Thesis (Ph.D.)--Memorial University of Newfoundland, 2002. / Bibliography: leaves 167-196.

Type 2 Diabetes Mellitus (T2DM) is a growing healthcare problem in the United States that increases the risk for numerous health complications if left unidentified and untreated. Prediabetes, while not a clinical diagnosis, is a state of increased risk of developing T2DM based on elevated blood glucose laboratory markers such as hemoglobin A1C (HbA1C). There are numerous risk factors that predispose individuals to prediabetes and T2DM. Researchers have shown that targeting those risk factors that are modifiable, such as physical inactivity and obesity, with exercise and diet interventions can increase physical activity, decrease weight, decrease HbA1C, and decrease the incidence of T2DM in prediabetics. Tools such as pedometers that track physical activity in the form of step count can be used in interventions to improve upon these metrics. Researchers have also shown that pedometers can enhance interventions aimed at improving physical activity, weight, HbA1C, and incidence of T2DM. Recently, electronic tools that are wearable such as the Fitbit Flex2 have gained in popularity due to their additional interactive features with users. These electronic wearable devices employ behavior change techniques approved by the US Preventive Services Task Force to motivate individuals to be more physically active. Current research has shown that these electronic wearable devices enhance interventions aimed at improving physical activity, weight loss, and HbA1C in those with T2DM. Yet, there is a gap in current research that examines the effect that these devices have on HbA1C in prediabetics. The proposed study seeks to examine if the Fitbit Flex 2 wrist device, in conjunction with a standard diet and exercise intervention, improves HbA1C measures in prediabetic individuals over a one-year period. Results from the proposed study could support the future use of these devices to help decrease HbA1C measures and the risk of development of T2DM and other T2DM- health complications in prediabetics. Electronic wearable devices could alter the way in which clinicians monitor lifestyle interventions aimed at T2DM risk reduction and treatment. The use of electronic wearable devices may also serve as a more cost effective treatment alternative for those at risk of developing, as well as those diagnosed with, T2DM.

Artistic painting involves mastery of haptic interaction with tools. Each tool brings unique physical affordances which determines an aesthetic expression of the finished work. For instance, a pen offers an ability to make a precise stroke in a realism painting, whereas a thick brush or a sponge works perfectly with dynamic arm movement in the abstract art such as action painting. Yet the selection of a tool is just a beginning. It requires repetitive training to understand the full capability of the tool affordance and to master the painting of preferred aesthetic strokes. Such physical act of an artistic expression cannot be captured by the computational tools today. Due to the increasing market adoption of augmented reality and virtual reality, and the decades of studies in haptics, we see an opportunity for advancing 3D painting experiences in non-conventional approach. In this research, we focus on force haptic interaction for 3D painting art in a room-scale virtual reality. We explore virtual tangibility and tool affordance of its own medium. In addition to investigating the fidelity of a physical interactivity, we seek ways to extend the painting capabilities by computationally customized force feedback and metaphor design. This system consists of a wearable force feedback device that sits on user’s hand, a software for motor control and real-time 3D stroke generation, and their integration to VR platform. We work closely with an artist to refine the 3D painting application and to evaluate the system’s usability.

Conventional healthcare and the practice of medicine largely relies on the ineffective concept of one size fits all. Personalized medicine is an emerging therapeutic approach that aims to develop an advanced therapeutic technique that provides tailor-made therapy based on every individuals’ needs by delivering the right drug at the right time with the right amount of dosage. The advancement in technologies such as flexible electronics, microfluidics, biosensors, and advanced artificial intelligence can enable the realization of a truly effective personalized therapy. However, currently, there is a lack for a personalized minimally-invasive wearable closed-loop drug delivery system that is continuous, automated, conformal to the skin and cost-effective. Thus, this thesis focuses on the design, fabrication, optimization, and application of an automated personalized microfluidics drug delivery platform augmented with flexible biosensors, heaters, and expandable polymeric actuator. The platform provides precise drug delivery with spatiotemporal control over the administered dose as a response to real-time physiological changes of the individual. The system is flexible enough to be conformal to the skin and drug is transdermally administered through biocompatible microneedles. The platform includes a flexible multi-reservoir microfluidics layer, flexible and conformal heating elements, skin sensors and processing units which are powered by a lightweight battery integrated into the platform. The developed platform was fabricated using rapid, cost-effective techniques that are independent of advanced microfabrication facilities to expand its applications to low-resource setting and environments.

Advancements in technology have brought about a wide variety of devices, such as embedded devices with sensors and actuators, personal computers, smart devices, and health devices. Many of these devices are categorized as “wearables,” meaning that they are intended to be carried and used on one’s body. As this category increases in popularity and functionality, developers will need a convenient way for these devices to communicate with each other and store information in a standardized and ecient manner. The Fog protocol and FogKit framework developed and demonstrated for this thesis address these issues by providing a set of powerful features, including data posting, data querying, event notifications, and network status requests. These features are defined as convenient JSON formatted messages which can be communicated between Bluetooth peripherals using an iOS device running FogKit as router and server.

Walking is the most common form of human locomotion and the systematic study thereof is known as gait analysis. Measurement and assessment thereof have application in many fields including clinical diagnosis, rehabilitation and biomechanics. The process of gait evaluation is typically done using an optical motion analysis system combined with stationary force platforms. This is considered the gold standard, but unfortunately, has several drawbacks. It is expensive, requires dedicated laboratories with spatial restrictions, calls for lengthy set up and post-processing times and cannot be used in 'real-world' environments. Alternative systems based on wearable sensors have been developed to overcome these limitations. The Council for Scientific and Industrial Research (CSIR) has therefore developed a prototype wearable sensor unit consisting of an inertial measurement unit (IMU). The objective of the current study is, therefore, to advance the prototype to a wearable multi-sensor system for quantitative gait analysis. The focus is on the development of the pre- and post-processing algorithms and methods used to transform the measurements into interpretable information. The focus outlined includes establishing techniques for synchronising the data from the sensors offline, pre-processing the signals, developing algorithms for stride and gait event detection, selecting an appropriate gait model and defining methods for estimating gait parameters. The determined parameters were the spatio-temporal and joint kinematics (hip, knee and ankle). The algorithms and new system were validated against the Vicon motion capture system through gait analyses. The twenty able-bodied volunteers that took part were required to walk across the laboratory six times at three self-selected walking speeds (slow, normal and fast). For the sake of simplicity and due to various limitations, only data in the sagittal plane of the right lower limb of each volunteer was used to validate the wearable system and associated algorithms. The results obtained were then evaluated against several validation criteria. The absolute mean difference between the estimated timing of detected gait events of the two systems was consistently small (between 0.021 and 7.25% of the gait cycle overall). The spatially dependent parameters, stride length and walking speed, had significant maximum mean absolute percentage errors (31.9 and 34.5% respectively), but with little variation. Excluding outliers, that of the temporal parameters, stride time and cadence, was significantly lower (5.7 and 5.6% respectively). The kinematic results were substantially comparable with a minimum correlation co-efficient of 0.86 and a maximum RMSE of 7.8 degrees with little variation implying repeatability. Although there were some discrepancies between the outputs, the wearable sensor system and its corresponding algorithms were considered feasible and potentially beneficial to developing countries like South Africa. Recommendations for future work include synchronising data between the wearable and reference system for stride-to-stride comparisons and validating algorithms using a known reliable wearable system. / Dissertation (MEng)--University of Pretoria, 2017. / Mechanical and Aeronautical Engineering / MEng / Unrestricted

Advancements in soft materials and hybrid flexible electronics have enabled developments in flexible circuits and wearables. Where rigid electronics are extremely precise over small physical areas, flexible electronics have the capability to sense over large curved areas. From the onset of epidermal electronics and flexible transistors, there have been great advancements in sensing over soft curved objects, such as human skin or brain tissue. This thesis focuses on hybrid flexible electronics to sense and stimulate over large areas. The aim of the systems presented is to provide insight into complex navigation and sensor processing systems. In addition to the design, fabrication, and characterization of each device, several important characteristics of each device are investigated: material choice, curvature limits, and device sensitivity. The first device presented in this thesis uses strain gauges to track the bending of neurosurgery navigation stylets for catheter placement. The strain gauge fabrication and characterization is presented. Adhesive testing, stylet bending modeling, and noise techniques are also discussed as they were found to be critical components of the system. The device's limit of detection is 1 mm tip displacement. The purpose of the second set of devices presented is to gain object information from curved or edged robotic structures. Three sensing modes were explored: piezoelectric, strain, and capacitive. The piezoelectric sensor was founded to have a 6.7 times increase in sensitivity when an open-cell foam compliant layer is used. The strain sensor was found to have a gauge factor of 2.83 on a silicone layer and 1.5 on a polymer layer. The combination of the piezoelectric and strain sensing modes is presented. The capacitive sensor is able to detect object shape using inverse problem mathematical techniques. The third device and system presented is a flexible electrode array for stimulating the electroreceptors of electric fish. The spatial and temporal control of a conformal stimulation array enables the decoding of motor signals in the brain. The array fabrication and system development is presented. Surface modification of the electrode array successfully altered the surface energy of the array to match that of the fish for the optimal array-fish interface. In summary, the development and integration of these flexible electronic devices has been achieved. It was found that the interface between the flexible electronic devices and binding objects is critical to device sensitivity and reliability.

Context information available in wearable devices is believed to be useful in many ways. It allows for hiding much of the complexity from the user, thus enabling simpler user interfaces and less user interaction when carrying out tasks on behalf of a user, as well as enabling network operators to provide a better interface to thirdparty service providers who will provide and deliver wireless services. Using the available context information from the wearable device, optimization of service delivery in wireless networks, such as setting up optimal delivery paths between two wearable devices, may be possible without using a third party to do negotiations. In order to fully enable context-awareness, a clear model for how to sense, manage, derive, store, and exchange context information must be defined. This will then provide the platform needed to enable development of context-aware applications that can exploit the possibilities of context-aware computing. The model must take into consideration parameters such as memory usage and power and bandwidth consumption, in order to be efficient on all types of platforms and in all types of networks. It must also be modular enough to survive replacing and upgrading of internal parts. Today little research is available about sensing context information, sensor management, APIs towards other applications, and how and how often to present context information to applications. Since context aware computing relies heavily on the ability to obtain and represent context information, sensing strategies greatly affect efficiency and performance. It is therefore of great interest to develop and evaluate models for carrying out these tasks in order to exploit the results of context awareness research. This thesis will identify and design several components of such a model, as well as test and evaluate the design, in order to be able to make conclusions to whether is lives up to the expectations stated. In order to make the proper design decisions, a full understanding of the context-awareness research area and the goals and purposes of context-aware computing are required. To understand the entire picture is crucial to find a suitable solution. Therefore, determining an efficient sensor input and management strategy, along with a powerful and flexible API for applications, which are the goals of this thesis, fully qualifies as a significant master thesis assignment. / Information om bärbara enheters omgivning som kan göras tillgänglig i enheten, tros kunna vara användbart på många sätt. Det kan möjliggöra gömmande av komplexitet från användaren, vilket ger enklare användargränssnitt och mindre användarinteraktivitet, när utförandet av uppdrag från användaren sker, eller underlätta för en nätverksoperatör som tillhandahåller ett bättre gränssnitt gentemot en tredje part, som tillhandahåller och levererar trådlösa tjänster. Genom att utnyttja tillgänglig information om omgivningen från en bärbar enhet, kan man optimera leverans av tjänster i trådlösa nätverk, så som att hitta en optimal kommunikationsväg mellan två bärbara enheter, utan att använda sig av förhandlingar med en tredje part. För att till fullo möjliggöra ett sådant omgivningsmedvetande, krävs en tydlig modell för att uppfatta, förfina, lagra och utbyta det data som beskriver omgivningen. Denna modell kan då utgöra en plattform som möjliggör utveckling av omgivningsmedvetande applikationer, som kan utnyttja och reagera på de data som beskriver omgivningen. Modellen måste ta hänsyn till parametrar så som minneskonsumtion och batteri- och bandbreddsförbrukning, för att vara effektiv på alla typer av plattformar och i alla typer av nätverk. Den måste också bestå av tillräckligt väl separerade moduler för att klara av byten och uppgraderingar av dess beståndsdelar. Idag finns endast lite tillgänglig forskning om insamlandet av omgivningsdata, hanteringen av sensorer, gränssnitt gentemot mot applikationer och hur och hur ofta omgivningsdata skall presenteras för applikationer. Eftersom omgivningsmedvetenhet beror av möjligheten att införskaffa och representera omgivningsdata, påverkar strategier för att uppfatta omgivningen både effektivitet och prestanda. Det finns därför ett stort intresse i att utveckla och utvärdera modeller för utförandet av dessa uppdrag och för att utforska forskningsresultat om omgivningsmedvetande. Denna rapport identifierar och konstruerar flera komponenter till en sådan modell, samt testar och utvärderar denna för att kunna dra slutsatser om huruvida den lever upp till de förväntningar som finns. För att kunna göra en fullgod konstruktion, krävs en ingående förståelse i forskningsområdet omgivningsmedvetande och syften och mål med densamma. Att förstå den övergripande bilden är nyckeln till en passande lösning. Konstruktion av effektiva strategier för att uppfatta omgivningen, tillsammans med ett kraftfullt och flexibelt API gentemot applikationer, vilket är målen med denna rapport, kvalificerar sig därför som ett examensarbete.

A dissertation submitted to the Faculty of Engineering and the Built Environment, University of Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering, Johannesburg, June 2019 / Data from wearable proximity sensors can be used to measure and describe social contact patterns between individuals in a household. Previous work describing contact patterns, has been qualitative and relies on visual, subjective observations. Data of this kind has been collected for a short period of measurement ranging from 2-3 days. An automated, quantitative analysis of contact patterns could enable an accurate and new representation of social contact patterns. Data was collected from ten households, for 21 days in a pilot study implemented in South Africa. 20 datasets were analysed, representing contact events of 20 individuals. Principal Component Analysis was implemented to determine the similarity of contact events across the days of the experiment and to estimate the minimum number of days required to be sampled, to validly represent an individual’s contact activity. The results show that there is a great variation in contact activity across the days of the experiment, as represented by the number of clusters of similar days. The minimum number of days required was determined by the number of days that had a significant contribution to the first three principal components and this varied across individuals from 5 – 11 days. Further analysis on a larger cohort has a potential to provide better social contact parameters for complex social behavioural models and may assist in understanding transmission dynamics of respiratory pathogens, needed in public health research. / PH2020

The aim of this dissertation is to summarize my research on the development of multifunctional multimaterial fibers that are designed and produced for sensing and modulation applications in wearable and biomedical fields. Fiber-shaped devices have gained significant attention due to their potential in human-machine interface applications. These devices can be woven into fabrics to create smart textiles or used as implantable probes for various biomedical purposes. To meet the requirements of human-machine interface, these fiber devices need to be flexible, robust, scalable, and capable of integrating complex structures and multiple functionalities. The thermal drawing technique has emerged as a promising method for fabricating such fiber devices. It allows for the integration of multiple materials and intricate microstructures, thereby expanding the functionality and applications of the devices. However, the range of materials and structures that can be integrated into these fiber devices is still limited, posing a constraint on their potential applications. To address this limitation, the dissertation focuses on expanding the range of materials and structures that can be integrated into multimaterial fiber devices. This involves the development and application of stretchable electrical and optical deformation fiber sensors by incorporating composite thermoplastic elastomers through the thermal drawing process (Chapter 2). Additionally, the dissertation explores the use of the thermal drawing technique to create multifunctional ferromagnetic fiber robots capable of navigation, sensing, and modulation in minimally invasive surgery (Chapter 3). Furthermore, the integration of nano-optoelectrodes and micro robotic chips on the fiber tip using the combination of thermal drawing and lab-on-fiber techniques is investigated (Chapter 4). The dissertation concludes with an overview of the research findings and potential future directions in the field of multifunctional multimaterial fiber devices (Chapter 5). / Doctor of Philosophy / Human-machine interface (HMI) is the technology that enables communication and interaction between humans and machines or computer systems. It plays a vital role in various domains, including consumer electronics, robotics, healthcare, virtual reality, and industrial automation. Fiber-shaped devices have recently emerged as a promising technology for HMI applications due to their flexibility, lightweight nature, and versatile functionality. These devices can be seamlessly integrated into wearable forms, such as clothing or accessories, and even implanted in the body, opening up a wide range of possibilities for HMI. In the past decades, significant progress has been made in developing multifunctional multimaterial fiber devices using the thermal drawing process (TDP). TDP allows for the fabrication of fibers with complex geometries and microstructures by heating and drawing a preform consisting of different materials. However, the current range of materials and structures that can be integrated into these fiber devices is still limited, which hinders their potential applications. This dissertation aims to expand the capabilities of multimaterial fiber devices by exploring new materials and structures that can be incorporated using TDP. The research focuses on three main areas. First, the development and application of stretchable electrical and optical deformation fiber sensors by integrating composite thermoplastic elastomers are explored (Chapter 2). This enables the sensing of various deformations, enhancing the functionality of the fiber devices. Second, the dissertation investigates the creation of multifunctional ferromagnetic fiber robots capable of navigation, sensing, and modulation in minimally invasive surgery (Chapter 3). These robots offer new possibilities for precise and controlled interventions. Lastly, the integration of nano-optoelectrodes and micro robotic chips on the fiber tip using a combination of thermal drawing and lab-on-fiber techniques is explored (Chapter 4). This allows for advanced optical sensing and remote-control capabilities at the fiber tip. Overall, these three aspects of the project broaden the capabilities and functionalities of multifunctional multimaterial fibers, making them highly versatile and suitable for a wide range of applications in wearable technology and biomedicine. These advancements have the potential to revolutionize the field of human-machine interface (HMI) by enabling seamless and intuitive communication, control, and feedback between humans and machines.