Analysis of Wireless Body-Centric Medical Sensors for Remote Healthcare

Aquesta tesi aborda el problema de trobar solucions confortables, de baixa potència i sense fils per aplicacions mèdiques. La tesi tracta els avantatges i les limitacions de tres tecnologies de comunicació diferents per la mesura de paràmetres del cos i mètodes per redissenyar sensors per avaluacions òptimes centrades en el cos. La tecnologia RFID es considera una de les solucions més influents per superar el problema del consum d'energia limitat, a causa de la presència de molts sensors connectats. També s'ha estudiat la tecnologia Bluetooth de baixa energia per resoldre els problemes de seguretat i la distància de lectura que, en general, representen el coll d'ampolla de RFID pels sensors de cos. Els dispositius analògics poden reduir dràsticament les necessitats d'energia a causa dels sensors i les comunicacions, considerant pocs elements i un mètode de transmissió simple. S'estudia un mètode de comunicació completament passiu, basat en FSS, que permet una distància de lectura raonable amb capacitats de detecció precises i confiables, que s'ha discutit en aquesta tesi. L'objectiu d'aquesta tesi és investigar múltiples tecnologies sense fils per dispositius portàtils per identificar solucions adequades per aplicacions particulars en el camp mèdic. El primer objectiu és demostrar la facilitat d'ús de les tecnologies econòmiques sense bateria com un indicador útil de paràmetres fisiopatològics mitjançant la investigació de les propietats de les etiquetes RFID. A més a més, s'ha abordat un aspecte més complex respecte a l'ús de petits components passius com sensors sense fils per trastorns del son. Per últim, un altre objectiu de la tesi és el desenvolupament d'un sistema completament autònom que utilitzi tecnologia BLE per obtenir propietats avançades mantenint baix tant el consum com el preuEsta tesis aborda el problema de encontrar soluciones confortables, inalámbricas y de baja potencia para aplicaciones médicas. La tesis discute las ventajas y limitaciones de tres tecnologías de comunicación diferentes para la medición en el cuerpo y los métodos para elegir y remodelar los sensores para evaluaciones óptimas centradas en el cuerpo. La tecnología RFID se considera una de las soluciones más influyentes para superar el consumo de energía limitado debido a la presencia de muchos sensores conectados. Además, la baja energía de Bluetooth se ha estudiado se ha estudiado la tecnologia Bluetooth de baja energia para resolver los problemas de seguridad y la distancia de lectura que, en general, representan el cuello de botella de la RFID para los sensores de cuerpo. Los dispositivos analógicos pueden reducir drásticamente las necesidades de energía debido a los sensores y las comunicaciones, considerando pocos elementos y un método de transmisión simple. Se estudia un método de comunicación completamente pasivo, basado en FSS, que permite una distancia de lectura razonable con capacidades de detección precisas y confiables, que se ha discutido en esta tesis. El objetivo de esta tesis es investigar múltiples tecnologías inalámbricas para dispositivos portátiles para identificar soluciones adecuadas para aplicaciones particulares en campos médicos. El primer objetivo es demostrar la facilidad de uso de las tecnologías económicas sin batería como un indicador útil de dichos parámetros fisiopatológicos mediante la investigación de las propiedades de las etiquetas RFID. Además, se ha abordado un aspecto más complejo con respecto al uso de pequeños componentes pasivos como sensores inalámbricos para enfermedades del sueño. Por último, un resultado de la tesis es desarrollar un sistema completamente autónomo que utilice la tecnología BLE para obtener propiedades avanzadas que mantengan la baja potencia y un precio bajo.This thesis addresses the problem of comfortable, low powered and, wireless solutions for specific body-worn sensing. The thesis discusses advantages and limitations of three different communication technologies for on body measurement and investigate methods to reshape sensors for optimum body-centric assessments. The RFID technology is considered one of the most influential solutions to overcome the limitated power consumption due to the presence of many sensors connected. Further, the Bluetooth low energy has been studied to solve security problems and reading distance that overall represent the bottleneck of the RFID for the body-worn sensors. Analog devices can drastically reduce the energy needs due to the sensors and the communications, considering few elements and a simple transmitting method. An entirely passive communication method, based on FSS is studied, enabling a reasonable reading distance with precise and reliable sensing capabilities, which has been discussed in this thesis. The objective of this thesis is to investigate multiple wireless technologies for wearable devices to identify suitable solutions for particular applications in medical fields. The first objective is to demonstrate the usability of the inexpensive battery-less technologies as a useful indicator of such a physio-pathological parameters by investigating the properties of the RFID tags. Furthermore, a more complex aspect regards the use of small passive components as wireless sensors for sleep diseases has been addressed. Lastly, an outcome of the thesis is to develop an entirely autonomous system using the BLE technology to obtain advanced properties keeping low power and a low price

Robust and Efficient Deep Visual Learning

The past decade was marked by significant progress in the field of artificial intelligence and statistical learning. However, the most impressive of modern models come in the form of computationally expensive black boxes, with the majority of them lacking the ability to reason about the confidence of their predictions robustly. Being capable of quantifying model uncertainty and recognizing failure scenarios is crucial when it comes to incorporating them into complex decision-making pipelines, e.g. autonomous driving or medical image analysis systems. It is also important to maintain a low computational cost of these models. In the present thesis, the aforementioned desired properties of robustness and efficiency of deep learning models are studied and developed in the three specific realms of computer vision. First, we investigate deep probabilistic models that allow uncertainty quantification, i.e. the models that "know what they do not know". Here, we propose a novel model for the task of angular regression that allows probabilistic object pose estimation from 2D images. We also showcase how the general deep density estimation paradigm can be adapted and utilized in two other real-world applications, ball trajectory prediction and brain imaging. Next, we turn to the field of 3D shape analysis and rendering. We propose a method for efficient encoding of 3D point clouds, the type of data that is hard to handle with conventional learning algorithms due to its unordered nature. We show that simple neural networks that use the developed encoding as input can match the performance of state-of-the-art methods on various point cloud processing tasks while using orders of magnitude less floating-point operations. Finally, we explore the emerging field of neural rendering and develop the framework that connects classic deformable 3D body models with modern image-to-image translation neural networks. This combination allows efficient photorealistic human avatar rendering in a controlled manner, with the possibility to control the camera flexibly and to change the body pose and shape appearance. The thesis concludes with the discussion of the presented methods, including current limitations and future research directions

DIFFRACTING REPRESENTATION: TOWARDS A SITUATED AESTHETICS OF TECHNOSPACES

Thesis embargoed until 01-09-2017. Embargo set on 04/08/2015 by CLC, Graduate School.My research for this thesis focusses on the concepts of representation and space in order to demonstrate their theoretical and practical co-implications. Discussing various theorists of space in the first part and analyzing a number of artists and artworks as case studies in the second part, I elaborate a critique of the representational imaginary in order to articulate an alternative notion of representation by means of which a relational, qualitative and performative spatiality can emerge. I specifically focus on technospaces, which I consider a privileged field for observing the intersections of representation and spatiality; it is a field in which the use of spatial metaphors abounds, very often relying on a series of dichotomies (such as location and mobility, the real and the virtual) that have employed and, in most cases, reinforced the traditional idiom of representational. Drawing on the lessons of feminist theory, particularly on approaches to the politics of location, from Adrienne Rich‘s initial formulation to the situated knowledge theorized by Donna Haraway, I elaborate a situated aesthetics of technospaces in which the observer‘s engagement with representational practices replaces the view from a distance of traditional representation, so that her/his position is accounted for together with the history of the production of space and its multiple representations. For this reason, I also formulate an articulatory turn in representation based on Haraway‘s semiotics in order to propose a non-reflexive notion of representation in which invention and factuality eventually meet