Wearable wireless sensor devices, which are implemented by deploying sensor nodes on objects, are widely utilized in a broad field of applica-tions, especially in the healthcare system for improving the quality of life or monitoring different types of physical data from the observed objects. The aim of this study is to design an in-home, small-size and long-term wearable fall detection system in wireless network by using barometric pressure sensing for elderly or patient who needs healthcare monitoring. This threshold-based fall detection system is to measure the altitude of different positions on the human body, and detect the fall event from that altitude information. As a surveillance system, it would trigger an alert when the fall event occurs so that to protect people from the potential life risk by immediate rescue and treatment. After all the performances evaluation, the measurement result shows that standing, sitting and fall state was detected with 100% accuracy and lying on bed state was detected with 93.3% accuracy by using this wireless fall detection system. Furthermore, this system with low power consumption on battery-node can operate continuously up to 150 days.

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Cette thèse est axée sur le domaine de la communication optique sans fil en intérieur pour la surveillance de la santé basée sur des capteurs corporels. L’état de l'art des communications optique sans fil dans les domaines infrarouge, visible et UV ainsi que l'analyse des systèmes liés à la santé utilisant cette technologie ont été fournis. Cela a permis de définir les objectifs et l'orientation de cette thèse. Nous avons étudié l'utilisation de la technologie infrarouge pour la transmission de données entre un capteur porté par un patient et des récepteurs situés aux coins d'un panneau d'éclairage central au plafond de l'environnement. Un lien en visible a été utilisé pour la transmission de données du luminaire vers le patient portant un smartphone équipé d'un décodeur. Les principaux défis étaient la robustesse des liens infrarouge et visible en ce qui concerne la mobilité du patient et l'impact du corps de l'utilisateur en raison de l'emplacement du capteur. Les simulations de canaux réalisées grâce à la technique de Ray-Tracing associée à la méthode de Monte-Carlo ont permis de déterminer le gain de canal qui est le paramètre principal représentant la performance. En raison de la mobilité du patient, l'analyse a été réalisée de manière statistique et en tenant compte de différents emplacements du capteur sur le corps, de la cheville à l'épaule. Les paramètres physiques et géométriques optimaux relatifs aux émetteurs et aux récepteurs afin de garantir les meilleures performances ont été déduites. Il a été démontré qu’il est essentiel de modéliser la présence du corps pour les deux liaisons montante et descendante. Les performances globales du système ont mis en évidence le potentiel des transmissions sans fil entièrement optiques pour la surveillance médicale basée sur des capteurs corporels. Cela a été en partie confirmé par des expérimentations menées à partir de prototypes de capteur communicant en infrarouge et de produits commerciaux pour la liaison en visible. / This thesis is focused on the field of indoor optical wireless communication for health monitoring based on body sensors. The state of the art of optical wireless in the infrared, visible and UV domains as well as the analysis of health related systems using this technology have been provided. This helped to define the objectives and orientations of this thesis. We have studied the use of infrared technology for data transmission between a sensor worn by a patient and receivers located at the corners of a central lighting panel at the ceiling of the environment. A link in visible was used for the transmission of data from the luminaire to the patient carrying a smartphone equipped with a decoder. The main challenges were the robustness of the infrared and visible links with regard to patient mobility and the impact of the user's body due to the location of the sensor. The channel simulations performed using the Ray-Tracing technique associated with the Monte-Carlo method allowed determining the channel gain, which is the main parameter representing the performance. Due to the patient mobility, the analysis was performed statistically and taking into account different locations of the sensor on the body, from the ankle to the shoulder. The optimal physical and geometrical parameters for transmitters and receivers to ensure the best performance have been deduced. It has been shown that it is essential to model the presence of the body for both uplink and downlink. The overall performance of the system has highlighted the potential of fully optical wireless transmissions for medical surveillance based on body sensors. This has been partly confirmed by experiments carried out from infrared communicating sensor prototypes and commercial products for the visible link.

Ces travaux de recherche se sont déroulés dans le cadre du développement d’une application de télévigilance médicale ayant pour but de détecter des situations de détresse à travers l’utilisation de plusieurs types de capteurs. La fusion multi-capteurs peut fournir des informations plus précises et fiables par rapport aux informations provenant de chaque capteur prises séparément. Par ailleurs les données issues de ces capteurs hétérogènes possèdent différents degrés d’imperfection et de confiance. Parmi les techniques de fusion multi-capteurs, les méthodes crédibilistes fondées sur la théorie de Dempster-Shafer sont actuellement considérées comme les plus adaptées à la représentation et au traitement des informations imparfaites, de ce fait permettant une modélisation plus réaliste du problème. En nous appuyant sur une représentation graphique de la théorie de Dempster-Shafer appelée Réseaux Évidentiels, nous proposons une structure de fusion de données hétérogènes issues de plusieurs capteurs pour la détection de chutes afin de maximiser les performances de détection chutes et ainsi de rendre le système plus fiable. La non-stationnarité des signaux recueillis sur les capteurs du système considéré peut conduire à une dégradation des conditions expérimentales, pouvant rendre les Réseaux Évidentiels incohérents dans leurs décisions. Afin de compenser les effets résultant de la non-stationnarité des signaux provenant des capteurs, les Réseaux Évidentiels sont rendus évolutifs dans le temps, ce qui nous a conduit à introduire les Réseaux Evidentiels Dynamiques dans nos traitements et à les évaluer sur des scénarios de chute simulés correspondant à des cas d’usage variés / This work took place in the development of a remote home healthcare monitoring application designed to detect distress situations through several types of sensors. The multi-sensor fusion can provide more accurate and reliable information compared to information provided by each sensor separately. Furthermore, data from multiple heterogeneous sensors present in the remote home healthcare monitoring systems have different degrees of imperfection and trust. Among the multi-sensor fusion techniques, belief methods based on Dempster-Shafer Theory are currently considered as the most appropriate for the representation and processing of imperfect information, thus allowing a more realistic modeling of the problem. Based on a graphical representation of the Dempster-Shafer called Evidential Networks, a structure of heterogeneous data fusion from multiple sensors for fall detection has been proposed in order to maximize the performance of automatic fall detection and thus make the system more reliable. Sensors’ non-stationary signals of the considered system may lead to degradation of the experimental conditions and make Evidential Networks inconsistent in their decisions. In order to compensate the sensors signals non-stationarity effects, the time evolution is taken into account by introducing the Dynamic Evidential Networks which was evaluated by the simulated fall scenarios corresponding to various use cases

The delivery of quality healthcare to all citizens at reasonable costs is an important challenge. With the increase in the aging population, the costs of managing chronic diseases increase. Today, healthcare services tend to shift from recovery to prevention. Remote healthcare monitoring is crucial for prevention and monitoring of chronic diseases since they require continuous and long-term monitoring. The advances in networking, mobile communications and medical device technologies offer a great potential to realize remote healthcare monitoring. However, seamless integration of multi-modal medical devices to the existing healthcare information systems is necessary for the automated use of medical device observations in related applications. The thesis addresses the automatic acquisition and use of multi-modal medical device observations in healthcare information systems. The interoperability of medical devices with healthcare information systems requires both physical connectivity and application level interoperability. Therefore, the thesis concentrates on both the medical device domain and the interoperability efforts on the existing healthcare information systems. It provides an interoperability solution based on ISO/IEEE 11073 and HL7 standards. This work is also realized the automatic acquisition and use of multi-modal medical device observations in an intelligent healthcare monitoring and decision support system which is developed as a part of the IST-027074 SAPHIRE project funded by the European Commission.

A wearable body temperature sensor would allow for early detection of fever or infection, as well as frequent and accurate hassle-free recording. This thesis explores the design of a body-temperature-sensing device inkjet-printed on a flexible substrate. All structures were first modeled by first-principles, theoretical calculations, and then simulated in HFSS. A variety of planar square inductor geometries were studied before selecting an optimal design. The designs were fabricated using multiple techniques and compared to the simulation results. It was determined that inductance must be carefully measured and documented to ensure good functionality. The same is true for parallel-plate and interdigitated capacitors. While inductance remains relatively constant with temperature, the capacitance of the device with a temperature-sensitive dielectric layer will result in a shift in the resonant frequency as environmental or ambient temperature changes. This resonant frequency can be wirelessly detected, with no battery required for the sensing device, from which the temperature can be deduced. From this work, the optimized version of the design comprises of conductive silver in with a temperature-sensitive graphene oxide layer, intended for inkjet-printing on flexible polyimide substrates. Graphene oxide demonstrates a high dielectric permittivity with good sensing capabilities and high accuracy. This work pushes the state-of-the-art in applying these novel materials and techniques to enable flexible body temperature sensors for future biomedical applications.

Cette thèse aborde les performances d’un réseau corporel utilisant la technologie optique sans fil, comme alternative aux radiofréquences. L’application visée concerne la télésurveillance de patients mobiles, en milieu hospitalier. Après avoir défini les principales caractéristiques des réseaux corporels radiofréquences, notamment dans le cas de l’ultra large bande, nous présentons les avantages à utiliser la technologie optique sans fil. Nous considérons ensuite cette technologie en infrarouge, avec une méthode de propagation dite diffuse, exploitant les réflexions des rayons optiques dans l’environnement du réseau corporel. Les différentes méthodes de modélisation d’un canal optique diffus sont introduites, et nous utilisons deux types de méthodes pour modéliser le canal entre deux noeuds portés : un modèle classique dit « à une réflexion », permettant d’évaluer rapidement des variations de performances, et une méthode de lancer de rayon pour considérer un grand nombre de réflexions. En utilisant différents scénarios, ainsi que la notion de probabilité de rupture, nous montrons que l’optique diffuse permet de réaliser un lien corporel, pour les débits et la qualité de service requise par une application de télésurveillance médicale, et pour une puissance de transmission très inférieure à la limite imposée par la sécurité oculaire. Finalement, nous étudions les performances théoriques d’un réseau corporel en optique diffuse en termes de probabilité d’erreur, avec une gestion de l’accès multiple réalisé par répartition de codes optiques. Nous concluons qu’un réseau de capteurs corporels en optique diffuse est théoriquement réalisable, pour une application médicale de surveillance de patients mobiles dans l’environnement. / This thesis deals with the performance of optical girelles communications for body area networks (BAN) as an alternative solution to the radiofrequency one, in the context of mobile healthcare monitoring. After presenting the main characteristics of a BAN using the radiofrequency technology, specifically in the UWB band, we explain the advantages of the optical wireless technology. Diffuse propagation based on infrared technology is then considered for BAN, exploiting optical reflections from environment surfaces. Several optical wireless channel modeling methods are introduced, and we consider two solutions for the link between two on-body nodes: a classical method named “one reflection model”, used to estimate performance variations, and a ray-launching method, used to take into account a great amount of optical reflections. Considering several scenarios, we determine the outage probability, and show that the diffuse optical wireless technology is able to achieve an on-body link, with the data rates and the quality of service required by health monitoring applications, for a transmitted power far lower than the limit defined in standards. Then, we evaluate the theoretical performance, in terms of error probability, of an optical wireless BAN, considering the optical code division multiple access technique. Finally, we show that a BAN using optical wireless technology is theoretically feasible, regarding a health monitoring application, and considering the mobility of the patient in indoor environment.

Two mm-wave frequency modulated continuous wave (FMCW) radars were combined with a recurrent neural network (RNN) to perform fall detection. The purpose was to find methods to implement a multi-radar setup for healthcare monitoring and to study the resulting models’ resilience to interference and other obstacles, such as re-arranging the radars in the room. Single-board computers (SBCs) controlled the radars to record and transfer data over Ethernet to a PC. The Ethernet connection also allowed synchronization with the network time protocol (NTP), which was necessary to put the data from the two sensors in correspondence. The proposed RNN used two bidirectional long-short term memory (Bi-LSTM) layers with L2-regularization and dropout layers. It had an overall accuracy of 95.15% and 98.11% recall with a test set. Performance in live testing varied with different arrangements, with an accuracy of 98% with the radars along the same wall, 94% with the radars diagonally, and 90% with an alternative arrangement that the RNN model had not seen during training. However, the latter arrangement resulted in a recall of 95.7%, with false alarms reducing the overall performance. In conclusion, the model performed adequately for fall detection, even with different radar arrangements but could still be sensitive to interference. / Två millimetervågs-radarsystem av typen frequency modulated continuous wave (FMCW) kombinerades för att med hjälp av ett recurrent neural network (RNN) utföra falldetektering. Syftet var att finna metoder för att implementera en multiradarplatform för hälsoövervakning samt att studera de resulterande modellernas tolerans mot interferens och andra hinder så som att radarsystemen placeras på olika sätt i rummet. Enkortsdatorer kontrollerade radarsystemen för att kunna spela in och överföra data över Ethernet till en PC. Ethernetanslutningen möjliggjorde även synkronisering över network time protocol (NTP), vilket var nödvändigt för att sammanlänka datan från de båda sensorerna. Det föreslagna RNN:et använde två dubbelriktade (bidirectional) long-short term memory (Bi-LSTM) lager med L2-regularisering och dropout-lager. Det hade en total noggrannhet på 95.15% och 98.11% recall med ett test-set. Prestandan vid testning i drift varierade beroende på olika uppställningar av radarmodulerna, med en noggrannhet på 98% då de placerades längs samma vägg, 94% då de placerades diagonalt och 90% vid en alternativ uppställning som RNN-modellen inte hade sett när den tränades. Det senare resulterade dock i 95.7% recall, där falsklarm var den främsta felkällan. Sammanfattningsvis presterade modellen bra för falldetektering, även med olika uppställningar, men den verkar fortfarande vara känslig för interferens.

Several sensor technologies have been developed and experimented over the last few decades to cater various needs of medical diagnostics. Among these, fiber optic sensors, in particular, Fiber Bragg Grating (FBG) based sensors have attracted considerable attention due to their inherent advantages such electrical passiveness, immunity to Electro Magnetic Interference (EMI), chemical inertness, etc. The present research work focuses on design, development and validation of FBG sensor based devices for measurement of certain healthcare parameters in the context of foot function/gait cycle, cardiac and breathing activity, nostril dominance, hand grip/wrist angle force function, etc. The experimental work presented here emphasizes on the effectiveness and competitiveness of the FBG devices developed, in comparison with standard tools such as Accelerometer, Load cell, Electronic Stethoscope, Electromyogram and Dynamometer. In the field of human balance, stability and geriatrics, two independent FBG devices namely, Fiber Bragg Grating based Stability Assessment Device (FBGSAD) and Optical Sensor Ground Reaction Force measurement Platform (OSGRFP) have been designed, developed and experimented for postural stability assessment and gait analysis respectively. The result of these studies have significant implications in understanding of the mechanism of plantar strain distribution, identifying issues in gait cycles, detecting foot function discrepancies, identifying individuals who are susceptible to falls and to qualify subjects for balance and stability. In the field of ergonomic assessment, Fiber Braggs Grating based Hand Grip Device (FBGHGD) is designed and developed for the measurement of hand grip force which helps in the understanding of several important biomechanical aspects such as neuromuscular system function, overall upper-limb strength, vertebral fracture, skeletal muscle function, prediction of disability, incapacity, mortality and bone mass density (forearm, skeletal sites, spine, hip etc.). Further as an extension of this work, the FBGHGD is used for measurement of force generated by the wrist in different positions of the flexion and extension which relates to the wrist muscle activity and its enactment. In the field of cardiac activity monitoring, a novel, in-vivo, non-invasive and portable device named Fiber Bragg Grating based Heart Beat Device (FBGHBD) is developed for the simultaneous measurement of respiratory and cardiac activities. The work involves designing FBGHBD, validating its performance against traditional diagnostic systems like electronic stethoscope, exploration of its clinical relevance and the usage of FBGHBD in studies involving normal persons and patients with myocardial infarction. The unique design of FBGHBD provides critical information such as nascent morphology of cardiac and breathing activity, heart rate variability, heart beat rhythm, etc., which can assist in early clinical diagnosis of many conditions associated to heart and lung malfunctioning. Further, the scope of this work extends towards evaluating several signal processing algorithms and demonstrating a suitable signal processing architecture for real-time extraction of heart beat and respiratory rates along with its nascent morphologies for critical health care application. In the area of breath monitoring, a Nostril Pressure and Temperature Device (NPTD) is designed and developed which aims at simultaneous, accurate and real-time measurement of nostril air flow pressure and temperature to aid in clinical diagnosis of nasal dysfunction and associated nose disorders. The results of NPTD can offer certain vital features like breathing pattern, respiratory rate, changes in individual nostril temperature/pressure, nostrils dominance, body core temperature etc., which can assist in early clinical diagnosis of breathing problems associated with heart, brain and lung malfunctioning. Since the research work in this thesis involve experiments engaging human subjects, necessary approvals from the ethical committee is obtained before the experiments and required ethical procedures are followed during all the experimental trials.