Chronic cardiovascular disease (CVD) is increasingly becoming a burden for global healthcare systems. This burden can be attributed in part to traditional methods of managing CVD in an aging population that involves periodic meetings between the patient and their healthcare provider. There is growing interest in developing continuous monitoring systems to assist in the management of CVD. Monitoring systems can utilize advances in wearable devices and health records, which provides minimally invasive methods to monitor a patient’s health. Despite these advances, the algorithms deployed to automatically analyze the wearable sensor and health data is considered too computationally expensive to run on the mobile device. Instead, current mobile devices continuously transmit the collected data to a server for analysis at great computational and data transmission expense. In this thesis a novel mobile system designed for monitoring CVD is presented. Unlike existing systems, the proposed system allows for the continuous monitoring of physiological sensors, data from a patient’s health record and analysis of the data directly on the mobile device using machine learning algorithms (MLA) to predict an individual’s CVD severity level. The system successfully demonstrated that a mobile device can act as a complete monitoring system without requiring constant communication with a server. A comparative analysis between the support vector machine (SVM) and multilayer perceptron (MLP) to explore the effectiveness of each algorithm for monitoring CVD is also discussed. Both models were able to classify CVD risk with the SVM achieving the highest accuracy (63%) and specificity (76%). Finally, unlike current systems the resource requirements for each component in the system was evaluated. The MLP was found to be more efficient when running on the mobile device compared to the SVM. The results of thesis also show that the MLAs complexity was not a barrier to deployment on a mobile device. / Thesis / Master of Applied Science (MASc) / In this thesis, a novel mobile system for monitoring cardiovascular (CVD) disease is presented. The system allows for the continuous monitoring of both physiological sensors, data from a patient’s health record and analysis of the data directly on the mobile device using machine learning algorithms (MLA) to predict an individual’s CVD severity level. The system successfully demonstrated that a mobile device can act as a complete monitoring system without requiring constant communication with a remote server. A comparative analysis between the support vector machine (SVM) and multilayer perceptron (MLP) to explore the effectiveness of each MLA for monitoring CVD is also discussed. Both models were able to classify CVD severity with the SVM achieving the highest accuracy (63%) and specificity (76%). Finally, the resource requirements for each component in the system were evaluated. The results show that the MLAs complexity was not a barrier to deployment on a mobile device.

First part of this thesis presents the design, validation, and implementation of an Orthogonal Frequency Division Multiplexing (OFDM) transmitter and receiver on a Cyclone II FPGA chip using DSP builder and Quartus II high level design tools. The resources in terms of logical elements (LE) including combinational functions and logic registers allocated by the model have been investigated and addressed. The result shows that implementing the basic OFDM transceiver allocates about 14% (equivalent to 6% at transmitter and 8% at receiver) of the available LE resources on an Altera Cyclone II EP2C35F672C6 FPGA chip, largely taken up by the FFT, IFFT and soft decision encoder. Secondly, a new wavelet-based OFDM system based on FDPP-DA based channel estimation is proposed as a reliable ECG Patient Monitoring System, a Personal Wireless telemedicine application. The system performance for different wavelet mothers has been investigated. The effects of AWGN and multipath Rayleigh fading channels have also been studied in the analysis. The performances of FDPP-DA and HDPP-DA-based channel estimations are compared based on both DFT-based OFDM and wavelet-based OFDM systems. The system model was studied using MATLAB software in which the average BER was addressed for randomized data. The main error differences that reflect the quality of the received ECG signals between the reconstructed and original ECG signals are established. Finally a DA-based architecture for 1-D iDWT/DWT based on an OFDM model is implemented for an ECG-PMS wireless telemedicine application. In the portable wireless body transmitter unit at the patient site, a fully Serial-DA-based scheme for iDWT is realized to support higher hardware utilization and lower power consumption; whereas a fully Parallel-DA-based scheme for DWT is applied at the base unit of the hospital site to support a higher throughput. It should be noted that the behavioural level of HDL models of the proposed system was developed and implemented to confirm its correctness in simulation. Then, after the simulation process the design models were synthesised and implemented for the target FPGA to confirm their validation.

The lack of digital and easily accessible information for home hemodialysis patients leads to a disinclination of using the provided manuals. This problem could potentially be solved with a user-friendly app, where all information and communication with the healthcare providers could take place. Hence, leading to them feeling better prepared to take charge of their own treatment. The purpose of this thesis is to provide a minimum viable product of a mobile application to facilitate treatment for home hemodialysis patients. The app was developed using the programming language SwiftUI. Information was collected from patients with home hemodialysis treatment through interviews conducted in their homes.  The mobile application enables patients to access the manual and failure identification codes through a search bar. It also provides digital checklists, dialysis protocol and symptom follow-up. The healthcare providers can then access the dialysis protocol and symptom follow-up through remote patient monitoring. A chat function allows patients to contact nurses. The mobile application fulfills the clients’ requests and with additional work it could be fully operational. / Bristen på digital och lättåtkomlig information för patienter med hemhemodialys leder till en ovilja att använda manualer och felkoder. En lösning på detta problem skulle kunna vara att utveckla en användarvänlig app som innehåller all nödvändig information, samt ett kommunikationsverktyg mellan patient och vårdpersonal. Syftet med detta examensarbete är att skapa en minsta gångbar produkt i form av en app för att underlätta behandlingen för patienter med hemhemodialys. Appen utvecklades med programmeringsspråket SwiftUI. Information hämtades från patienter genom utförda hemintervjuer.  Den mobila applikationen ger patienter åtkomst till manualen samt felkoderna genom en sökruta. Den innehåller även digitala checklistor, dialysprotokoll och symtomuppföljning. Vårdpersonal kan genom appen få tillgång till patienters dialysprotokoll och symtomuppföljning genom fjärrövervakning. Via chatten kan patienter kontakta sjukvårdspersonal. Applikationen uppfyller uppdragsgivarens önskemål om funktionaliteter. Om fortsatt arbete genomförs kan appen användas för att ge patienterna stöd i sin egenvård. / Nej

[pt] Estimativas informam que 80 por cento a 99 por cento dos alarmes disparados em unidades hospitalares são falsos ou clinicamente insignificantes, representando uma cacofonia de sons que não apresenta perigo real aos pacientes. Estes falsos alertas podem culminar em uma sobrecarga de alertas que leva um profissional da saúde a perder eventos importantes que podem ser prejudiciais aos pacientes ou até mesmo fatais. À medida que as unidades de saúde se tornam mais dependentes de dispositivos de monitoramento que acionam alarmes, o problema da fadiga de alarme deve ser tratado como uma das principais questões, a fim de prevenir a sobrecarga de alarme para os profissionais da saúde e aumentar a segurança do paciente. O principal objetivo desta tese é propor uma solução para o problema de fadiga de alarme usando um mecanismo de raciocínio automático para decidir como notificar os membros da equipe de saúde. Nossos objetivos específicos são: reduzir o número de notificações enviadas à equipe de cuidadores; detectar alarmes falsos com base em informações de contexto do alarme; decidir o melhor cuidador a quem uma notificação deve ser atribuída. Esta tese descreve: um modelo para suportar algoritmos de raciocínio que decidem como notificar os profissionais de saúde para evitar a fadiga de alarme; uma arquitetura para sistemas de saúde que suporta recursos de monitoramento, raciocínio e notificação de pacientes; e três algoritmos de raciocínio que decidem: (i) como notificar os profissionais de saúde decidindo quando agrupar um conjunto de alarmes; (ii) se deve ou não notificar os profissionais de saúde com uma indicação de probabilidade de falso alarme; (iii) quem é o melhor cuidador a ser notificado considerando um grupo de cuidadores. Experimentos foram realizados para demonstrar que, ao fornecer um sistema de raciocínio que agrupa alarmes semelhantes e recorrentes, pode-se reduzir o total de notificações recebidas pelos cuidadores em até 99.3 por cento do total de alarmes gerados, sem perda de informação útil. Esses experimentos foram avaliados através do uso de um conjunto de dados reais de monitoramento de sinais vitais de pacientes registrados durante 32 casos cirúrgicos nos quais os pacientes foram submetidos à anestesia, no hospital Royal Adelaide. Apresentamos os resultados desse algoritmo através de gráficos gerados na linguagem R, onde mostramos se o algoritmo decidiu emitir um alarme imediatamente ou após um determinado delay. Para a tarefa de atribuição de notificações realizada pelo nosso algoritmo de raciocínio que decide sobre qual cuidador notificar, também alcançamos nossos resultados esperados, uma vez que o algoritmo priorizou o cuidador que estava disponível no momento do alarme, além de ser o mais experiente e capaz de atender à notificação. Os resultados experimentais sugerem fortemente que nossos algoritmos de raciocínio são uma estratégia útil para evitar a fadiga de alarme. Embora tenhamos avaliado nossos algoritmos em um ambiente experimental, tentamos reproduzir o contexto de um ambiente clínico utilizando dados reais de pacientes. Como trabalho futuro, visamos avaliar os resultados de nossos algoritmos utilizando condições clínicas mais realistas, aumentando, por exemplo, o número de pacientes, os parâmetros de monitoramento e os tipos de alarme. / [en] Estimates show that 80 per cent to 99 per cent of alarms set off in hospital units are false or clinically insignificant, representing a cacophony of sounds that do not present a real danger to patients. These false alarms can lead to an alert overload that causes a health care provider to miss important events that could be harmful or even life-threatening. As health care units become more dependent on monitoring devices for patient care purposes, the alarm fatigue issue has to be addressed as a major concern in order to prevent healthcare providers from undergoing alarm burden, as well as to increase patient safety. The main goal of this thesis is to propose a solution for the alarm fatigue problem by using an automatic reasoning mechanism to decide how to notify members of the health care team. Our specific goals are: to reduce the number of notifications sent to caregivers; to detect false alarms based on alarm-context information; to decide the best caregiver to whom a notification should be assigned. This thesis describes: a model to support reasoning algorithms that decide how to notify caregivers in order to avoid alarm fatigue; an architecture for health systems that supports patient monitoring, reasoning and notification capabilities; and three reasoning algorithms that decide: (i) how to notify caregivers by deciding whether to aggregate a group of alarms; (ii) whether, or not, to notify caregivers with an indication of a false alarm probability; (iii) who is the best caregiver to notify considering a group of caregivers. Experiments were used to demonstrate that by providing a reasoning system that aggregates alarms we can reduce the total of notifications received by the caregivers by up to 99.3 per cent of the total alarms generated. These experiments were evaluated through the use of a dataset comprising real patient monitoring data and vital signs recorded during 32 surgical cases where patients underwent anesthesia at the Royal Adelaide Hospital. We present the results of this algorithm by using graphs generated with the R language, which show whether the algorithm decided to deliver an alarm immediately or after a given delay. We also achieved the expected results for our reasoning algorithm that handles the notifications assignment task, since the algorithm prioritized the caregiver that was available and was the most experienced and capable of attending to the notification. The experimental results strongly suggest that our reasoning algorithms are a useful strategy to avoid alarm fatigue. Although we evaluated our algorithms in an experimental environment, we tried to reproduce the context of a clinical environment by using real-world patient data. As future work, we aim to evaluate our algorithms using more realistic clinical conditions by increasing, for example, the number of patients, monitoring parameters, and types of alarm.

The master thesis is a prototyping project of a wireless body area network (WBANs) for patient monitoring in hospitals. The goal of this project was to study various technologies suitable for wireless body area networks, complete a requirement analysis, design a WBAN suitable to achieve the requirements and to test and evaluate the system against the requirements. Seven sensor end nodes are chosen to monitor seven vital signs for patient monitoring. After studying different technologies suitable for WBANs, IEEE 802.15.4j was chosen because it communicates in a special allocation of medical spectrum of 2360 to 2400MHz. A coordinator or master will be the center of the network using a star topology. Due to certain limitations in the firmware of the NXP FRDMKW40Z, IEEE 802.15.4j had to be dropped and IEEE 802.15.4 was the final chosen technology because the only difference between IEEE 802.15.4j and IEEE802.15.4 is the difference in the physical layer, while the developed application remains the same, making the shift back to IEEE802.15.4j, in the future, simple. There have been several projects working on the same idea with IEEE 802.15.4, but they do not combine multiple sensors to form a network and the total throughput requirements for this thesis project are much higher. The beacon mode and the non-beacon mode of IEEE 802.15.4 are studied. Non beacon mode is unpredictable due to the use of carrier sense multiple access with collision avoidance (CSMA/CA) to access the medium. When multiple end nodes compete to get access to the medium, unreliability is introduced into the system. In the beacon mode, because of the slotted CSMA access of sixteen equally spaced time slots for communication, there is a restriction of the size of a time slot and thus, the high throughput requirement of the system is not met. The solution proposed in the thesis project is to develop a custom time slot system in the non-beacon mode, where each end node is granted a reserved time slot of a specific length as required by the end node. There is a timer mechanism which makes sure that the time slots for each device maintain the time limit on the time slot, on the side of the main master/coordinator of the network and on the side of the end node. The protocol for an end node to join a personal area network (PAN) is called as the association process. The association process enables the end node to be a part of a PAN to exchange its sensor data. Traditionally, in IEEE 802.15.4, the end nodes scan the sixteen IEEE 802.15.4 channels and when an appropriate coordinator is found, the end node initiates the association process with the coordinator. The solution proposed for the formation of the network by the association process is to use two different technologies. The end nodes and the coordinator exchange information using near field communication (NFC) technology by a simple tapping mechanism. The end node has an active NFC tag while the coordinator has an NFC reader. During the tap between the two devices, first the coordinator reads the end node data from the active tag. This data is required to form the custom time slot. Next the coordinator writes all association information into the active tag. After the NFC data exchange is done, the end node initiates the traditional IEEE 802.15.4 association protocol to join the coordinator’s PAN. Similarly after seven end nodes are associated to the coordinator, the network begins to function. All the end nodes communicate their data to the coordinator. The coordinator collects all the sensor data from the seven end nodes and may send the cumulative sensor data to the backend database servers which may be viewed by the medical authorities, this part is not included in the current version of the project. Several tests are run on this system to evaluate the requirements of latency, throughput and quality of service with two different ranges of 20cm and 250cm. The latency of association between the coordinator and end node is 632ms. The required throughput is met by the network. The packet delivery rate of the system is always above 99%. The graphs for packet delivery rates for all the sensors with a range of 20cm and 250 cm are shown in the appendices. The probabilities for the packet delivery rates greater than 90%, 99%, 99.9% and 99.99% are also graphically shown using a normal distribution in the appendices.

Under detta examensarbete har en lösning framtagits som underlättar distansmonitorering av patienter. Då olika medicinska produkter skickar data till sina egna plattformar blir det krångligt för både patienten och vårdgivaren att ta fram och hålla koll på alla vitalparametrar som tas. Därför har en gemensam plattform, LinkWatch, utvecklats. Idag kan flera vitalparametrar mätas och ses i plattformen. En säker och effektiv dataöverföring mellan en blodsockermätare och LinkWatchs webbserver har gjorts för att utöka funktionaliteten på LinkWatch. Målet med projektet var att integrera en blodsockermätare med LinkWatch. Arbetet har utförts i programmeringsspråken Kotlin och Swift. För att få kunskap om dataöverföringen söktes information om bland annat standarden FHIR, Bluetooth Low Energy samt tidigare arbeten. Resultatet av arbetet är två applikationer, en för iOS och en för Android. Mobilapplikationerna kan koppla sig till blodsockermätaren via Bluetooth, överföra dess värden till mobilen samt skicka dessa till LinkWatchs webbserver. Applikationerna har enkla användargränssnitt och enkla layouter för att underlätta patientens användning av applikationerna. Använder patienten LinkWatch, kan patienten se sitt blodsockervärde tillsammans med andra vitalparametrar och på så sätt få en bra överblick över sin hälsa. Projektet är positivt för diabetiker och andra som är intresserade av hälsa. Tack vare den användarvänliga plattformen och mångsidigheten av LinkWatch, kan användare enklare kunna hålla koll på sitt blodsockervärde och göra livsviktiga åtgärder vid uppkomst av symtom. Vidare kan även vårdgivare ta del av information som LinkWatch lämnar ut för att exempelvis se trender i patientens blodsockervärden. Fördelarna med att dela data med vårdgivaren är bland annat reducerade kostnader och ökad trygghet hos patienterna. / During this project, a solution has been developed that promotes remote patient monitoring. As different medical products send data to their own platforms, it becomes troublesome for both the patient and the care provider to take and keep track of all the vital parameters. Hence a common platform, LinkWatch, has been developed. LinkWatch is a platform where all the patient's medical signs can be seen. To increase the functionality of LinkWatch, a secure and efficient data transfer between a blood glucose meter and LinkWatch’s web server has been established. The goal of this project was to integrate a blood glucose meter with LinkWatch. The programming languages Kotlin and Swift were used to develop the mobile applications. To gain knowledge about the data transfer, research was done to obtain information about the FHIR standard, Bluetooth Low Energy and previous work in the field. The results of the project are two applications, one for iOS and one for Android. The mobile applications can connect to the blood glucose meter with Bluetooth, transfer its values to the mobile phone and send these to LinkWatch’s web server. When the records are in LinkWatch’s system, the patient is able to see their glucose levels along with other vital parameters. This project will have a major impact on patients with diabetes and others who are interested in health. Thanks to the user-friendly platform and the flexibility of LinkWatch, users of the application will be able to more easily keep track of their blood sugar value and take early action in the event of symptoms. Furthermore, health care providers can also take part in information that LinkWatch will provide, for example see trends in the patient's blood sugar values. The benefits with sharing data with the health care providers are cost reductions and increased patient satisfaction.

Qu’il s’agisse de suivre des patients à domicile, ou de prévenir l’isolement ou la vulnérabilité de personnes âgées, les systèmes de suivi et d'assistance électroniques qui émergent offrent des opportunités sans précédents. L’enjeu est considérable, et on assiste à un développement technologique important qui permet désormais aux particuliers ou aux établissements hospitaliers ou médico-sociaux d’assurer le diagnostic, la prévention, le contrôle, voire le traitement de patients à distance (mesures de paramètres physiologiques, administration de médicaments, détection de chutes, etc.). Ce suivi à distance est en particulier devenu possible et performant avec l’avènement des objets connectés. On peut ainsi envisager d’exploiter un réseau de capteurs embarqué sur un patient pour mesurer à distance et en temps réel la température, le rythme cardiaque ou la tension artérielle d’un patient. Les données sont transmises (et/ou stockées) au praticien pour réaliser le diagnostic et définir les traitements. Pour autant la conception optimale (choix des technologies de transmission, de stockage, etc.) ainsi que la problématique de la gestion d’énergie constituent des verrous à leur adoption. Le travail proposé dans cette thèse consiste donc à développer un outil d’aide à la conception de réseaux de capteurs médicaux communicants embarqués sur la personne. Il s’agit en particulier de fournir une information sur la faisabilité au plus tôt dans le cycle de conception, et garantir l’obtention d’un circuit « correcte par construction ». L’accent est porté sur la maîtrise (voire la réduction) de la consommation d’énergie Dans ce sens, une simulation fiable et précise permet de contrôler, dès le début du flot de conception, la consommation en énergie du réseau. Elle assure par la suite une meilleure gestion de l’énergie disponible et éventuellement une autonomie plus importante. L’outil, centré sur l’optimisation de la consommation d’énergie, est implémenté dans un environnement Matlab. Basé sur une modélisation de la consommation en énergie d’un nœud de capteur, il se veut générique aussi bien que précis. Il assure une implémentation simple de nouveaux composants à partir de fiches techniques. Ces composants sont construits sous la forme de blocs réutilisables permettant ainsi à l’utilisateur de créer sa propre librairie. En plus de l’estimation de la consommation, cet outil met en œuvre des algorithmes d’optimisation pour guider l’utilisateur vers une conception qui respecte les contraintes énergétiques et médicales de l’application (choix de composants, choix de source d’énergie, configuration du réseau, etc.). Une application est proposée d’abord au niveau d’un nœud de capteur de température corporelle communiquant par Bluetooth Low Energy. Ce même nœud est ensuite placé au sein d’un réseau de capteurs pour la surveillance de cinq paramètres physiologiques différents. Une validation expérimentale des résultats de simulation est également réalisée. / Whether it is to monitor patients at home, or to prevent the isolation and vulnerability of the elderly, the emerging electronic monitoring and assistance systems offer new opportunities. The technological development we have witnessed allows individuals, hospitals, or medical aid organizations to provide the diagnosis, prevention, control or even treatment of patients outside of conventional clinical settings (measurements of physiological parameters, drug administration, fall detection, etc.).Recent developments in connected objects made efficient remote patient monitoring possible. In other words, we are able to use a network of wearable or implantable sensors to remotely obtain real time measurements of a patient’s vital signs (temperature, heart rate, blood pressure, etc.). Data is transmitted (and / or stored) to medical personnel who are able to perform diagnosis and define treatments accordingly. An optimal design (transmission protocols, data storage, etc.) and energy management are the bottlenecks involved in the implementation of such systems. This work proposes to develop a tool to help in the design of medical sensor networks. It aims to provide information regarding feasibility during the early stages of the design thus ensuring that a "well-constructed" circuit is obtained. The emphasis is on the control (or even reduction) of energy consumption. In this regard, an efficient energy consumption simulation at the beginning of the design flow would enable the user to decide on system parameters. This will ensure an optimal management of the available energy and eventually a longer network lifetime. The proposed tool is centered on the optimization of the energy consumption using Matlab environment. It is built over a model of the energy consumption of wireless sensor nodes. It is intended to be generic and accurate. In fact, it enables fast creation of new component description based on the datasheets. These components are reusable thus producing a growing database. In addition to energy consumption estimation, the tool uses optimization routines to guide the user through an energy aware design (picking energy sources, components, network configuration, etc.) that complies with medical requirements. An application to a single Bluetooth Low Energy body temperature sensor is first proposed. The same sensor is then included in a physiological sensor network. A physical implementation is used in order to compare the results obtained through simulation with practical measurements.

The overall aim of this thesis was to develop, deploy and evaluate new IT-based methods for supporting treatment and assessment of treatment of advanced Parkinson’s disease. In this condition a number of different motor and non-motor symptoms occur in episodes of varying frequency, duration and severity. In order to determine outcome of treatment changes, repeated assessments are necessary. Hospitalization for observation is expensive and may not be representative for the situation at home. Paper home diaries have questionable reliability and storage and retrieval of results are problematic. Approaches for monitoring using wearable sensors are unable to address important non-motor symptoms. A test battery system consisting of both self-assessments of symptoms and motor function tests was constructed for a touch screen mobile phone. Tests are performed on several occasions per day during test periods of one week. Data is transmitted over the mobile net to a central server where summaries in different symptom dimensions and an overall test score per patient and test period are calculated. There is a web application that graphically presents the results to treating clinical staff. As part of this work, a novel method for assessment of spiral drawing impairment useful during event-driven sampling was developed. To date, the system has been used by over 100 patients in 10 clinics in Sweden and Italy. Evidence is growing that the test battery is useful, reliable and valid for assessment of symptoms during advanced Parkinson’s disease. Infusion of a levodopa/carbidopa gel into the small intestine has been shown to reduce variation in plasma drug levels and improve clinical response in this patient category. A pharmacokinetic-pharmacodynamic model of this intestinal gel infusion was constructed. Possibly this model can assist the process of individualization of dosage for this treatment through in numero simulations. Results from an exploratory data analysis indicate that severity measures during oral levodopa treatment may be factors to consider when deciding candidates for infusion treatment.

Significant challenges to patient monitoring systems in a hospital environment include the reliable and energy-efficient transmission of data and their real-time display. This thesis proposes innovative and novel mechanisms for the reliable transmission of patient data in Body Area Network (BAN) communication, which simultaneously ensure high throughput, low data latency, and low energy consumption by implementing energy and QoS aware routing protocols. Five main contributions are made in this regard. Firstly, a novel patient monitoring system (ZK-BAN peering framework) is proposed for real-time hospital BAN communication that displays patient data on the display units by considering data privacy, low energy consumption, better control on the devices, and patient mobility. Secondly, a novel energy-aware peering routing protocol (EPR) is introduced in which the choice of next hop is based on the residual energy and geographic information of the neighbor nodes. EPR contains three main components: a Hello protocol, a neighbor table constructor algorithm, and a routing table constructor algorithm. Thirdly, a new modular QoS-aware routing protocol (QPRD) is designed to handle the ordinary and delay-sensitive data for BAN communication in hospitals. QPRD provides an end-to-end path delay mechanism to calculate the path delays of all possible paths from a source to destination and then chooses the best path with the lowest path delay for delay-sensitive packets. Fourthly, a novel modular QoS-aware routing protocol (QPRR) is developed to handle ordinary and reliability-sensitive data for BAN communication in hospitals. The modular architecture of QPRR includes five modules: a reliability module, a packet classifier, a Hello protocol module, a routing services module, and a QoS-aware queuing module. The proposed mechanisms for end-to-end path reliability calculation and data transmission using redundant paths ensure more reliable BAN communication. Finally, a new integrated energy and QoS aware routing protocol (ZEQoS) is designed to deal with ordinary, delay-sensitive, and reliability-sensitive data packets. Extensive simulations in the OMNeT++ based Castalia 3.2 simulator show that EPR, QPRD, QPRR, and ZEQoS perform better than other similar energy and QoS aware routing protocols.

The implementation of electronic medical record (EMR) systems is a complex process that is receiving more focus in developing countries to support understaffed and overcrowded health facilities deal with the HIV/AIDS epidemic. This thesis research uses exploratory-grounded theory to study clinician perceived benefits of EMRs in antiretroviral therapy (ART) clinics at four hospitals in Ethiopia. The study is designed to understand the process, technology, social and organizational challenges associated with EMR implementation in resource-limited areas. The research found the attitude of ART clinicians towards the implementation of EMR systems to be overwhelmingly positive. The data showed that perceived benefits of EMRs are improved continuity of care, timely access to complete medical record, patient care efficiency, reduced medication errors, improved patient confidentiality, improved communication among clinicians, integration of various HIV programs, timely decision support and overall job motivation. Conversely, drawbacks to EMR implementation include productivity loss and negative impact on the interaction and relationship between clinicians and their patients. The study proposes a conceptual framework classifying key components for successful EMR implementation in Ethiopia.