Error grid analysis of noninvasive glucose monitoring via gingival cerevicular fluid

In order to realize a noninvasive blood glucose monitor, we monitored the gingival cerevicular fluid (GCF). In this paper, the clinical evaluations were performed on not only normal subjects but also diabetic subjects using a GCF-glucose monitor to determine blood glucose levels. Meal load tests were carried out and the time-course changes in blood glucose level and GCF glucose level were measured continuously. A positive correlation of more than 0.9 was found between blood glucose level and GCF glucose level, necessitating the calibration of individual correlations for every subject. Finally, the performance of the GCF-glucose monitor was evaluated using Error Grid Analysis. As the results, significant information for the glucose level decision was obtained not only for normal subjects, but also for diabetic subjects.     

Blood glucose response to stress hormone exposure in healthy manand insulin dependent diabetic patients: prediction by computer modeling

To establish a qualitative and quantitative model of blood glucose response to stress hormone exposure, healthy subjects (HS) on and off somatostatin (250 micrograms/h) as well as insulin dependent diabetic patients were infused with either epinephrine (E), glucagon (G), cortisol (F), growth hormone (GH) or with a cocktail of these hormones raising plasma stress hormones to values seen in severe diabetic ketoacidosis. The developed input/output model consists of two submodels interconnected in series plus two additional submodels for correction of gains describing both sensitivity of tissue response and utilisation as well as provision of glucose. It was shown and confirmed experimentally that blood glucose response to stress hormones was essentially nonlinear. Furthermore, the mathematical models for healthy subjects and for insulin dependent diabetic patients proved to be of the same structure and differed only in the values of some typical parameters. The model raises the possibility to describe and in part to predict blood glucose response to stress hormone exposure in healthy man and insulin dependent diabetic patients.     

Nanotechnology‐Enabled Closed Loop Insulin Delivery Device: In Vitro and In Vivo Evaluation of Glucose‐Regulated Insulin Release for Diabetes Control

Recently, a new multifunctional, bio‐inorganic nanocomposite membrane with the ability to self‐regulate the release of insulin in response to blood glucose (BG) levels was reported. Herein, the application of this material as part of a small, implantable, closed‐loop insulin delivery device designed to continuously monitor BG concentrations and regulate insulin release is proposed. The insulin delivery device consists of a nanocomposite glucose‐responsive plug covalently bound to an insulin reservoir made of surface‐modified silicone. The plug is prepared with crosslinked bovine serum albumin (BSA) and enzymes (glucose oxidase (GOx) and catalase (CAT)), pH‐responsive hydrogel nanoparticles, and multifunctional MnO₂ nanoparticles. The plug functions both as a glucose sensor and controlled delivery unit to release higher rates of insulin from the reservoir in response to hyperglycemic BG levels and basal insulin rates at normal BG concentration. The surfaces of the device are modified by silanization followed by PEGylation to ensure its safety and biocompatibility and the stability of encased insulin. Our results show that insulin release can be modulated in vitro in response to glucose concentrations. In vivo experiments show that the glycemia of diabetic rats can be controlled with implantation of the prototype device. The glucose‐responsiveness of the device is also demonstrated by rapid drop in BG level after challenging diabetic rats with bolus injection of glucose solution. In addition, it is demonstrated that surface PEGylation of the device is necessary for reducing the immune response of the host to the implanted foreign object and maintaining insulin stability and bioactivity. With this molecular architecture and the bio‐inorganic nanocomposite plug, the device has the ability to maintain normal BG levels in diabetic rats.     

Does Physiological Blood Glucose Control Require an Adaptive Control Strategy?

To test the hypothesis that only an adaptive algorithm would guarantee optimal feedback control of glycemia in insulin-dependent diabetes, fasting chronically diabetic dogs at rest were subjected to short-term artificial beta cell treatment. Insulin was applied intravenously and an oral glucose load was given during the experiment. Employing the same dosing algorithm, three different control strategies were employed in a random order on different days: adaptive control (minimum variance controller, Test A), fixed command control using on-line parameter estimates (Test B), and fixed command control using off-line individually optimized dosage constants (Test C). Comparison was made to nondiabetic control animals. The glycemic profiles were entirely normal in Test A and C, but were distinctly elevated in Test B. The peripheral hyperinsulinaemia could, however, not be avoided by adaptive control. It is concluded that the restoration of physiological blood glucose control in insulin-dependent diabetes requires dosage parameters which are either continually adapted to the actual situation (adaptive control) or are optimized to meet the individual's needs. In the latter case, fixed command control may be employed. Peripheral hyperinsulinaemia cannot be avoided as long as insulin is administered by a posthepatic route.     

Glucose‐Responsive Bioinorganic Nanohybrid Membrane for Self‐Regulated Insulin Release

A bioinorganic nanohybrid glucose‐responsive membrane is developed for self‐regulated insulin delivery analogous to a healthy human pancreas. The application of MnO₂ nanoparticles as a multifunctional component in a glucose‐responsive, protein‐based membrane with embedded pH‐responsive hydrogel nanoparticles is proposed. The bio‐nanohybrid membrane is prepared by crosslinking bovine serum albumin (BSA)–MnO₂ nanoparticle conjugates with glucose oxidase and catalase in the presence of poly(N‐isopropyl acrylamide‐co‐methacrylic acid) nanoparticles. The preparation and performance of this new nanocomposite material for a glucose‐responsive insulin release system is presented. The activity and stability of immobilized glucose oxidase and the morphology and mechanical properties of the membrane are investigated. The enzymatic activity is well preserved in the membranes. The use of MnO₂ nanoparticles not only reinforces the mechanical strength and the porous structure of the BSA‐based membrane, but enhances the long‐term stability of the enzymes. The in vitro release of insulin across the membrane is modulated by changes in glucose concentration mimicking possible fluctuations of blood‐glucose level in diabetic patients. A four‐fold increase in insulin permeation is observed when the glucose concentration is increased from normal to hyperglycemic levels, which returns to the baseline level when the glucose concentration is reduced to a normal level.     

A Multifunctional Pro‐Healing Zwitterionic Hydrogel for Simultaneous Optical Monitoring of pH and Glucose in Diabetic Wound Treatment

Diabetic ulcer is the most common kind of chronic wound worldwide. Though great efforts have been devoted, diabetic ulcer still remains as a challenge that requires constant monitoring and management. In this work, a multifunctional zwitterionic hydrogel is developed to simultaneously detect two fluctuant wound parameters, pH and glucose level, to monitor the diabetic wound status. A pH indicator dye (phenol red) and two glucose sensing enzymes, glucose oxidase (GOx) and horseradish peroxidase (HRP), are encapsulated in the anti‐biofouling and biocompatible zwitterionic poly‐carboxybetaine (PCB) hydrogel matrix. The visible images are collected by a smartphone and transformed into RGB signals to quantify the wound parameters. Results show that the activity and stability of both two enzymes are improved within PCB hydrogel, and the K_cat/K_m value of PCB‐HRP is ≈5.5 fold of free HRP in artificial wound exudate. This novel wound dressing can successfully monitor the pH range of 4–8 and glucose level of 0.1–10 × 10^?3 m . Meanwhile, it also provides a moist healing environment that can promote diabetic wound healing. This multifunctional wound dressing may open vistas in chronic wound management and guide the diabetes treatment in clinical applications.     

A Gait Monitoring System Based on Air Pressure Sensors Embedded in a Shoe

Measurement of ground contact forces (GCFs) provides necessary information to detect human gait phases. In this paper, a new analysis method of the GCF signals is discussed for detection of the gait phases. Human gaits are complicated, and the gait phases cannot be exactly distinguished by comparing sensor outputs to a threshold. This paper proposes a method by fuzzy logic for detecting the gait phases continuously and smoothly. The smooth and continuous detection of the gait phases enables a full use of information obtained from GCF sensors. For advanced rehabilitation systems, this paper also introduces a higher level algorithm that quantitatively monitors the amount of abnormalities in a human gait. The abnormalities detected by the proposed method include an improper GCF pattern as well as an incorrect sequence of the gait phases. To realize the monitoring algorithm, the gait phases are analyzed as a vector and the abnormalities are detected by simple kinematic equations. The proposed methods are implemented by using signals from sensor-embedded shoes called smart shoes. Each smart shoe has four GCF sensors installed between the cushion pad and the sole. The GCF sensor applies an air pressure sensor connected to an air bladder. A gait monitoring system that integrates the proposed methods is shown in this paper and verified for both normal and abnormal gaits.     

Optimal insulin infusion resulting from a mathematical model ofblood glucose dynamics

Mathematical optimization techniques are applied to a simplified mathematical model of blood glucose dynamics to derive insulin infusion programs for the control of blood glucose levels in diabetic individuals. Two particular cases are discussed. First, the insulin infusion program which results in an initially high blood glucose level being reduced to acceptable levels. Second, the control of blood glucose levels following a meal, prior to which blood glucose and net blood-glycemic hormone were at their fasting levels.     

Quantify Glucose Level in Freshly Diabetic’s Blood by Terahertz Time-Domain Spectroscopy

We demonstrate the capability of terahertz (THz) time-domain spectroscopy (TDS) to quantify glucose level in ex vivo freshly diabetic’s blood. By investigating the THz spectra of different human blood, we find out THz absorption coefficients reflect a high sensitivity to the glucose level in blood. With a quantitative analysis of 70 patients, we demonstrate that the THz absorption coefficients and the blood glucose levels perform a linear relationship. A comparative experiment between THz measurement and glucometers is also conducted with another 20 blood samples, and the results confirm that the relative error is as less as 15%. Our ex vivo human blood study indicates that THz technique has great potential application to diagnose blood glucose level in clinical practice.     

正弦调制偏振光无创血糖检测的研究

常规的有创血糖检测方法有较多的局限性,光学无创血糖检测是糖尿病患者自我血糖评估的最佳方法,提出了一种偏振光无创血糖检测方法,将正弦调制偏振光通过血糖引起的微小偏振角的变化转化为电光调制器基频和倍频两个分量的变化,由相关原理高灵敏锁相放大器检测基频信号,控制法拉第线圈电流补偿血糖引起的偏转角变化,利用血糖浓度与法拉第线圈电流的线性关系,计算获得血糖浓度。以LX-20全自动生化分析仪测得的数据作为标准进行对比实验,葡萄糖溶液实验的相关系数为0.9952。研究表明偏振光无创血糖检测方法具有较高的检测灵敏度和准确度,为研制实用的新型无创血糖检测仪打下了基础。     

血糖浓度荧光光谱检测研究

传统血糖检测需从患者静脉取血,给糖尿病人带来了极大的痛苦和经济负担,利用荧光测试技术进行血糖的无创检测研究.通过对不同葡萄糖浓度的全血、血清和不同浓度的红细胞溶液进行系列荧光光谱实验,结果表明全血在720～730 nm附近有明显荧光特征峰,其中720 nm附近特征峰由血细胞引起、730 nm附近特征峰是由糖份引起,且全血和血清中此位置处峰值强度均随血糖浓度变化而规律性变化.实验结果为进一步进行血糖荧光无创检测打下了基础.     

Microscopic investigations in a diabetic rat urinary bladder infected with Trichosomoides crassicauda

Rats are widely used laboratory animals and have several parasites. One of these are helminths, known not only to cause serious effects on the experimental results in healthy subjects, but also in subjects with heavy infections. One of the relatively pathologic helminth is Trichosomoides crassicauda, which lives in the nodules of the urinary bladder. It is known that diabetics are more prone to infections with several microorganisms. Observations in a diabetic rat bladder showed T. crassicauda eggs inside the transitional epithelium, and structural changes in the bladder epithelium were evident. Urinary-bladder tissues taken from streptozotocin-injected diabetic subjects and citrate buffer-injected control subjects were fixed, embedded in araldite and investigated under a light microscope. Distinct changes in the histological structure of a diabetic urinary bladder transitional epithelium were observed after T. crassicauda infection. Many papillomas were formed and the epithelial tissues were completely degenerated. In addition, electron microscopic examinations also revealed degeneration of the subepithelial tissues.     

Universal Glucose Models for Predicting Subcutaneous Glucose Concentration in Humans

This paper tests the hypothesis that a “universal,” data-driven model can be developed based on glucose data from one diabetic subject, and subsequently applied to predict subcutaneous glucose concentrations of other subjects, even of those with different types of diabetes. We employed three separate studies, each utilizing a different continuous glucose monitoring (CGM) device, to verify the model's universality. Two out of the three studies involved subjects with type 1 diabetes and the other one with type 2 diabetes. We first filtered the subcutaneous glucose concentration data by imposing constraints on their rate of change. Then, using the filtered data, we developed data-driven autoregressive models of order 30, and used them to make short-term, 30-min-ahead glucose-concentration predictions. We used same-subject model predictions as a reference for comparisons against cross-subject and cross-study model predictions, which were evaluated using the root-mean-squared error (RMSE) and Clarke error grid analysis (EGA). We found that, for each studied subject, the average cross-subject and cross-study RMSEs of the predictions were small and indistinguishable from those obtained with the same-subject models. These observations were corroborated by EGA, where better than 99.0% of the paired sensor-predicted glucose concentrations lay in the clinically acceptable zone A. In addition, the predictive capability of the models was found not to be affected by diabetes type, subject age, CGM device, and interindividual differences. We conclude that it is feasible to develop universal glucose models that allow for clinical use of predictive algorithms and CGM devices for proactive therapy of diabetic patients.      

Control of Diabetes with Artificial Systems for Insulin Delivery Algorithm Independent Limitations Revealed by a Modeling Study

The causes of the inability of insulin infusion systems to restore normal metabolic conditions in diabetic subjects have been investigated with the aid of modeling and computer simulation. It has been possible to compute, by the model, the so-called minimal insulin profile with peripheral insulin infusion, i. e., the time course of plasma insulin which should be observed in a diabetic subject after an oral glucose test, when insulin is infused in a peripheral vein, in order to have a normal blood glucose profile. This profile allows assessment of the performance of insulin infusion systems by evidencing the relative role of the route of infusion and of the control algorithm on the normalization of metabolic control. It is concluded that the route of infusion is of major importance, while the control algorithm plays a minor role. The importance of modeling and simulation in circumstances, which make in vivo experiments; unfeasible or unethical, is emphasized along with the clinical and physiological relevance of the results.     

Prediction of interstitial glucose level

Glucose is an important source of energy for cells. In clinical practice, we measure glucose level in blood and interstitial fluid. Each method has its pros and cons, and both levels correlate with each other. As the body tries to maintain the glucose level within a particular range to avoid adverse effects, it is desirable to predict future glucose levels in order to aid provided health care. We can see this desire in research, e.g., research on glucose transporters of cells. As yet another example, we can see it with diabetic patients, patients in a metabolic intensive care unit, particularly. In this paper, a glucose level prediction method is proposed.     

A semiclosed-loop algorithm for the control of blood glucose levelsin diabetics

In this paper, a theoretical analysis of the control of plasma glucose levels in diabetic individuals is undertaken using a simple mathematical model of the dynamics of glucose and insulin interaction in the blood system. Mathematical optimization techniques are applied to the mathematical model to derive insulin infusion programs for the control of blood levels in diabetic individuals. Based on the results of the mathematical optimization, a semiclosed-loop algorithm is proposed for continuous insulin delivery to diabetic patients. The algorithm is based on three hourly plasma glucose samples. A theoretical evaluation of the effectiveness of this algorithm shows that it is superior to two existing algorithms in controlling hyperglycemia. A glucose infusion term representing the effect of glucose intake resulting from a meal is then introduced into the model equations. Various insulin infusion programs for the control of plasma glucose levels following a meal are then assessed. The theoretical results suggest that the most effective short-term control is achieved by an insulin infusion program which incorporates an injection to coincide with the meal.     

Fast Hartley transforms for spectral analysis of ultrasound Dopplersignals

Spectral analysis of Doppler ultrasound is known to yield valuable information to assess the state of circulation in the peripheral blood vessels. In the past, the raw Doppler data have been directly input into a dedicated spectrum analyzer or transformed on a microcomputer using the fast Fourier transform (FFT) technique. In the present study, the first Hartley technique is used to transform on a microcomputer to the digitized Doppler data obtained from a normal common carotid artery is presented and the resulting spectra are compared to those obtained by using the Cooley-Tukey FFT algorithm. The Hartley transform has the advantages of being a purely real-numbered transform; therefore, for real Doppler data, it is not only more conceptually straightforward, but also requires less computer memory, is simpler to calculate, and is better suited to large-scale integration implementation. The raw Doppler data were input into a digital oscilloscope from the analog Doppler unit, digitized in real time with 12-b resolution, and displayed on the computer monitor. These data were then stored in a file, on floppy or hard disk, using software provided with the digitizing oscilloscope, and then transformed to the spectral domain using either transform technique. In this application, the transforms were performed using a compiled BASIC language     

对称α稳定分布噪声环境下短波衰落信号时延估计的新算法

脉冲噪声环境下信号时延估计是信号处理领域十分活跃的研究方向。在对称α稳定分布噪声环境下,文章提出了一种基于非线性压缩核函数（NCCF）的短波衰落信号的时延估计算法。该算法采用非线性压缩核函数抑制了对称α稳定分布噪声的脉冲拖尾,同时较好保持了目标信号之间的互相关特性,从而保证了信号时延估计的准确性。同以往算法相比,本算法不仅降低了计算复杂度,而且对于衰落信号的时延估计具有更强的稳定性。理论证明和仿真结果均表明,该算法比GCC、FLOC、GCF和非线性变换等算法具有更好的时延估计有效性和准确度。      

An Improved Control Algorithm for an Artificial ?-Cell

With the successful implementation of a computer analog for (?-cell function to restore normal glucose tolerance in diabetic patients, one of the major obstacles to the ultimate development of an implantable ``artificial pancreas' was overcome. The next step was to optimize the original algorithm and simplify the operation of the blood sugar control system to make it more amenable to miniaturization.     

The Low-Potential Approach of Glucose Sensing

Study of glucose sensing using a smooth Pt electrode and cyclic voltammetry (CV) at low potentials revealed two well-defined, redox current peaks of adsorbed species. At 370 C a reduction peak occurs at ?0.80 V versus Ag/AgCl and an oxidation peak at ?0.72 V. Furthermore, the redox couple has been shown to be reversible, involving a simple, direct, electron-transfer process under diffusion control. The reaction is not complicated by secondary chemical (nonelectro-chemical) reactions. Based on this approach, a square wave voltammetry (SWV) technique has been adopted to obtain pure faradaic currents (noncapacitance current), fast response times, and enhanced sensitivity-for the designated reversible redox peaks. The SWV technique also permits the employment of much smaller-sized Pt wire electrodes (0.5 mm diameter) for glucose sensing. Plots of current versus glucose concentration in Krebs-Ringer solutions, for both redox peaks, are linear for glucose levels in the 70-350 mg/dl range. Studies of glucose concentration variations in the ultrafiltrate of human serum have also demonstrated a linear relationship between current and glucose level. Thus far, the linearity is limited to a narrow glucose range (80?180 mg/dl), but this is within the critical domain for diabetic control. The advantages of the low-potential approach using SWV is an improvement over CV and could be a promising method for implantable microelectrode glucose sensing.