the pumps, week while[96]. In in fact, the across USA, theEurope use, ofthere insulin are less pump than is 30% relatively T1DM higherpatients [97 which]. The are key dominanceusing insulin of insulin pumps, pumps while in is the the USA, additional the use flexibility, of insulin allowingpump is relatively patients tohigher adjust [97]. basal The insulin key indominance response to of theinsulin requirement pumps is the changes additional due flexibility, to illness, allowing alcohol patients and exercise. to adjust Many basal pumpsinsulin in also provideresponse on-board to the requirement automated boluschanges calculators, due to illness, allowing alcohol persistent and exercise. boluses Many for correctionspumps also byprovide the day. Moreover,on-board wellbeing automated and bolus increased calculators, flexibility allowing using persistent CSII in patients boluses may for increase corrections their by attachment the day. to intensifiedMoreover, therapy wellbeing [98 and]. A increased short randomized flexibility using trial revealedCSII in patients that increased may increase glucose their in attachment the target to but toointensified short to report therapy HbA1c [98]. A levels short [ 99randomized]. Despite thetrial fact revealed that CSII that isincreased effective, glucose it must in be the appropriately target but maintainedtoo short to and report used, HbA1c as device levels [99]. performance Despite the heavily fact that depends CSII is effective, on proper it must operation be appropriately (i.e., timely replacementmaintained of and consumables) used, as device to avoid performance failure modes heavil suchy depends as impeded on proper or clogged operation infusion (i.e., pathways, timely replacement of consumables) to avoid failure modes such as impeded or clogged infusion pathways, which can lead to the insulin deficiency and hyperglycemia. The tools used by the T1DM subjects which can lead to the insulin deficiency and hyperglycemia. The tools used by the T1DM subjects for for insulin dosing are summarized in Figure6, and the detailed description about each method /tool, insulin dosing are summarized in Figure 6, and the detailed description about each method/tool, and their advantages and disadvantages are summarized by Rima et al. [100]. and their advantages and disadvantages are summarized by Rima et al. [100].
FigureFigure 6. 6.Overview Overview of of the the tools tools usedused byby T1DMT1DM subjects for for insulin insulin dosing dosing (adopted (adopted from from [100]). [100 ]).
4. Closed4. Closed Loop Loop Administration Administration of of InsulinInsulin CurrentCurrent treatment treatment methods methods such such as as SC SC injections injections and and continuous continuous deliverydelivery ofof insulininsulin cancan resultresult in frequentin frequent variations variations in the in BG the levels BG levels due todue their to thei open-loopr open-loop nature nature [101 [101].]. In order In order to keep to keep a stable a stable basal glycemiabasal glycemia with the with continuous the continuous insulin insulin infusion, infusi weon, require we require a feedback a feedback system system [102]. [102]. The mainThe main aim of theaim feedback of the feedback system issystem to maintain is to maintain a set point a set po whichint which is predefined. is predefined. Variable Variable transfer transfer functions functions like proportional,like proportional, integral integral or derivative or derivative terms areterms used are to used implement to implemen a feedbackt a feedback system system [102]. The[102]. diabetes The controldiabetes and control complications and complications trial (DCCT) trial published (DCCT) publ in 1993ished showed in 1993 thatshowed it is that very it importantis very important to tightly controlto tightly the BG control in a humanthe BG bodyin a human [103]. Thebody trial [103]. showed The trial that showed there is that an increased there is an risk increased of hypoglycemia risk of byhypoglycemia combining the by results combining of SC injectionsthe results and of SC insulin injections pumps and [103 insulin]. A person pumps with [103]. T1DM A person has always with a T1DM has always a long-term risk related to hyperglycemia, and short-term risks of the long-term risk related to hyperglycemia, and short-term risks of the hypoglycemia, so they need to have hypoglycemia, so they need to have a tight BG control. However, the T2DM patients’ needs an a tight BG control. However, the T2DM patients’ needs an insulin treatment when oral anti-diabetic insulin treatment when oral anti-diabetic agent and changing lifestyle do not provide glucose agent and changing lifestyle do not provide glucose control [104]. A closed-loop AP system shown in control [104]. A closed-loop AP system shown in Figure 7a,b requires three main things: (i) a glucose Figure7a,b requires three main things: (i) a glucose sensor or continuous glucose monitor (CGM), (ii) sensor or continuous glucose monitor (CGM), (ii) an insulin pump, and (iii) a control device that an insulin pump, and (iii) a control device that receives CGM values and uses a control algorithm to receives CGM values and uses a control algorithm to convey signal to the insulin pump for conveyappropriate signal toamount the insulin of insulin pump delivery for appropriate [104]. amount of insulin delivery [104].
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(a) (b)
FigureFigure 7. 7. ExampleExample of the the closed closed loop loop insulin insulin delivery delivery system system using using artificial artificial pancreas pancreas (AP) [104]. (AP) ( [a104) ]. (a)Abstract Abstract overview overview of ofAP AP system system components. components. (b) Detailed (b) Detailed overview overview of the of AP the system. AP system.
DiDifferentfferent control control algorithmsalgorithms have have been been proposed proposed in inliterature literature for forclosed closed looploop administration administration of ofinsulin insulin so so far, far, but but two two of of the the most most commonly commonly used used algorithms algorithms are: are: (i) (i) proportionalproportional integral integral control control (PID)(PID)- it- regulatesit regulates insulin insulin by noticingby noticing variations variations from from the targetthe target glucose glucose levels, levels, and (ii) andmodel (ii) predictivemodel controlpredictive (MPC) control- it regulates(MPC)- it theregulates insulin the by insulin minimizing by minimizing the diff erencethe difference of forecasted of forecasted and target and target glucose levelsglucose [105 levels]. The [105]. different The different control challenges control challeng whiches need which to need be considered to be considered for the APsfor the [106 APs] are: [106] (i) in theare: closed (i) in loop the closed system, loop insulin system, is delivered insulin is when deliv thereered when is only there glucose is only deviation glucose without deviation consideration without ofconsideration information aboutof information the meal size,about and the timing; meal size, (ii) the and hypoglycemia timing; (ii) the condition hypoglycemia is risky condition as it can causeis coma,risky seizures, as it can andcause mental coma, illness.seizures, Also, and hyperglycemiamental illness. Also, is not hyperglycemia good as it causes is not cardiovascular good as it causes disease andcardiovascular other chronic disease diseases. and Therefore,other chronic these diseases. conditions Therefore, must bethese considered; conditions (iii) must diff beerent considered; treatments for(iii) diabetes different patients treatments have for diff erentdiabetes requirements. patients have In different some cases, requ rapidirements. insulin In some delivery cases, is required,rapid andinsulin vice versa.delivery Exercise is required, can also and create vice versa. the hypoglycemia Exercise can also condition, create the so allhypoglycemia of these physical condition, factors so are importantall of these to considerphysical whilefactors designing are important an AP system;to consider (iv) whenwhile creatingdesigning a rapidan AP insulin system; delivery (iv) when control creating a rapid insulin delivery control algorithm mostly the maximum BG lowering effect occur algorithm mostly the maximum BG lowering effect occur after up to 90–120 min. When designing after up to 90–120 min. When designing control algorithm this time range should be considered. control algorithm this time range should be considered. Furthermore, sometimes there occurs noise in Furthermore, sometimes there occurs noise in the sensor measurements so different estimation the sensor measurements so different estimation techniques should be employed for compensating techniques should be employed for compensating these noise values. Also, the self-calibration these noise values. Also, the self-calibration methods with self/auto correction ability are required for methods with self/auto correction ability are required for the success of the APs. the success of the APs. 5. Proportional Integral Derivative (PID) Controller 5. Proportional Integral Derivative (PID) Controller The proportional integral derivative (PID) controller is one of the most widely used controllers in industrialThe proportional applications. integral In derivativeT1DM treatment (PID) controllerand control, is oneit is of used the mostto emulate widely β used-cell’scontrollers insulin β insecretion industrial in applications.the body in response In T1DM to the treatment glucose, and it control, is also called it is used external to emulate physiological-cell’s insulin insulin secretiondelivery in(e-PID) the body [107,108]. in response The insulin to the is glucose,rapidly secreted and it isby also the calledβ -cells external in the bolus physiological during the insulinfirst deliveryphase in (e-PID) response [107 to,108 the]. increased The insulin BG is(proportio rapidlynal secreted component), by the βand-cells in the in thesecond bolus phase during (integral the first phasecomponent), in response it is released to the increased slowly, called BG (proportional basal insulin, component),to account for andthe insulin in the secondrequired phase in between (integral component),meals to keep it isBG released at a normal slowly, level called [108,109]. basal In insulin, order toto accountreduce the for hypoglycemic the insulin required cases, that in betweenis, to mealsreduce to over keep delivery BG at a of normal the insulin, level [108insulin,109 ].feedback In order was to included reduce the to hypoglycemicmake the controller cases, more that is, torobust reduce [107,110,111]. over delivery For of critically the insulin, ill patients, insulin Ch feedbackee et al. [112] was developed included a to rule-based make the PID controller controller. more robustMarchetti [107, 110et al.,111 [113]]. For developed critically a switching ill patients, PID Chee controller et al. [ 112using] developed the Hovorka a rule-based model. The PID developed controller. Marchetticontroller et works al. [113 in] such developed a way athat switching the controller PID controller is turned usingon only the after Hovorka meals model.and is off The before developed the controllermeal bolus. works Various in such schemes a way for that tuning the controller the hybrid-PID is turned and on PID only controller after meals parameters and is o fftobefore obtain the mealsignificantly bolus. Various optimized schemes results forare tuningdeveloped the hybrid-PIDusing soft computing and PID techniques controller parameterssuch as the cuckoo to obtain significantlysearch algorithm optimized [114], genetic results algorith are developedm [115], usingand fire-fly soft computing algorithm [116]. techniques such as the cuckoo searchHuyett algorithm et [al.114 [117]], genetic conducted algorithm experiments [115], and in fire-fly silico algorithmfor inter-peritoneal [116]. (IP; deliver in or administerHuyett etthrough al. [117 ]the conducted abdominal experiments cavity or peritoneum) in silico for inter-peritonealinsulin delivery (IP; and deliver IP glucose in or administersensing (IP–IP) for an implantable AP [118,119]. The working mechanism of the PID controller is shown in through the abdominal cavity or peritoneum) insulin delivery and IP glucose sensing (IP–IP) for
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Appl. Syst. Innov.2020, 3, x FOR PEER REVIEW 12 of 35 an implantable AP [118,119]. The working mechanism of the PID controller is shown in Figure8. TheFigure brief 8. overviewThe brief ofoverview the PID workingof the PID is summarizedworking is summarized as: the PID controlleras: the PID utilizes controller proportional, utilizes integralproportional, and derivative integral gainand toderivative control a gain process to variablecontrol (systema process/process variable output). (system/process They obtained output). input fromThey theobtained process input output from and the compared process itoutput with a and set pointcompared value it to with calculate a set error point signal value or to deviations. calculate Errorerror /signaldeviation or deviations. value was processedError/deviation using value the proportional, was processed derivative using the and proportional, integrationcontrollers. derivative Thisand integration input from controllers. the PID controller This input was from used the to controlPID controller the process was variable.used to control To stabilize the process a PID controllervariable. isTo very stabilize challenging a PID because controller it requires is very the proper challenging understanding because of theit proportional,requires the integral,proper andunderstanding derivative gainof the values. proportional, There exist integral, plenty and of methods derivative for gain PID controllervalues. There tuning. exist PID plenty control of algorithmsmethods for are PID the controller simplest tuning. way to PID design control a robust algorithms control are system the simplest for the way T1DM to design treatment a robust and control.control system Turksoy for et the al. [T1DM120] presented treatment a comprehensiveand control. Turksoy review et about al. [120] the adaptivepresented control a comprehensive techniques andreview their about use inthe the adaptive AP systems. control Klemen techniques et al. and [121 th]eir summarized use in the theAP mostsystems. recent Klemen advances et al. in [121] the closed-loopsummarized systems the most in recent adolescents advances and in children the clos withed-loop T1DM, systems using in both adolescents single- and and dual-hormone children with closed-loopT1DM, using systems. both single- and dual-hormone closed-loop systems.
Figure 8. Conceptual overview of the proportional integral derivative (PID) controller used in T1DM Figure 8. Conceptual overview of the proportional integral derivative (PID) controller used in T1DM treatment and control. treatment and control.
Trevor etet al.al. [[122]122] proposedproposed aa newnew insulininsulin controllercontroller fromfrom aa complementarycomplementary metalmetal oxideoxide semiconductor microprocessor microprocessor (CMOS) (CMOS) which which works works on on wake-up wake-up cycle; cycle; each each cycle cycle occurs occurs afterafter 2.86 2.86ms. The ms. CMOS The CMOS operational operational amplifier amplifier and direct and directcurrent current (DC) driver (DC) driverprovide provide voltage voltage to motor to from motor 0 fromto 7.5 0volt to 7.5in 29.41 volt inmV. 29.41 A feedback mV. A feedback loop is used loop having is used three having parts three as outlined parts as in outlined Section in4. The Section input4. Theof the input system of the is systemoutput isof outputglucose of sensor, glucose and sensor, outp andut of output the system of the is system the input is the to input the insulin to the insulinpump. pump.Shainer Shaineret al. [123] et al.developed [123] developed a model and a model controller and controllerdesign for designconcentration for concentration of glucose, ofthe glucose, system theinstructs system the instructs insulin the pump insulin how pump much how insulin much insulin is required is required to be to beinjected. injected. A APID PID controller controller is constructed by computer-aided design (CAD) tools, and 81 mgmg/dL/dL is taken as a normal glycemia set point. StrategiesStrategies are are implemented implemented in ain discrete a discrete manner. manner. The device The hasdevice three has major three parts: major (i) mechanical parts: (i) pump,mechanical (ii) in pump, vivo glucose (ii) in vivo sensor, glucose and sensor, (iii) a mathematical and (iii) a mathematical algorithm. algorithm. The pump The is driven pump using is driven the readingsusing the of readings a sensor. Itof isa the sensor. classic It PID is controllerthe classic which PID iscontroller based upon which the CADis based methodology upon the having CAD amethodology dynamic model having of the a controldynamic system. model CAD of isthe based control upon system. frequency CAD response is based (FR) upon tool [124frequency]. responseAn expert (FR) tool PID [124]. controller is designed to regulate the BG levels. It uses clinical sliding table technique. The slidingAn expert table PID contains controller multiple is designed insulin to concentration regulate the rates. BG levels. The slidingIt uses tableclinical implements sliding table the proportionaltechnique. The control sliding scheme table and contains this table multiple is improved insulin with theconcentration condition of therates. intended The sliding patient [table125]. Theimplements proportional the proportional integral (PI) controller control scheme is the most and common this table used is improved controller inwith it. Thethe Pcondition and I controller of the areintended implemented patient for[125]. the The individual proportional purposes. integral There (P areI) controller many methods is the tomost tune common the PI controller, used controller one of thosein it. The is trial P and and I controller error method. are implemented In this method, for th thee individual gains of the purposes. proportional There andare many integral methods were set to randomlytune the PI to controller, boost the performanceone of those of is insulin trial and delivery error system.method. Controller In this method, designers the improved gains of thethe steadyproportional and transient and integral achievement were set of randomly the PI controller to boost bythe introducing performance fuzzy of insulin theory delivery [108]. Sanaul system. et al.Controller [126] explained designers a PID improved controller strategythe steady which and is evaluatedtransient inachievement silico using theof physiologicalthe PI controller Hovorka by model.introducing There fuzzy aresome theory key [108]. points Sanaul of the et strategy: al. [126] (i) explained switching a strategyPID contro forller the PIDstrategy initiating, which(ii) is aevaluated novel time in varyingsilico using set point the trajectory,physiological (iii) reducingHovorka themodel. sensor There noise are and some noise key derivative points withof the a filter,strategy: and (i) (iv) switching a strategy strategy is used for to the tune PID the initiating, controller. (ii) The a novel proposed time varying PID strategy set point is widely trajectory, used (iii) in reducing the sensor noise and noise derivative with a filter, and (iv) a strategy is used to tune the controller. The proposed PID strategy is widely used in the industrial applications. The PID controller is best because it mimics the first and second phase responses. The controller is based
Appl. Syst. Innov. 2020, 3, 31 13 of 36 the industrial applications. The PID controller is best because it mimics the first and second phase responses. The controller is based upon novel PID controller. The authors explained various control strategies, which are: (i) bolus only (ii) PID control only (iii) bolus plus PID control (iv) bolus plus PID control with switching criteria, and (v) bolus plus PID control with switching criteria and time varying glucose set point which are called improved PID (IPID). Delgado et al. [127] discussed a fuzzy logic-based controller for glucose regulation in the T1DM patients. To get rid of daily injection insulin and to obtain professional education about the treatment of the disease, Mamdani type fuzzy logic controller is simulated. Chengwei et al. [128] discussed an IPID controller and explained some new features of it. The controller is on “silico” using the physiologic model of Hovoraka which is the best glucose–insulin dynamics model. The key features of the proposed control strategies are (i) switching strategy, (ii) novel time-varying set point (iii) noise and derivate filters, and (iv) systematic controller tuning strategy. The IPID controller of this type are built upon the novel PID controller and bolus injection for the meal [128]. Maleki et al. [129] described a glucose insulin system model with only few parameters. The model is designed using Mamdani type fuzzy structure. It has two input and one output variables. The inputs are error and its rate, and output is rate of the insulin infusion. To make the mathematical model, the Stolwijk–Hardy glucose-insulin interaction model is employed. The exogenous insulin infusion term is added in the modified model to yield superior results. The glucose dynamics are formally expressed as:
dG Ag = µg + Pg πG νGI, G ϑ (1) dt − − ≤ dG Ag = µg + Pg πG νGI σ(G ϑ), G > ϑ (2) dt − − − − The insulin dynamics are formally expressed as:
dI C = µ γI, G ω (3) i dt i − ≤ dI C = µ γI + δ(G ω), G > ω (4) i dt i − − where G(t) represents instantaneous BGL in mg/mL, I(t) denotes the instantaneous blood insulin level mU/mL, µG(t) represents exogenous glucose infusion in mg/h, µI(t) denotes the exogenous insulin infusion in mU/h, Ag represents the glucose capacitance in the extracellular space, Ci: represents the insulin capacitance in the extracellular space, PG(t) is a glucose inflow into blood in mg/h, π is tissue usage rate of the glucose that is independent of I(t), v denotes the tissue usage rate of glucose that is dependent on I(t), γ: Insulin destruction rate, δ represents the insulin production rate by the pancreas, ϑ is a threshold for renal discharge of the glucose, Φ is a threshold for pancreatic production of an insulin, and σ denotes the glucose excretion rate [130]. In the open loop control systems, specialists direct a pre-determined dose of insulin hypodermically based on an invasive method of finger prick GM on a daily basis 3~4 times managed by the patients. This procedure is painful, inappropriate, and untrustworthy because of the fuzzy evaluation of the type and amount of insulin dosage. The semi-closed loop control is dissatisfactory, and unable to adjust the BG level properly. It also experiences long sampling as it depends upon infrequent BG readings. The closed loop control is the most effective method. It acts as an AP, and it can upgrade the life expectancy of the patients. AP enables diabetic patients to maintain the normal BG levels by providing accurate amount of the insulin at the right time without human interaction, even when there is need of human-based decision [131]. The term AP is becoming a reality by using a closed loop strategy. There are two loop strategies inner loop and outer loop. The inner loop provides an amount of both rapid and intermediate acting insulin (RSAI and ILAI), and outer loop adjusts the max amount Appl. Syst. Innov. 2020, 3, 31 14 of 36 of the insulin provided in a time scale of the days [132]. Figure9 explains Simulink model of a normal personAppl. Syst. using Innov. a PID2020, controller3, x FOR PEER [130 REVIEW]. 14 of 35
FigureFigure 9. 9.Schematic Schematic diagram diagram ofof thethe fuzzy logic controller controller (adopted (adopted from from [133]). [133]). 6. Linear and Non-Linear Insulin Infusion Control Schemes 6. Linear and Non-Linear Insulin Infusion Control Schemes This section explains the seven different types of the linear and non-linear insulin infusion control This section explains the seven different types of the linear and non-linear insulin infusion schemes used in the APs. We present formalization and general description for the clarity and better control schemes used in the APs. We present formalization and general description for the clarity understandingand better understanding of each scheme. of each scheme. 6.1. Self-Tuning Control 6.1. Self-Tuning Control AA self-tuning self-tuning controller controller isis basicallybasically aa non-linearnon-linear control control scheme scheme which which was was developed developed on ona a micro-controllermicro-controller unit unit (MCU) (MCU) [ 134[134].]. ThisThis schemescheme was verified verified through through computer computer simulations, simulations, and and it it concludedconcluded that that glycemia glycemia control control isis insensitiveinsensitive to changes in in a a patient’s patient’s behavior; behavior; also, also, the the insulin insulin concentrationconcentration it it produced produced was was the the moremore physiological.physiological. A A discrete-time discrete-time model model is isassumed assumed for for the the controlledcontrolled system system to to implement implement a a self-tuning self-tuning controller.controller.
Xn 1 Xm+h 1 − − y = fi yk i + giuk i + d (5) k+h i=0 i=0 yk + h = − + −+d (5) where uk and yk are the kth samples of u(t) and y(t), n and m are number of poles and zeros, respectively. Self-tuning control uses an estimator, and the coefficients in Equation (5) are estimated by where uk and yk are the kth samples of u(t) and y(t), n and m are number of poles and zeros, therespectively. least-squares Self-tuning method; control it compares uses an the estimator, true output and ofthe the coefficients model and in Equation controlled (5) systemsare estimated so that estimationby the least-squares is sensitive method; to slow it changes compares in thethe patienttrue output response. of the model and controlled systems so that
estimation is sensitive to slow changes in the patient response.2 J = y y + Q u 2 (6) k k+h re f k Jk = ( −− ) +Q (6) wherewhereQ isQ theis the arbitrary arbitrary weighting weighting factor. factor. Putting Putting Equation Equation (5) (5) in in Equation Equation (6) (6) and and equating equating to to zero zero the derivative of J with respect to u , result is given in Equation (7). the derivativek of Jk with respectk to uk, result is given in Equation (7).
Xn 1 Xm+h 1 1 − − uk = 1 yref fi yk i giuk i d (7) g + Q/g − i=0 − − i=0 − − k = 0 0 (yref − − − d) (7) + / where arbitrary parameters h, m, n and Q and sampling time characterize the controller in Equation (7). whereThe arbitrary self-tuning parameters controller h, hasm, n the and following Q and sampling structure time (see characterize Figure 10 )the where controller both controllerin Equation and estimator(7). work as a self-tuner for accurate insulin infusion in a human body. The self-tuning controller has the following structure (see Figure 10) where both controller and estimator work as a self-tuner for accurate insulin infusion in a human body.
Appl. Syst. Innov. 2020, 3, 31 15 of 36 Appl. Syst. Innov.2020, 3, x FOR PEER REVIEW 15 of 35
FigureFigure 10. 10.Self-tuning Self-tuning controller controller with with the the help help of of estimates estimates and and adjustments adjustments [ 134[134].]. The controller in Figure 10 is characterized by the transfer function, which is given below. The controller in Figure 10 is characterized by the transfer function, which is given below.
Ks G(s) = (8) G(s) = + 1 τ s (8) where Ks is arbitrary coefficient which can be figured out according to the yref. where Ks is arbitrary coefficient which can be figured out according to the yref. 6.2. Adaptive Control 6.2. Adaptive Control This control method is used by the controllers which must adapt to a controlled system with varyingThis parameters control method which is are used initially by the uncertain. controllers For which adaptive must modeling,adapt to a thecontrolled “Minimal system Model with of Bergmanvarying”[ parameters135] is commonly which usedare initially due to its uncertain. conceptual For simplicity. adaptive Most modeling, of the existingthe “Minimal T1DM Model models of areBergman designed” [135] via is the commonly Bergman model.used due The to T1DM its conceptual model can simplicity. be extended Most for of the the T2DM existing with T1DM ease. Themodels model are has designed two inputs: via the (i) glucoseBergman rate model.p(t), andThe (ii) T1DM the subcutaneously model can be extended injected insulinfor the flowT2DMu(t );with at theease. same The time model this has input two is inputs: the control (i) glucose input rate as well. p(t), and The (ii) output the subcutaneously of the model is injected the plasma insulin glucose flow levelu(t); G(t)at the. The same model time has this three input state is variablesthe control that inpu aret connectedas well. The to theoutput blood of plasma the model which is the are: plasma (i) the bloodglucose glucose level concentrationG(t). The modelG(t) has, (ii) three insulin-excitable state variables tissue that are glucose connected uptake to activity the bloodX(t) plasma, and (iii) which the bloodare: (i) insulin the blood concentration glucose concentrationI(t). Figure 11 G(t) shows, (ii) theinsulin-excitable detailed model tissu of ane glucose adaptive uptake control activity using X(t) the ,
T1DMand (iii) model. the blood insulin concentration. I(t). Figure 11 shows the detailed model of an adaptive control using the T1DM model.G( t) = (p1 + X(t)) G(t) + p1G + p(t) (9) − B . ( ) = X −( 1(t) = +p 2 ( ))X(t) + ( )p3[I ( +t) 1 BI ] + ( ) (10)(9) − − B . ( ) I=(t ) − 2 ( )= n[I(t ) +I 3 ( )] + u(t) − B (10)(11) − − B where GB and IB are the basal pre injection ( ) = level −n ( ) of glucose − B and + insulin ( ) in blood, p1: insulin-independent(11) rate constant of glucose uptake in muscles and liver in (1/min), p2: rate for decrease in tissue glucose upwhere take abilityGB and (in 1IB/ min),are p3:the insulin-dependentbasal pre injection increase level in glucoseof glucose uptake and ability insulin in tissue in perblood, unit p1: of insulin-independent rate constant of glucose uptake in1 muscles1 and liver in (1/min), p2: rate for Appl.insulin Syst. concentration Innov.2020, 3, x FOR above PEER the REVIEW basal level in ((űU/mL)− min− ). 16 of 35 decrease in tissue glucose up take ability (in 1/min), p3: insulin-dependent increase in glucose uptake ability in tissue per unit of insulin concentration above the basal level in ((ʮU/mL)−1 min−1).
Figure 11. TheThe schematic schematic structure of the T1DM model used [135]. [135].
The controller reacts promptly to large and rapid variations in the insulin action [108]. The absorption model is approximated as the exponential equation given below.