Fuzzy-based controller for glucose regulation in type-1 diabetic patients by subcutaneous route

This paper presents an advisory/control algorithm for a type-1 diabetes mellitus (TIDM) patient under an intensive insulin treatment based on a multiple daily injections regimen (MDIR). The advisory/control algorithm incorporates expert knowledge about the treatment of this disease by using Mamdani-type fuzzy logic controllers to regulate the blood glucose level (BGL). The overall control strategy is based on a two-loop feedback strategy to overcome the variability in the glucose-insulin dynamics from patient to patient. An inner-loop provides the amount of both rapid/short and intermediate/long acting insulin (RSAI and ILAI) formulations that are programmed in a three-shots daily basis before meals. The combined preparation is then injected by the patient through a subcutaneous route. Meanwhile, an outer-loop adjusts the maximum amounts of insulin provided to the patient in a time-scale of days. The outer-loop controller aims to work as a supervisor of the inner-loop controller. Extensive closed-loop simulations are illustrated, using a detailed compartmental model of the insulin-glucose dynamics in a TIDM patient with meal intake.     

Enhancing the accuracy of subcutaneous glucose sensors: a real-time deconvolution-based approach

Minimally invasive continuous glucose monitoring (CGM) sensors can greatly help diabetes management. Most of these sensors consist of a needle electrode, placed in the subcutaneous tissue, which measures an electrical current exploiting the glucose-oxidase principle. This current is then transformed to glucose levels after calibrating the sensor on the basis of one, or more, self-monitoring blood glucose (SMBG) samples. In this study, we design and test a real-time signal-enhancement module that, cascaded to the CGM device, improves the quality of its output by a proper postprocessing of the CGM signal. In fact, CGM sensors measure glucose in the interstitium rather than in the blood compartment. We show that this distortion can be compensated by means of a regularized deconvolution procedure relying on a linear regression model that can be updated whenever a pair of suitably sampled SMBG references is collected. Tests performed both on simulated and real data demonstrate a significant accuracy improvement of the CGM signal. Simulation studies also demonstrate the robustness of the method against departures from nominal conditions, such as temporal misplacement of the SMBG samples and uncertainty in the blood-to-interstitium glucose kinetic model. Thanks to its online capabilities, the proposed signal-enhancement algorithm can be used to improve the performance of CGM-based real-time systems such as the hypo/hyper glycemic alert generators or the artificial pancreas.     

Microcomputer-aided insulin dose determination in intensifiedconventional insulin therapy

A microcomputer program is presented that gives information when insulin-dependent diabetes mellitus (IDDM) patients need to make decisions regarding the insulin regimen in intensified conventional insulin therapy in conjunction with self-monitoring of blood glucose. This information consists of the optimum insulin dose and timing of its administration that these IDDM patients need. Estimates were made by a statistical approach based on the impulse response of blood glucose to a bolus injection of insulin (insulin sensitivity) calculated from blood glucose profiles, which consisted of nine daily blood glucose level measurements. This information is objective because it is mathematically substantiated, and useful because it can be obtained from insulin sensitivity     

Online denoising method to handle intraindividual variability of signal-to-noise ratio in continuous glucose monitoring

In the last decade, the availability of new minimally invasive subcutaneous sensors for monitoring glucose level continuously stimulated research on new online strategies for improving the treatment of diabetes, including hyper/hypoglycemic alert generators and artificial pancreas. An important aspect that has to be dealt with in these applications is the random measurement noise that affects continuous glucose monitoring (CGM) signals. One major difficulty is that for a given sensor technology, the signal-to-noise ratio (SNR) can vary from subject to subject (interindividual variability) and also within subject (intraindividual variability). Recently, a denoising approach implemented through a Kalman filter with parameters automatically tuned, once for all, in a burn-in interval was proposed to cope with the interindividual variability of SNR. In this paper, we propose a new denoising method able to cope also with the intraindividual variability of the SNR. The method resorts to a Bayesian smoothing procedure that uses a statistically-based criterion to determine, and continuously update, filter parameters in real time. The performance of the method is assessed on both Monte Carlo simulation and 24 real CGM time series obtained with the Glucoday system (Menarini, Florence, Italy). The method has a general applicability, also outside from the CGM context.     

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.      

Meal simulation model of the glucose-insulin system

A simulation model of the glucose-insulin system in the postprandial state can be useful in several circumstances, including testing of glucose sensors, insulin infusion algorithms and decision support systems for diabetes. Here, we present a new simulation model in normal humans that describes the physiological events that occur after a meal, by employing the quantitative knowledge that has become available in recent years. Model parameters were set to fit the mean data of a large normal subject database that underwent a triple tracer meal protocol which provided quasi-model-independent estimates of major glucose and insulin fluxes, e.g., meal rate of appearance, endogenous glucose production, utilization of glucose, insulin secretion. By decomposing the system into subsystems, we have developed parametric models of each subsystem by using a forcing function strategy. Model results are shown in describing both a single meal and normal daily life (breakfast, lunch, dinner) in normal. The same strategy is also applied on a smaller database for extending the model to type 2 diabetes.     

Devices for the control of diabetes mellitus

New devices are being developed for continuous insulin infusion in diabetes mellitus. Of these the bedside closed-loop system (artificial β-cell) normalizes measured blood glucose in the fasting and fed states, while favorably altering other fuel substrates and hormone levels in short-term studies of one to two days. More recent portable external open-loop insulin delivery devices have been developed which can be programmed to achieve similar results in long-term studies on animals (up to 400 days, and on humans up to 30 days). This is accomplished without the need for continuous glucose sensing. The metabolic normalization achieved is not compromised by physical exercise and unacceptably low blood glucose levels are not observed. Further development and application of these new devices will enable researchers to establish whether the achievement of ideal control of blood glucose in diabetes will in any way alter the cougse of the complications of the disease.     

Mobile-Based Self-Monitoring for Preventing Patients with Type 2 Diabetes Mellitus and Hypertension from Cardiovascular Complication

Currently, there is less attention to the prevention of patients with type 2 diabetes mellitus and hypertension from cardiovascular complication, although it is the significant cause of death for these patients worldwide. To be prevented from this complication, these patients should develop their self-monitoring skills along with their healthcare journey. Consequently, this paper aims to provide an efficient mobile-based self-monitoring that can encourage patients with type 2 diabetes mellitus and hypertension to improve their health status. The distinctive point of the proposed mobile application is the trend progression module for demonstrating the progression of four health statuses for the patients. This trend progression is modeled with a fuzzy logic-based method. The rules are generated based on clinical data, lifestyle data, and experience of healthcare professionals. There are eleven healthcare professionals involved in this paper. The experiment with one hundred twenty-one patients shows that the proposed mobile application provides 92% trend progression accuracy compared with healthcare professionals’ decisions. The developed mobile application obtains the function satisfaction and performance satisfaction in the “strongly satisfied” level. Besides, the developed mobile application can encourage 85% of patients to improve their health statuses. It can be seen that this paper is a new aspect of encouraging patients to concern more about the improvement of their health statuses anywhere and anytime.

     

Artificial Neural Network Expert System for Integrated Heart Rate Variability

This paper describes the combination of an expert system for bio-information with smart devices using a wireless sensor network. A wireless bio-sensor module acquires physiological signals, including electrocardiogram, heart rate, heart rate variability (HRV) and autonomic nervous system activity. The smart device transmits the bio-information over a wireless network to a real-time expert consultation function for analysis, storage and decision making. An artificial neural network algorithm detects the HRV parameters and examines them for features of diabetes. A centralized internet information service platform can interrogate the remote client at any time for its bio-information. In addition, the system platform can compare data files. Bio-information and diabetes information can trigger timely alert messages. The system described in this paper could be the basis for a ubiquitous mobile physiological monitor.     

Keeping watch on glucose

New monitors help fight the long-term complications of diabetes. While a great many innovative technologies have been proposed, only a fraction are in advanced stages of development. They fall into three categories: implantable monitors, transdermal (through the skin) meters, and meters depending on spectroscopic methods. Each is a far cry from the painful methods used over the last several decades. By offering greater convenience and less pain, the devices encourage people to test more frequently, the extra testing providing previously unobtainable information on trends in glucose levels in response to insulin dosage and other treatments. Also, monitors that provide frequent, automatic readings can be equipped with preset alarms to warn the user of high or low glucose levels. Parents of children with diabetes, for example, can be warned of overnight low glucose, rather than having to wake up each night to check their child's blood sugar. These advances will lead to better decisions about treatment and ultimately reduce the long-term medical complications of diabetes     

应用Apriori算法研究2型糖尿病与其并发症的关系

应用Apriori算法,利用糖尿病筛查数据集中的1473条记录进行关联分析,探讨2型糖尿病与其三种主要并发症(高脂血症、高血压、冠心病)之间的关系.通过计算分析按照密切程度排序,得到2型糖尿病与其三种主要并发症的密切关系为:高血压>冠心病>高脂血症.研究结果结合临床实际,证明利用该方法分析2型糖尿病与其相关并发症的关系...     

The INCA System: A Further Step Towards a Telemedical Artificial Pancreas

Biomedical engineering research efforts have accomplished another level of a ldquotechnological solutionrdquo for diabetes: an artificial pancreas to be used by patients and supervised by healthcare professionals at any time and place. Reliability of continuous glucose monitoring, availability of real-time programmable insulin pumps, and validation of safe and efficient control algorithms are critical components for achieving that goal. Nevertheless, the development and integration of these new technologies within a telemedicine system can be the basis of a future artificial pancreas. This paper introduces the concept, design, and evaluation of the ldquointelligent control assistant for diabetes, INCArdquo system. INCA is a personal digital assistant (PDA)-based personal smart assistant to provide patients with closed-loop control strategies (personal and remote loop), based on a real-time continuous glucose sensor (Guardian RT, Medtronic), an insulin pump (D-TRON, Disetronic Medical Systems), and a mobile general packet radio service (GPRS)-based telemedicine communication system. Patient therapeutic decision making is supervised by doctors through a multiaccess telemedicine central server that provides to diabetics and doctors a Web-based access to continuous glucose monitoring and insulin infusion data. The INCA system has been technically and clinically evaluated in two randomized and crossover clinical trials showing an improvement on glycaemic control of diabetic patients.     

CoopMACA: a cooperative MAC protocol using packet aggregation

In this paper we propose a cooperative MAC protocol for Wireless Local Area Networks (WLAN) that involves the concept of cooperation among nodes to avoid the negative effect caused by multi rate modulation employed in IEEE 802.11 standards. In our proposed protocol a low data rate direct transmission link is replaced by two faster transmission links using a relay node. During transmission, each node selects either direct or indirect transmission (through a helper node) in order to minimize the total transmission time and utilizes the packet aggregation concept to improve the system throughput. The new protocol does not violate the inter frame space specified in IEEE 802.11 and shows compatibility with the standard. We give the mathematical analysis that shows that our proposed protocol increases the system throughput considerably in comparison to the existing ones. The analytical results are supported with the help of simulation. We have shown how this protocol can be implemented in combination with others to improve the system throughput in specific network scenarios.     

Adaptive TDMA slot assignment protocol for vehicular ad-hoc networks

This paper proposes a novel adaptive time division multiple access (TDMA) slot assignment protocol (ATSA) for vehicular ad-hoc networks. ATSA divides different sets of time slots according to vehicles moving in opposite directions. When a node accesses the networks, it choices a frame length and competes a slot based on its direction and location to communication with the other nodes. Based on the binary tree algorithm, the frame length is dynamically doubled or shortened, and the ratio of two slot sets is adjusted to decrease the probability of transmission collisions. The theoretical analysis proves ATSA protocol can reduce the time delay at least 20% than the media access control protocol for vehicular ad-hoc networks (VeMAC) and 30% than the ad-hoc. The simulation experiment shows that ATSA has a good scalability and the collisions would be reduced about 50% than VeMAC, channel utilization is significantly improved than several existing protocols.     

WSN中CSMA/CA协处理器的软硬协同设计

在分析了IEEE802.15.4关于无线传感器网络协议带有冲突避免的载波监听多点接入机制的基础上,通过采用独立的指令集、使用软件来控制射频接入流程的实现方式和复用伪随机数产生电路和CRC校验电路等技术,实现了节点芯片的CSMA/CA协处理器。给出采用了这种CSMA/CA协处理器结构的无线传感器网络节点基带芯片的FPGA硬件资源消耗情况,并搭建了该节点芯片与CC2420进行相互通信的测试平台,给出了测试结果,分析时延情况表明,节点芯片在资源有限的情况下获得了较高的处理速度,并实现了对多射频收发芯片支持的灵活性。     

两方有理数多重集的保密计算

集合的安全多方计算(SMC)在联合数据分析、敏感数据安全查询、数据可信交换等场景有着广泛的应用。该文基于有理数的几何编码,结合保密内积协议,首次提出了有理数域上两方多重集交集和并集的保密计算协议。应用模拟范例证明了协议在半诚实模型下的安全性,分别通过理论分析和仿真测试验证了协议的高效性。与现有协议相比,所设计协议无需给定包含所有集合元素的全集,可以保护集合势的隐私性,且在协议执行过程主要使用乘法运算,达到了信息论安全。     

Performance analysis of MSP: feature-rich high-speed transportprotocol

A performance analysis of the MultiStream Protocol (MSP), a feature-rich flexible transport protocol designed to meet the needs of high-performance applications, is presented. The analysis presents the advantages and disadvantages of the implementation of several different protocol mechanisms, such as packet or block mode data transfer. It is based on the processing complexity associated with executing each protocol function. Results show that a feature-rich transport protocol can be implemented in which the protocol control processing overhead is not prohibitive to providing high performance to an application. Instead, the benefits of a lean protocol are achieved because the protocol services better fit application requirements. Also, the primary bottleneck for data transfer is shown to be the complexity associated with error control, which can reduced through the technique of transmitting packets in blocks     

A smartphone‐based U‐Healthcare system for real‐time monitoring of acute myocardial infarction

In recent years, medical service has been evolving from systems designed around centralized hospitals to Ubiquitous Healthcare (U‐Healthcare). U‐Healthcare system can facilitate real‐time monitoring of patient states, and can provide medical checkups and management whenever and wherever the medical staff deems necessary. U‐Healthcare services can provide chronic condition monitoring in the early stages of diseases and help execute decisive medical action in emergencies. However, thus far, the application of U‐Healthcare systems has been limited to diseases such as obesity, diabetes, etc. Acute myocardial infarction (AMI) is among the most critical chronic diseases and requires early detection and treatment. In this paper, we propose an AMI diagnostic software technique and protocol that can support real‐time communication between the patient and medical personnel. Our monitoring and diagnostic system has been developed using a protocol based on ISO/IEEE 11073. When data is transferred from the patient's smartphone to a server in hospital, the medical personnel consult the patient's biosensor data to determine the status of the relevant disease and provide appropriate medical service. The relevant information is sent back to the patient's smartphone through a wireless network, and patients can view their data in graphical format through their smartphone. Copyright © 2015 John Wiley & Sons, Ltd.     

Contention-based reservation protocols in multiwavelength opticalnetworks with a passive star topology

In a multiwavelength optical network with tunable transceivers, an algorithm to make the transmitter and the receiver tuned to the same wavelength simultaneously is needed. The paper proposes contention-based reservation protocols using a separate control channel for multiwavelength optical networks with a passive star topology. First, they present a protocol which can be used in the network where the ratio of the end-to-end signal propagation delay to the transmission time of a data packet is smaller than 1. Also, for a very high speed network where this ratio is greater than 1, the authors present three protocols according to the variability of the packet length and the buffering of the reservation. To access the control channel, all the proposed protocols use the slotted ALOHA protocol. The authors analyze these protocols with a finite population model and investigate the delay-throughput characteristics