Propuesta de algoritmos de predicción de glucosa en pacientes diabéticos

La diabetes mellitus es el conjunto de alteraciones provocadas por un defecto en la cantidad de insulina secretada o por un aprovechamiento deficiente de la misma. Es causa directa de complicaciones a corto, medio y largo plazo que disminuyen la calidad y las expectativas de vida de las personas con diabetes. La diabetes mellitus es en la actualidad uno de los problemas más importantes de salud. Ha triplicado su prevalencia en los últimos 20 anos y para el año 2025 se espera que existan casi 300 millones de personas con diabetes. Este aumento de la prevalencia junto con la morbi-mortalidad asociada a sus complicaciones micro y macro-vasculares convierten la diabetes en una carga para los sistemas sanitarios, sus recursos económicos y sus profesionales, haciendo de la enfermedad un problema individual y de salud pública de enormes proporciones. De momento no existe cura a esta enfermedad, de modo que el objetivo terapéutico del tratamiento de la diabetes se centra en la normalización de la glucemia intentando minimizar los eventos de hiper e hipoglucemia y evitando la aparición o al menos retrasando la evolución de las complicaciones vasculares, que constituyen la principal causa de morbi-mortalidad de las personas con diabetes. Un adecuado control diabetológico implica un tratamiento individualizado que considere multitud de factores para cada paciente (edad, actividad física, hábitos alimentarios, presencia de complicaciones asociadas o no a la diabetes, factores culturales, etc.). Sin embargo, a corto plazo, las dos variables más influyentes que el paciente ha de manejar para intervenir sobre su nivel glucémico son la insulina administrada y la dieta. Ambas presentan un retardo entre el momento de su aplicación y el comienzo de su acción, asociado a la absorción de los mismos. Por este motivo la capacidad de predecir la evolución del perfil glucémico en un futuro cercano, ayudara al paciente a tomar las decisiones adecuadas para mantener un buen control de su enfermedad y evitar situaciones de riesgo. Este es el objetivo de la predicción en diabetes: adelantar la evolución del perfil glucémico en un futuro cercano para ayudar al paciente a adaptar su estilo de vida y sus acciones correctoras, con el propósito de que sus niveles de glucemia se aproximen a los de una persona sana, evitando así los síntomas y complicaciones de un mal control. La aparición reciente de los sistemas de monitorización continua de glucosa ha proporcionado nuevas alternativas. La disponibilidad de un registro exhaustivo de las variaciones del perfil glucémico, con un periodo de muestreo de entre uno y cinco minutos, ha favorecido el planteamiento de nuevos modelos que tratan de predecir la glucemia utilizando tan solo las medidas anteriores de glucemia o al menos reduciendo significativamente la información de entrada a los algoritmos. El hecho de requerir menor intervención por parte del paciente, abre nuevas posibilidades de aplicación de los predictores de glucemia, haciéndose viable su uso en tiempo real, como sistemas de ayuda a la decisión, como detectores de situaciones de riesgo o integrados en algoritmos automáticos de control. En esta tesis doctoral se proponen diferentes algoritmos de predicción de glucemia para pacientes con diabetes, basados en la información registrada por un sistema de monitorización continua de glucosa así como incorporando la información de la insulina administrada y la ingesta de carbohidratos. Los algoritmos propuestos han sido evaluados en simulación y utilizando datos de pacientes registrados en diferentes estudios clínicos. Para ello se ha desarrollado una amplia metodología, que trata de caracterizar las prestaciones de los modelos de predicción desde todos los puntos de vista: precisión, retardo, ruido y capacidad de detección de situaciones de riesgo. Se han desarrollado las herramientas de simulación necesarias y se han analizado y preparado las bases de datos de pacientes. También se ha probado uno de los algoritmos propuestos para comprobar la validez de la predicción en tiempo real en un escenario clínico. Se han desarrollado las herramientas que han permitido llevar a cabo el protocolo experimental definido, en el que el paciente consulta la predicción bajo demanda y tiene el control sobre las variables metabólicas. Este experimento ha permitido valorar el impacto sobre el control glucémico del uso de la predicción de glucosa. ABSTRACT Diabetes mellitus is the set of alterations caused by a defect in the amount of secreted insulin or a suboptimal use of insulin. It causes complications in the short, medium and long term that affect the quality of life and reduce the life expectancy of people with diabetes. Diabetes mellitus is currently one of the most important health problems. Prevalence has tripled in the past 20 years and estimations point out that it will affect almost 300 million people by 2025. Due to this increased prevalence, as well as to morbidity and mortality associated with micro- and macrovascular complications, diabetes has become a burden on health systems, their financial resources and their professionals, thus making the disease a major individual and a public health problem. There is currently no cure for this disease, so that the therapeutic goal of diabetes treatment focuses on normalizing blood glucose events. The aim is to minimize hyper- and hypoglycemia and to avoid, or at least to delay, the appearance and development of vascular complications, which are the main cause of morbidity and mortality among people with diabetes. A suitable, individualized and controlled treatment for diabetes involves many factors that need to be considered for each patient: age, physical activity, eating habits, presence of complications related or unrelated to diabetes, cultural factors, etc. However, in the short term, the two most influential variables that the patient has available in order to manage his/her glycemic levels are administered insulin doses and diet. Both suffer from a delay between their time of application and the onset of the action associated with their absorption. Therefore, the ability to predict the evolution of the glycemic profile in the near future could help the patient to make appropriate decisions on how to maintain good control of his/her disease and to avoid risky situations. Hence, the main goal of glucose prediction in diabetes consists of advancing the evolution of glycemic profiles in the near future. This would assist the patient in adapting his/her lifestyle and in taking corrective actions in a way that blood glucose levels approach those of a healthy person, consequently avoiding the symptoms and complications of a poor glucose control. The recent emergence of continuous glucose monitoring systems has provided new alternatives in this field. The availability of continuous records of changes in glycemic profiles (with a sampling period of one or five minutes) has enabled the design of new models which seek to predict blood glucose by using automatically read glucose measurements only (or at least, reducing significantly the data input manually to the algorithms). By requiring less intervention by the patient, new possibilities are open for the application of glucose predictors, making its use feasible in real-time applications, such as: decision support systems, hypo- and hyperglycemia detectors, integration into automated control algorithms, etc. In this thesis, different glucose prediction algorithms are proposed for patients with diabetes. These are based on information recorded by a continuous glucose monitoring system and incorporate information of the administered insulin and carbohydrate intakes. The proposed algorithms have been evaluated in-silico and using patients’ data recorded in different clinical trials. A complete methodology has been developed to characterize the performance of predictive models from all points of view: accuracy, delay, noise and ability to detect hypo- and hyperglycemia. In addition, simulation tools and patient databases have been deployed. One of the proposed algorithms has additionally been evaluated in terms of real-time prediction performance in a clinical scenario in which the patient checked his/her glucose predictions on demand and he/she had control on his/her metabolic variables. This has allowed assessing the impact of using glucose prediction on glycemic control. The tools to carry out the defined experimental protocols were also developed in this thesis.

Tiempo promedio del efecto máximo de la insulina análoga en la glucemia postprandial y factores relacionados

Introducción: El tiempo promedio del efecto máximo de la insulina regular rápida en la glucemia postprandial ha sido considerado durante años de 120 minutos. En pacientes con Diabetes Mellitus (DM) que usan insulinas análogas este tiempo y los factores asociados no se encuentran reportados para ser aplicados en el automonitoreo. El objetivo de este estudio fue calcular el tiempo y factores relacionados al efecto máximo de la insulina en la glucemia postprandial. Metodología: Se desarrolló un estudio longitudinal retrospectivo a partir de una fuente secundaria donde se realizó un análisis descriptivo y bivariado con las variables demográficas y clínicas presentes en la población. Resultados: El tiempo promedio del pico máximo de insulina en pacientes con DM1 fue de 78.4 (DE± 16.512) y DM2 75.01(DE± 12.02) minutos. El 75% de la población con DM1 y el 54.2% en DM2 era de sexo femenino, la edad promedio en DM1 era 42.38 años y en DM2 68 años, en cuanto a la categorización del IMC el 50% de la población en DM1 y el 37.5% en DM2 estaban dentro del rango de obesidad y se encontró una relación con respecto al tipo de comida “desayuno-cena” vs el tiempo promedio del efecto máximo de la insulina calculado para ambos grupos (p:0.010). Conclusiones: El tiempo promedio del efecto máximo de la insulina calculado fue menor al tiempo reportado en la literatura clínica de 120 minutos. El tipo de comida principal mostró una relación con el tiempo promedio del efecto máximo en ambos grupos.

Surface acoustic wave streaming in a PDMS microfluidic system: effect of frequency and fluid geometry & A remote ultrasonic glucose sensor

This thesis describes two separate projects. The first is a theoretical and experimental investigation of surface acoustic wave streaming in microfluidics. The second is the development of a novel acoustic glucose sensor. A separate abstract is given for each here. Optimization of acoustic streaming in microfluidic channels by SAWs Surface Acoustic Waves, (SAWs) actuated on flat piezoelectric substrates constitute a convenient and versatile tool for microfluidic manipulation due to the easy and versatile interfacing with microfluidic droplets and channels. The acoustic streaming effect can be exploited to drive fast streaming and pumping of fluids in microchannels and droplets (Shilton et al. 2014; Schmid et al. 2011), as well as size dependant sorting of particles in centrifugal flows and vortices (Franke et al. 2009; Rogers et al. 2010). Although the theory describing acoustic streaming by SAWs is well understood, very little attention has been paid to the optimisation of SAW streaming by the correct selection of frequency. In this thesis a finite element simulation of the fluid streaming in a microfluidic chamber due to a SAW beam was constructed and verified against micro-PIV measurements of the fluid flow in a fabricated device. It was found that there is an optimum frequency that generates the fastest streaming dependent on the height and width of the chamber. It is hoped this will serve as a design tool for those who want to optimally match SAW frequency with a particular microfluidic design. An acoustic glucose sensor Diabetes mellitus is a disease characterised by an inability to properly regulate blood glucose levels. In order to keep glucose levels under control some diabetics require regular injections of insulin. Continuous monitoring of glucose has been demonstrated to improve the management of diabetes (Zick et al. 2007; Heinemann & DeVries 2014), however there is a low patient uptake of continuous glucose monitoring systems due to the invasive nature of the current technology (Ramchandani et al. 2011). In this thesis a novel way of monitoring glucose levels is proposed which would use ultrasonic waves to ‘read’ a subcutaneous glucose sensitive-implant, which is only minimally invasive. The implant is an acoustic analogy of a Bragg stack with a ‘defect’ layer that acts as the sensing layer. A numerical study was performed on how the physical changes in the sensing layer can be deduced by monitoring the reflection amplitude spectrum of ultrasonic waves reflected from the implant. Coupled modes between the skin and the sensing layer were found to be a potential source of error and drift in the measurement. It was found that by increasing the number of layers in the stack that this could be minimized. A laboratory proof of concept system was developed using a glucose sensitive hydrogel as the sensing layer. It was possible to monitor the changing thickness and speed of sound of the hydrogel due to physiological relevant changes in glucose concentration.

Development of a cost-effective and flexible vibration DAQ system for long-term continuous structural health monitoring

In the structural health monitoring (SHM) field, long-term continuous vibration-based monitoring is becoming increasingly popular as this could keep track of the health status of structures during their service lives. However, implementing such a system is not always feasible due to on-going conflicts between budget constraints and the need of sophisticated systems to monitor real-world structures under their demanding in-service conditions. To address this problem, this paper presents a comprehensive development of a cost-effective and flexible vibration DAQ system for long-term continuous SHM of a newly constructed institutional complex with a special focus on the main building. First, selections of sensor type and sensor positions are scrutinized to overcome adversities such as low-frequency and low-level vibration measurements. In order to economically tackle the sparse measurement problem, a cost-optimized Ethernet-based peripheral DAQ model is first adopted to form the system skeleton. A combination of a high-resolution timing coordination method based on the TCP/IP command communication medium and a periodic system resynchronization strategy is then proposed to synchronize data from multiple distributed DAQ units. The results of both experimental evaluations and experimental–numerical verifications show that the proposed DAQ system in general and the data synchronization solution in particular work well and they can provide a promising cost-effective and flexible alternative for use in real-world SHM projects. Finally, the paper demonstrates simple but effective ways to make use of the developed monitoring system for long-term continuous structural health evaluation as well as to use the instrumented building herein as a multi-purpose benchmark structure for studying not only practical SHM problems but also synchronization related issues.

Fibre optic distributed sensor system for condition monitoring of synthetic ropes

Reliability of the measuring devices is very important problem. Optical fibre sensors are very efficient. The use of optical fibre sensors for monitoring the physical and chemical parameters has been expanding over resent years. These sensors are applied for monitoring the structural integrity of long, parallel lay synthetic ropes. Such ropes are corrosion free, however, their operational lifetime under cyclic load is not well understood and premature failure can occur due to slippage and breakage of yarns within the rope. The monitoring system has been proposed which is based on acoustic detection of yarn breakage. Monitoring the strain and temperature is performed using the array of fibre gratings distributed along the rope length.

Monitoring and simulation of water, heat,and CO2 fluxes in terrestrial ecosystems based on the APEIS-FLUX system

The Integrated Environmental Monitoring (IEM) project, part of the Asia-Pacific Environmental Innovation Strategy (APEIS) project, developed an integrated environmental monitoring system that can be used to detect, monitor, and assess environmental disasters, degradation, and their impacts in the Asia-Pacific region. The system primarily employs data from the moderate resolution imaging spectrometer (MODIS) sensor on the Earth Observation System- (EOS-) Terra/Aqua satellite,as well as those from ground observations at five sites in different ecological systems in China. From the preliminary data analysis on both annual and daily variations of water, heat and CO2 fluxes, we can confirm that this system basically has been working well. The results show that both latent flux and CO2 flux are much greater in the crop field than those in the grassland and the saline desert, whereas the sensible heat flux shows the opposite trend. Different data products from MODIS have very different correspondence, e.g. MODIS-derived land surface temperature has a close correlation with measured ones, but LAI and NPP are quite different from ground measurements, which suggests that the algorithms used to process MODIS data need to be revised by using the local dataset. We are now using the APEIS-FLUX data to develop an integrated model, which can simulate the regional water,heat, and carbon fluxes. Finally, we are expected to use this model to develop more precise high-order MODIS products in Asia-Pacific region.

Fibre-optic strain sensor system with temperature compensation for arch bridge condition monitoring

This paper presents an innovative sensor system, created specifically for new civil engineering structural monitoring applications, allowing specially packaged fiber grating-based sensors to be used in harsh, in-the-field measurement conditions for accurate strain measurement with full temperature compensation. The sensor consists of two fiber Bragg gratings that are protected within a polypropylene package, with one of the fiber gratings isolated from the influence of strain and thus responding only to temperature variations, while the other is sensitive to both strain and temperature. To achieve this, the temperature-monitoring fiber grating is slightly bent and enclosed in a metal envelope to isolate it effectively from the strain. Through an appropriate calibration process, both the strain and temperature coefficients of each individual grating component when incorporated in the sensor system can be thus obtained. By using these calibrated coefficients in the operation of the sensor, both strain and temperature can be accurately determined. The specific application for which these sensors have been designed is seen when installed on an innovative small-scale flexi-arch bridge where they are used for real-time strain measurements during the critical installation stage (lifting) and loading. These sensors have demonstrated enhanced resilience when embedded in or surface-mounted on such concrete structures, providing accurate and consistent strain measurements not only during installation but subsequently during use. This offers an inexpensive and highly effective monitoring system tailored for the new, rapid method of the installation of small-scale bridges for a variety of civil engineering applications.

A gene knockout approach in mice to identify glucose sensors controlling glucose homeostasis.

A key aspect of glucose homeostasis is the constant monitoring of blood glucose concentrations by specific glucose sensing units. These sensors, via stimulation of hormone secretion and activation of the autonomic nervous system (ANS), regulate tissue glucose uptake, utilization or production. The best described glucose detection system is that of the pancreatic beta-cells which controls insulin secretion. Secretion of other hormones, in particular glucagon, and activation of the ANS, are regulated by glucose through sensing mechanisms which are much less well characterized. Here I review some of the studies we have performed over the recent years on a mouse model of impaired glucose sensing generated by inactivation of the gene for the glucose transporter GLUT2. This transporter catalyzes glucose uptake by pancreatic beta-cells, the first step in the signaling cascade leading to glucose-stimulated insulin secretion. Inactivation of its gene leads to a loss of glucose sensing and impaired insulin secretion. Transgenic reexpression of the transporter in GLUT2/beta-cells restores their normal secretory function and rescues the mice from early death. As GLUT2 is also expressed in other tissues, these mice were then studied for the presence of other physiological defects due to absence of this transporter. These studies led to the identification of extra-pancreatic, GLUT2-dependent, glucose sensors controlling glucagon secretion and glucose utilization by peripheral tissues, in part through a control of the autonomic nervous system.

A real-time measurement system for long-life flood monitoring and warning applications

A flood warning system incorporates telemetered rainfall and flow/water level data measured at various locations in the catchment area. Real-time accurate data collection is required for this use, and sensor networks improve the system capabilities. However, existing sensor nodes struggle to satisfy the hydrological requirements in terms of autonomy, sensor hardware compatibility, reliability and long-range communication. We describe the design and development of a real-time measurement system for flood monitoring, and its deployment in a flash-flood prone 650 km2 semiarid watershed in Southern Spain. A developed low-power and long-range communication device, so-called DatalogV1, provides automatic data gathering and reliable transmission. DatalogV1 incorporates self-monitoring for adapting measurement schedules for consumption management and to capture events of interest. Two tests are used to assess the success of the development. The results show an autonomous and robust monitoring system for long-term collection of water level data in many sparse locations during flood events.

Design and implementation of wireless sensor networks for impedance-based structural health monitoring using ZigBee and Global System for Mobile Communications

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Hydrologic monitoring of an integrated low impact development (LID) underdrained stormwater management system

In 2005, Wetland Studies and Solutions, Inc. (WSSI) installed an extensive Low Impact Development (LID) stormwater management system on their new office site in Gainesville, Virginia. The 4-acre site is serviced by a network of LID components: permeable pavements (two proprietary and one gravel type), bioretention cell / rain garden, green roof, vegetated swale, rainwater harvesting and drip irrigation, and slow-release underground detention. The site consists of heavy clay soils, and the LID components are mostly integrated by a series of underdrain pipes. A comprehensive monitoring system has been designed and installed to measure hydrologic performance throughout the LID, underdrained network. The monitoring system measures flows into and out of each LID component independently while concurrently monitoring rainfall events. A sensitivity analysis and laboratory calibration has been performed on the flow measurement system. Field data has been evaluated to determine the hydrologic performance of the LID features. Finally, hydrologic models amenable to compact, underdrained LID sites have been reviewed and recommended for future modeling and design.

Monitoring long distance WDM communication lines using a high-loss loopback supervisory system

In this paper, we present experimental results for monitoring long distance WDM communication links using a line monitoring system suitable for legacy optically amplified long-haul undersea systems. This monitoring system is based on setting up a simple, passive, low cost high-loss optical loopback circuit at each repeater that provides a connection between the existing anti-directional undersea fibres, and can be used to define fault location. Fault location is achieved by transmitting a short pulse supervisory signal along with the WDM data signals where a portion of the overall signal is attenuated and returned to the transmit terminal by the loopback circuit. A special receiver is used at the terminal to extract the weakly returned supervisory signal where each supervisory signal is received at different times corresponding to different optical repeaters. Therefore, the degradation in any repeater appears on its corresponding supervisory signal level. We use a recirculating loop to simulate a 4600 km fibre link, on which a high-loss loopback supervisory system is implemented. Successful monitoring is accomplished through the production of an appropriate supervisory signal at the terminal that is detected and identified in a satisfactory time period after passing through up to 45 dB attenuation in the loopback circuit. © 2012 Elsevier B.V. All rights reserved.

Blood glucose self-monitoring in non-insulin-treated type 2 diabetes:a qualitative study of patients' perspectives

Background: Self-monitoring of blood glucose is controversial in the management of type 2 diabetes. Some research suggests that self-monitoring improves glycaemic control, whereas other research is sceptical about its value for people with type 2 diabetes who are not on insulin. Although blood glucose meters are widely available and used by this group, patients' own views are absent from the debate. Aim: To explore the pros and cons of glucose monitoring from the patients' perspectives. Design of study: Qualitative repeat-interview study. Setting: Patients were recruited from 16 general practices and three hospital clinics within four local healthcare cooperatives in Lothian, Scotland. Method: Interview data from 40 patients diagnosed with type 2 diabetes within the previous 6 months were analysed using thematic analysis informed by grounded theory. We report findings from round 1 and round 2 interviews. Results: Glucose monitoring can heighten patients' awareness of the impact of lifestyle; for example, dietary choices, on blood glucose levels. Glucose monitoring amplifies a sense of 'success' or 'failure' about self-management, often resulting in anxiety and self-blame if glucose readings remain consistently high. Moreover, monitoring can negatively effect patients' self-management when readings are counter-intuitive. Conclusion: Our analysis highlights the importance of understanding the meanings that newly diagnosed patients attach to glucose self-monitoring. To maximise the positive effects of self-monitoring, health professionals should ensure that patients understand the purpose of monitoring and should clarify with patients how readings should be interpreted. © British Journal of General Practice.

Monitoring long distance WDM communication lines using a high-loss loopback supervisory system

In this paper, we present experimental results for monitoring long distance WDM communication links using a line monitoring system suitable for legacy optically amplified long-haul undersea systems. This monitoring system is based on setting up a simple, passive, low cost high-loss optical loopback circuit at each repeater that provides a connection between the existing anti-directional undersea fibres, and can be used to define fault location. Fault location is achieved by transmitting a short pulse supervisory signal along with the WDM data signals where a portion of the overall signal is attenuated and returned to the transmit terminal by the loopback circuit. A special receiver is used at the terminal to extract the weakly returned supervisory signal where each supervisory signal is received at different times corresponding to different optical repeaters. Therefore, the degradation in any repeater appears on its corresponding supervisory signal level. We use a recirculating loop to simulate a 4600 km fibre link, on which a high-loss loopback supervisory system is implemented. Successful monitoring is accomplished through the production of an appropriate supervisory signal at the terminal that is detected and identified in a satisfactory time period after passing through up to 45 dB attenuation in the loopback circuit. © 2012 Elsevier B.V. All rights reserved.

Monitoring long distance WDM communication lines using a high-loss loopback supervisory system

In this paper, we present experimental results for monitoring long distance WDM communication links using a line monitoring system suitable for legacy optically amplified long-haul undersea systems. This monitoring system is based on setting up a simple, passive, low cost high-loss optical loopback circuit at each repeater that provides a connection between the existing anti-directional undersea fibres, and can be used to define fault location. Fault location is achieved by transmitting a short pulse supervisory signal along with the WDM data signals where a portion of the overall signal is attenuated and returned to the transmit terminal by the loopback circuit. A special receiver is used at the terminal to extract the weakly returned supervisory signal where each supervisory signal is received at different times corresponding to different optical repeaters. Therefore, the degradation in any repeater appears on its corresponding supervisory signal level. We use a recirculating loop to simulate a 4600 km fibre link, on which a high-loss loopback supervisory system is implemented. Successful monitoring is accomplished through the production of an appropriate supervisory signal at the terminal that is detected and identified in a satisfactory time period after passing through up to 45 dB attenuation in the loopback circuit. © 2012 Elsevier B.V. All rights reserved.