Heart Failure Monitoring System Based on Wearable and Information Technologies

In Europe, Cardiovascular Diseases (CVD) are the leading source of death, causing 45% of all deceases. Besides, Heart Failure, the paradigm of CVD, mainly affects people older than 65. In the current aging society, the European MyHeart Project was created, whose mission is to empower citizens to fight CVD by leading a preventive lifestyle and being able to be diagnosed at an early stage. This paper presents the development of a Heart Failure Management System, based on daily monitoring of Vital Body Signals, with wearable and mobile technologies, for the continuous assessment of this chronic disease. The System makes use of the latest technologies for monitoring heart condition, both with wearable garments (e.g. for measuring ECG and Respiration); and portable devices (such as Weight Scale and Blood Pressure Cuff) both with Bluetooth capabilities

Using a causal smoothing to improve the performance of an on-line neural network glucose prediction algorithm

This work evaluates a spline-based smoothing method applied to the output of a glucose predictor. Methods:Our on-line prediction algorithm is based on a neural network model (NNM). We trained/validated the NNM with a prediction horizon of 30 minutes using 39/54 profiles of patients monitored with the Guardian® Real-Time continuous glucose monitoring system The NNM output is smoothed by fitting a causal cubic spline. The assessment parameters are the error (RMSE), mean delay (MD) and the high-frequency noise (HFCrms). The HFCrms is the root-mean-square values of the high-frequency components isolated with a zero-delay non-causal filter. HFCrms is 2.90±1.37 (mg/dl) for the original profiles.

Smart aeronautical structures: development and experimental validation of a structural health monitoring system for damage detection

En muchas áreas de la ingeniería, la integridad y confiabilidad de las estructuras son aspectos de extrema importancia. Estos son controlados mediante el adecuado conocimiento de danos existentes. Típicamente, alcanzar el nivel de conocimiento necesario que permita caracterizar la integridad estructural implica el uso de técnicas de ensayos no destructivos. Estas técnicas son a menudo costosas y consumen mucho tiempo. En la actualidad, muchas industrias buscan incrementar la confiabilidad de las estructuras que emplean. Mediante el uso de técnicas de última tecnología es posible monitorizar las estructuras y en algunos casos, es factible detectar daños incipientes que pueden desencadenar en fallos catastróficos. Desafortunadamente, a medida que la complejidad de las estructuras, los componentes y sistemas incrementa, el riesgo de la aparición de daños y fallas también incrementa. Al mismo tiempo, la detección de dichas fallas y defectos se torna más compleja. En años recientes, la industria aeroespacial ha realizado grandes esfuerzos para integrar los sensores dentro de las estructuras, además de desarrollar algoritmos que permitan determinar la integridad estructural en tiempo real. Esta filosofía ha sido llamada “Structural Health Monitoring” (o “Monitorización de Salud Estructural” en español) y este tipo de estructuras han recibido el nombre de “Smart Structures” (o “Estructuras Inteligentes” en español). Este nuevo tipo de estructuras integran materiales, sensores, actuadores y algoritmos para detectar, cuantificar y localizar daños dentro de ellas mismas. Una novedosa metodología para detección de daños en estructuras se propone en este trabajo. La metodología está basada en mediciones de deformación y consiste en desarrollar técnicas de reconocimiento de patrones en el campo de deformaciones. Estas últimas, basadas en PCA (Análisis de Componentes Principales) y otras técnicas de reducción dimensional. Se propone el uso de Redes de difracción de Bragg y medidas distribuidas como sensores de deformación. La metodología se validó mediante pruebas a escala de laboratorio y pruebas a escala real con estructuras complejas. Los efectos de las condiciones de carga variables fueron estudiados y diversos experimentos fueron realizados para condiciones de carga estáticas y dinámicas, demostrando que la metodología es robusta ante condiciones de carga desconocidas. ABSTRACT In many engineering fields, the integrity and reliability of the structures are extremely important aspects. They are controlled by the adequate knowledge of existing damages. Typically, achieving the level of knowledge necessary to characterize the structural integrity involves the usage of nondestructive testing techniques. These are often expensive and time consuming. Nowadays, many industries look to increase the reliability of the structures used. By using leading edge techniques it is possible to monitoring these structures and in some cases, detect incipient damage that could trigger catastrophic failures. Unfortunately, as the complexity of the structures, components and systems increases, the risk of damages and failures also increases. At the same time, the detection of such failures and defects becomes more difficult. In recent years, the aerospace industry has done great efforts to integrate the sensors within the structures and, to develop algorithms for determining the structural integrity in real time. The ‘philosophy’ has being called “Structural Health Monitoring” and these structures have been called “smart structures”. These new types of structures integrate materials, sensors, actuators and algorithms to detect, quantify and locate damage within itself. A novel methodology for damage detection in structures is proposed. The methodology is based on strain measurements and consists in the development of strain field pattern recognition techniques. The aforementioned are based on PCA (Principal Component Analysis) and other dimensional reduction techniques. The use of fiber Bragg gratings and distributed sensing as strain sensors is proposed. The methodology have been validated by using laboratory scale tests and real scale tests with complex structures. The effects of the variable load conditions were studied and several experiments were performed for static and dynamic load conditions, demonstrating that the methodology is robust under unknown load conditions.

Feasibility of a wireless health monitoring system for prevention and health assessment of elderly people

The work presented in this paper comprises the methodology and results of a pilot study on the feasibility of a wireless health monitoring system designed under main EU challenges for the promotion of healthy and active ageing. The system is focused on health assessment, prevention and lifestyle promotion of elderly people. Over a hundred participants including elderly users and caregivers tested the system in four pilot sites across Europe. Tests covered several scenarios in senior centers and real home environments, including performance and usability assessment. Results indicated strong satisfactoriness on usability, usefulness and user friendliness, and the acceptable level of reliability obtained supports future investigation on the same direction for further improvement and transfer of conclusions to the real world in the healthcare delivery.

Development of a human movement monitoring system based on wearable devices

It is essential to remotely and continuously monitor the movements of individuals in many social areas, for example, taking care of aging people, physical therapy, athletic training etc. Many methods have been used, such as video record, motion analysis or sensor-based methods. Due to the limitations in remote communication, power consumption, portability and so on, most of them are not able to fulfill the requirements. The development of wearable technology and cloud computing provides a new efficient way to achieve this goal. This paper presents an intelligent human movement monitoring system based on a smartwatch, an Android smartphone and a distributed data management engine. This system includes advantages of wide adaptability, remote and long-term monitoring capacity, high portability and flexibility. The structure of the system and its principle are introduced. Four experiments are designed to prove the feasibility of the system. The results of the experiments demonstrate the system is able to detect different actions of individuals with adequate accuracy.

A proposal for an Internet of Things-based monitoring system composed by low capability, open source and open hardware devices

The Internet of Things makes use of a huge disparity of technologies at very different levels that help one to the other to accomplish goals that were previously regarded as unthinkable in terms of ubiquity or scalability. If the Internet of Things is expected to interconnect every day devices or appliances and enable communications between them, a broad range of new services, applications and products can be foreseen. For example, monitoring is a process where sensors have widespread use for measuring environmental parameters (temperature, light, chemical agents, etc.) but obtaining readings at the exact physical point they want to be obtained from, or about the exact wanted parameter can be a clumsy, time-consuming task that is not easily adaptable to new requirements. In order to tackle this challenge, a proposal on a system used to monitor any conceivable environment, which additionally is able to monitor the status of its own components and heal some of the most usual issues of a Wireless Sensor Network, is presented here in detail, covering all the layers that give it shape in terms of devices, communications or services.

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.

Monitoring maximum peak power density values as a more reliable marker for measurement procedures to elucidate RF EMF health effects: Leganes project

Considering the measurement procedures recommended by the ICNIRP, this communication is a proposal for a measurement procedure based in the maximum peak values of equivalent plane wave power density. This procedure has been included in a project being developed in Leganés, Spain. The project plans to deploy a real time monitoring system for RF to provide the city with a useful tool to adapt the environmental EM conditions to the new regulations approved. A first stage consisting of 105 measurement points has been finished and all the values are under the threshold of the regulation.

On the monitoring of surface displacement in connection with volcano reactivation in Tenerife, Canary Islands, using space techniques

Geodetic volcano monitoring in Tenerife has mainly focused on the Las Cañadas Caldera, where a geodetic micronetwork and a levelling profile are located. A sensitivity test of this geodetic network showed that it should be extended to cover the whole island for volcano monitoring purposes. Furthermore, InSAR allowed detecting two unexpected movements that were beyond the scope of the traditional geodetic network. These two facts prompted us to design and observe a GPS network covering the whole of Tenerife that was monitored in August 2000. The results obtained were accurate to one centimetre, and confirm one of the deformations, although they were not definitive enough to confirm the second one. Furthermore, new cases of possible subsidence have been detected in areas where InSAR could not be used to measure deformation due to low coherence. A first modelling attempt has been made using a very simple model and its results seem to indicate that the deformation observed and the groundwater level variation in the island may be related. Future observations will be necessary for further validation and to study the time evolution of the displacements, carry out interpretation work using different types of data (gravity, gases, etc) and develop models that represent the island more closely. The results obtained are important because they might affect the geodetic volcano monitoring on the island, which will only be really useful if it is capable of distinguishing between displacements that might be linked to volcanic activity and those produced by other causes. One important result in this work is that a new geodetic monitoring system based on two complementary techniques, InSAR and GPS, has been set up on Tenerife island. This the first time that the whole surface of any of the volcanic Canary Islands has been covered with a single network for this purpose. This research has displayed the need for further similar studies in the Canary Islands, at least on the islands which pose a greater risk of volcanic reactivation, such as Lanzarote and La Palma, where InSAR techniques have been used already.

Upper Limb Portable Motion Analysis System Based on Inertial Technology for Neurorehabilitation Purposes

Here an inertial sensor-based monitoring system for measuring and analyzing upper limb movements is presented. The final goal is the integration of this motion-tracking device within a portable rehabilitation system for brain injury patients. A set of four inertial sensors mounted on a special garment worn by the patient provides the quaternions representing the patient upper limb’s orientation in space. A kinematic model is built to estimate 3D upper limb motion for accurate therapeutic evaluation. The human upper limb is represented as a kinematic chain of rigid bodies with three joints and six degrees of freedom. Validation of the system has been performed by co-registration of movements with a commercial optoelectronic tracking system. Successful results are shown that exhibit a high correlation among signals provided by both devices and obtained at the Institut Guttmann Neurorehabilitation Hospital.

On-Chip Thermal Monitoring: Design, Placement and Interconnection of Temperature Sensors

La temperatura es una preocupación que juega un papel protagonista en el diseño de circuitos integrados modernos. El importante aumento de las densidades de potencia que conllevan las últimas generaciones tecnológicas ha producido la aparición de gradientes térmicos y puntos calientes durante el funcionamiento normal de los chips. La temperatura tiene un impacto negativo en varios parámetros del circuito integrado como el retardo de las puertas, los gastos de disipación de calor, la fiabilidad, el consumo de energía, etc. Con el fin de luchar contra estos efectos nocivos, la técnicas de gestión dinámica de la temperatura (DTM) adaptan el comportamiento del chip en función en la información que proporciona un sistema de monitorización que mide en tiempo de ejecución la información térmica de la superficie del dado. El campo de la monitorización de la temperatura en el chip ha llamado la atención de la comunidad científica en los últimos años y es el objeto de estudio de esta tesis. Esta tesis aborda la temática de control de la temperatura en el chip desde diferentes perspectivas y niveles, ofreciendo soluciones a algunos de los temas más importantes. Los niveles físico y circuital se cubren con el diseño y la caracterización de dos nuevos sensores de temperatura especialmente diseñados para los propósitos de las técnicas DTM. El primer sensor está basado en un mecanismo que obtiene un pulso de anchura variable dependiente de la relación de las corrientes de fuga con la temperatura. De manera resumida, se carga un nodo del circuito y posteriormente se deja flotando de tal manera que se descarga a través de las corrientes de fugas de un transistor; el tiempo de descarga del nodo es la anchura del pulso. Dado que la anchura del pulso muestra una dependencia exponencial con la temperatura, la conversión a una palabra digital se realiza por medio de un contador logarítmico que realiza tanto la conversión tiempo a digital como la linealización de la salida. La estructura resultante de esta combinación de elementos se implementa en una tecnología de 0,35 _m. El sensor ocupa un área muy reducida, 10.250 nm2, y consume muy poca energía, 1.05-65.5nW a 5 muestras/s, estas cifras superaron todos los trabajos previos en el momento en que se publicó por primera vez y en el momento de la publicación de esta tesis, superan a todas las implementaciones anteriores fabricadas en el mismo nodo tecnológico. En cuanto a la precisión, el sensor ofrece una buena linealidad, incluso sin calibrar; se obtiene un error 3_ de 1,97oC, adecuado para tratar con las aplicaciones de DTM. Como se ha explicado, el sensor es completamente compatible con los procesos de fabricación CMOS, este hecho, junto con sus valores reducidos de área y consumo, lo hacen especialmente adecuado para la integración en un sistema de monitorización de DTM con un conjunto de monitores empotrados distribuidos a través del chip. Las crecientes incertidumbres de proceso asociadas a los últimos nodos tecnológicos comprometen las características de linealidad de nuestra primera propuesta de sensor. Con el objetivo de superar estos problemas, proponemos una nueva técnica para obtener la temperatura. La nueva técnica también está basada en las dependencias térmicas de las corrientes de fuga que se utilizan para descargar un nodo flotante. La novedad es que ahora la medida viene dada por el cociente de dos medidas diferentes, en una de las cuales se altera una característica del transistor de descarga |la tensión de puerta. Este cociente resulta ser muy robusto frente a variaciones de proceso y, además, la linealidad obtenida cumple ampliamente los requisitos impuestos por las políticas DTM |error 3_ de 1,17oC considerando variaciones del proceso y calibrando en dos puntos. La implementación de la parte sensora de esta nueva técnica implica varias consideraciones de diseño, tales como la generación de una referencia de tensión independiente de variaciones de proceso, que se analizan en profundidad en la tesis. Para la conversión tiempo-a-digital, se emplea la misma estructura de digitalización que en el primer sensor. Para la implementación física de la parte de digitalización, se ha construido una biblioteca de células estándar completamente nueva orientada a la reducción de área y consumo. El sensor resultante de la unión de todos los bloques se caracteriza por una energía por muestra ultra baja (48-640 pJ) y un área diminuta de 0,0016 mm2, esta cifra mejora todos los trabajos previos. Para probar esta afirmación, se realiza una comparación exhaustiva con más de 40 propuestas de sensores en la literatura científica. Subiendo el nivel de abstracción al sistema, la tercera contribución se centra en el modelado de un sistema de monitorización que consiste de un conjunto de sensores distribuidos por la superficie del chip. Todos los trabajos anteriores de la literatura tienen como objetivo maximizar la precisión del sistema con el mínimo número de monitores. Como novedad, en nuestra propuesta se introducen nuevos parámetros de calidad aparte del número de sensores, también se considera el consumo de energía, la frecuencia de muestreo, los costes de interconexión y la posibilidad de elegir diferentes tipos de monitores. El modelo se introduce en un algoritmo de recocido simulado que recibe la información térmica de un sistema, sus propiedades físicas, limitaciones de área, potencia e interconexión y una colección de tipos de monitor; el algoritmo proporciona el tipo seleccionado de monitor, el número de monitores, su posición y la velocidad de muestreo _optima. Para probar la validez del algoritmo, se presentan varios casos de estudio para el procesador Alpha 21364 considerando distintas restricciones. En comparación con otros trabajos previos en la literatura, el modelo que aquí se presenta es el más completo. Finalmente, la última contribución se dirige al nivel de red, partiendo de un conjunto de monitores de temperatura de posiciones conocidas, nos concentramos en resolver el problema de la conexión de los sensores de una forma eficiente en área y consumo. Nuestra primera propuesta en este campo es la introducción de un nuevo nivel en la jerarquía de interconexión, el nivel de trillado (o threshing en inglés), entre los monitores y los buses tradicionales de periféricos. En este nuevo nivel se aplica selectividad de datos para reducir la cantidad de información que se envía al controlador central. La idea detrás de este nuevo nivel es que en este tipo de redes la mayoría de los datos es inútil, porque desde el punto de vista del controlador sólo una pequeña cantidad de datos |normalmente sólo los valores extremos| es de interés. Para cubrir el nuevo nivel, proponemos una red de monitorización mono-conexión que se basa en un esquema de señalización en el dominio de tiempo. Este esquema reduce significativamente tanto la actividad de conmutación sobre la conexión como el consumo de energía de la red. Otra ventaja de este esquema es que los datos de los monitores llegan directamente ordenados al controlador. Si este tipo de señalización se aplica a sensores que realizan conversión tiempo-a-digital, se puede obtener compartición de recursos de digitalización tanto en tiempo como en espacio, lo que supone un importante ahorro de área y consumo. Finalmente, se presentan dos prototipos de sistemas de monitorización completos que de manera significativa superan la características de trabajos anteriores en términos de área y, especialmente, consumo de energía. Abstract Temperature is a first class design concern in modern integrated circuits. The important increase in power densities associated to recent technology evolutions has lead to the apparition of thermal gradients and hot spots during run time operation. Temperature impacts several circuit parameters such as speed, cooling budgets, reliability, power consumption, etc. In order to fight against these negative effects, dynamic thermal management (DTM) techniques adapt the behavior of the chip relying on the information of a monitoring system that provides run-time thermal information of the die surface. The field of on-chip temperature monitoring has drawn the attention of the scientific community in the recent years and is the object of study of this thesis. This thesis approaches the matter of on-chip temperature monitoring from different perspectives and levels, providing solutions to some of the most important issues. The physical and circuital levels are covered with the design and characterization of two novel temperature sensors specially tailored for DTM purposes. The first sensor is based upon a mechanism that obtains a pulse with a varying width based on the variations of the leakage currents on the temperature. In a nutshell, a circuit node is charged and subsequently left floating so that it discharges away through the subthreshold currents of a transistor; the time the node takes to discharge is the width of the pulse. Since the width of the pulse displays an exponential dependence on the temperature, the conversion into a digital word is realized by means of a logarithmic counter that performs both the timeto- digital conversion and the linearization of the output. The structure resulting from this combination of elements is implemented in a 0.35_m technology and is characterized by very reduced area, 10250 nm2, and power consumption, 1.05-65.5 nW at 5 samples/s, these figures outperformed all previous works by the time it was first published and still, by the time of the publication of this thesis, they outnumber all previous implementations in the same technology node. Concerning the accuracy, the sensor exhibits good linearity, even without calibration it displays a 3_ error of 1.97oC, appropriate to deal with DTM applications. As explained, the sensor is completely compatible with standard CMOS processes, this fact, along with its tiny area and power overhead, makes it specially suitable for the integration in a DTM monitoring system with a collection of on-chip monitors distributed across the chip. The exacerbated process fluctuations carried along with recent technology nodes jeop-ardize the linearity characteristics of the first sensor. In order to overcome these problems, a new temperature inferring technique is proposed. In this case, we also rely on the thermal dependencies of leakage currents that are used to discharge a floating node, but now, the result comes from the ratio of two different measures, in one of which we alter a characteristic of the discharging transistor |the gate voltage. This ratio proves to be very robust against process variations and displays a more than suficient linearity on the temperature |1.17oC 3_ error considering process variations and performing two-point calibration. The implementation of the sensing part based on this new technique implies several issues, such as the generation of process variations independent voltage reference, that are analyzed in depth in the thesis. In order to perform the time-to-digital conversion, we employ the same digitization structure the former sensor used. A completely new standard cell library targeting low area and power overhead is built from scratch to implement the digitization part. Putting all the pieces together, we achieve a complete sensor system that is characterized by ultra low energy per conversion of 48-640pJ and area of 0.0016mm2, this figure outperforms all previous works. To prove this statement, we perform a thorough comparison with over 40 works from the scientific literature. Moving up to the system level, the third contribution is centered on the modeling of a monitoring system consisting of set of thermal sensors distributed across the chip. All previous works from the literature target maximizing the accuracy of the system with the minimum number of monitors. In contrast, we introduce new metrics of quality apart form just the number of sensors; we consider the power consumption, the sampling frequency, the possibility to consider different types of monitors and the interconnection costs. The model is introduced in a simulated annealing algorithm that receives the thermal information of a system, its physical properties, area, power and interconnection constraints and a collection of monitor types; the algorithm yields the selected type of monitor, the number of monitors, their position and the optimum sampling rate. We test the algorithm with the Alpha 21364 processor under several constraint configurations to prove its validity. When compared to other previous works in the literature, the modeling presented here is the most complete. Finally, the last contribution targets the networking level, given an allocated set of temperature monitors, we focused on solving the problem of connecting them in an efficient way from the area and power perspectives. Our first proposal in this area is the introduction of a new interconnection hierarchy level, the threshing level, in between the monitors and the traditional peripheral buses that applies data selectivity to reduce the amount of information that is sent to the central controller. The idea behind this new level is that in this kind of networks most data are useless because from the controller viewpoint just a small amount of data |normally extreme values| is of interest. To cover the new interconnection level, we propose a single-wire monitoring network based on a time-domain signaling scheme that significantly reduces both the switching activity over the wire and the power consumption of the network. This scheme codes the information in the time domain and allows a straightforward obtention of an ordered list of values from the maximum to the minimum. If the scheme is applied to monitors that employ TDC, digitization resource sharing is achieved, producing an important saving in area and power consumption. Two prototypes of complete monitoring systems are presented, they significantly overcome previous works in terms of area and, specially, power consumption.

Tool wear monitoring using neuro-fuzzy techniques: a comparative study in a turning process

Tool wear detection is a key issue for tool condition monitoring. The maximization of useful tool life is frequently related with the optimization of machining processes. This paper presents two model-based approaches for tool wear monitoring on the basis of neuro-fuzzy techniques. The use of a neuro-fuzzy hybridization to design a tool wear monitoring system is aiming at exploiting the synergy of neural networks and fuzzy logic, by combining human reasoning with learning and connectionist structure. The turning process that is a well-known machining process is selected for this case study. A four-input (i.e., time, cutting forces, vibrations and acoustic emissions signals) single-output (tool wear rate) model is designed and implemented on the basis of three neuro-fuzzy approaches (inductive, transductive and evolving neuro-fuzzy systems). The tool wear model is then used for monitoring the turning process. The comparative study demonstrates that the transductive neuro-fuzzy model provides better error-based performance indices for detecting tool wear than the inductive neuro-fuzzy model and than the evolving neuro-fuzzy model.

A novel motion tracking system for evaluation of functional rehabilitation of the upper limbs

Upper limb function impairment is one of the most common sequelae of central nervous system injury, especially in stroke patients and when spinal cord injury produces tetraplegia. Conventional assessment methods cannot provide objective evaluation of patient performance and the tiveness of therapies. The most common assessment tools are based on rating scales, which are inefficient when measuring small changes and can yield subjective bias. In this study, we designed an inertial sensor-based monitoring system composed of five sensors to measure and analyze the complex movements of the upper limbs, which are common in activities of daily living. We developed a kinematic model with nine degrees of freedom to analyze upper limb and head movements in three dimensions. This system was then validated using a commercial optoelectronic system. These findings suggest that an inertial sensor-based motion tracking system can be used in patients who have upper limb impairment through data integration with a virtual reality-based neuroretation system.

Natural ventilation in underground wine cellars

The main objective of this research is to promote passive thermal design techniques in the construction of wineries. Natural ventilation in underground cellars is analyzed, focusing on the entrance tunnel, the ventilation chimney and the cave. A monitoring system was designed in order to detect changes in the indoor conditions and outdoor air infiltration. Monitoring process was carried out during one year. Results show the influence of outside temperature, ventilation chimney and access tunnel on the conditions inside the underground cellar. During hot periods, natural ventilation has a negligible influence on the indoor ambience, despite the permanently open vents in the door and chimney. The tunnel and ventilation chimney work as a temperature regulator, dampening outside fluctuations. Forced ventilation is necessary when a high air exchange ratio is needed. During cold periods, there is greater instability as a result of increased natural ventilation. The temperature differences along the tunnel are reduced, reflecting a homogenization and mixing of the air. The ventilation flow is sufficient to modify the temperature and relative humidity of the cave. Forced ventilation is not necessary in this period. During the intermediate periods --autumn and spring-- occurs different behaviors based on time of day.

Sistema de supervisión y soporte para nodos LTE

El proyecto consiste en la actualización del sistema de soporte operacional (OSS) con respecto a las nuevas redes para acceso móvil LTE/4G. El trabajo es un ejercicio real ejercido para Vodafone, compañía de telefonía en España. El producto OSS de Ericsson España es un sistema de supervisión de soporte de la red para cualquier tipo de nodo, pero el proyecto se centrará en los nodos de red LTE (Long Term Evolution). Con este sistema se puede gestionar cualquier cambio en los nodos, incidencias o actualizaciones en la red de manera fiable y sin pérdida de datos. Se profundizará en la descripción del software y del hardware del producto OSS. Se hablará de la tecnología LTE, detallando la evolución sufrida en las redes, el paso de 2G/3G a 4G y todo ello centrado en la industria puntera de las redes de telefonía móviles, así como las nuevas características que esta tecnología aporta y la compatibilidad con las anteriores. ABSTRACT. This project consists of the upgrade of the operational & support system (OSS) regarding the new functionality implemented for the LTE/4G mobile access networks. The project has been implemented in a live environment in Vodafone Spain. Ericsson OSS product consists of a network monitoring system for support and configuration of Core and Radio network elements. This project will be focused on LTE (Long Term Evolution) network nodes. The OSS system can manage any changes in the nodes, incidents or updates to the network in a reliable way without data loss. The description of OSS software and hardware is going to be explained in detail. LTE technology is going to be introduced, detailing the network evolution from 2G/3G to 4G, all focused on the industry leading mobile phone networks and the new features that this technology provides.