<p>Despite the many security and privacy concerns associated with Internet-of-Things (IoT) devices, we continue to be barraged by new IoT devices every day. These devices have infiltrated almost every aspect of our lives, from government and corporations to our homes, and now, on and within our person, in the form of smartphones and wearables. These personal IoT devices can collect some of the most intimate pieces of data about their user. For instance, a smartwatch can record its wearer's heart rate, skin temperature, physical activity, and even GPS location data. At the same time, a smartphone has access to almost every piece of information related to its user, including text messages, social media activity, web browser history, and application-specific data. Due to the quantity and quality of data these personal IoT devices record, these devices have become critical sources of evidence during forensic investigations. However, there are instances in which digital forensic investigators need to make doubly sure that the data obtained from these smart devices, in fact, belong to the alleged owner of the smart device and not someone else. To that end, this dissertation provides the first look at using personal IoT device handling as a user identification technique with machine learning models to aid forensic investigations. The results indicated that this technique is capable of significantly differentiating device owners with performance metrics of .9621, .9618, and .9753, for accuracy, F1, and AUC, respectively, when using a smartwatch with statistical time-domain features. When considering the smartphone performance, the performance was only marginally acceptable with accuracy, F1, and AUC values of .8577, .8560, and .8891, respectively.  The results also indicate that female users handled their devices notably differently from male users. This study thus lays the foundation for performing user identification during a forensic investigation to determine whether the smart device owner did, in fact, use the device at the time of the incident.</p>

Background: The rapid advancements in technology to measure different bodily functions have enabled normal person to measure various biological values of a body such as a heartbeat, calories, blood pressure, and more. These measurements can help healthcare providers provide better disease assessment, but what are the challenges that make it difficult for healthcare providers to adopt such devices? Purpose: This thesis investigates the challenges that healthcare providers face in adopting wearable devices. Method: To achieve the thesis' purpose, the authors choose to conduct a quantitative study through a survey and a qualitative study through semi-structured interviews. The data was acquired through an online survey of Indian healthcare providers and the public, which was distributed using the messaging app WhatsApp. To ensure that enough responses were collected, the authors adopted a non-probability snowball sampling approach. The interviews were conducted in India in person. The questionnaire was divided into five sections based on the Theory of Planned Behaviour (TPB) and the Technology Acceptance Model (TAM), two well-known theories for predicting human behaviour on technology adoption. Finding: The findings reveal that individuals' attitudes towards using wearables and their purchase intentions serve as strong predictors of its adoption intention. The study also highlights that the primary challenges hindering the adoption of wearable technologies in the healthcare sector are the ease of use and device affordability. These findings contribute to a better understanding of the factors influencing the adoption of wearables, offering valuable insights for healthcare professionals and stakeholders in promoting their effective implementation.

This paper is an explorative interaction design study focusing on the development of a wearable device for enhanced learning of bodily skills. It uses a variation of technology scouting and matchmaking to explore possible technologies related to assistive technology for learning. Semi-structured interviews were conducted with people in the concerned fields and analysis of the interviews resulted in insights that could inform the development of the design. Research findings suggest that a wearable learning system that leverages AI to guide and assist learning of bodily skills through a haptic interface could be possible with current technology. The paper proposes a schematic diagram of the system, UX goals and evaluates user attitudes towards such a system. Overall, this design study could serve as a resource for future development of AI-assisted education for activities involving bodily movement.

<p dir="ltr">In this dissertation, efforts and innovations are made to advance subtle pattern mining, edge computing, and system efficiency optimization for biomedical applications, thereby advancing precision medicine big data.</p><p dir="ltr">Brain visual dynamics encode rich functional and biological patterns of the neural system, promising for applications like intention decoding, cognitive load quantization and neural disorder measurement. We here focus on the understanding of the brain visual dynamics for the Amyotrophic lateral sclerosis (ALS) population. We leverage a deep learning framework for automatic feature learning and classification, which can translate the eye Electrooculography (EOG) signal to meaningful words. We then build an edge computing platform on the smart phone, for learning, visualization, and decoded word demonstration, all in real-time. In a further study, we have leveraged deep transfer learning to boost EOG decoding effectiveness. More specifically, the model trained on basic eye movements is leveraged and treated as an additional feature extractor when classifying the signal to the meaningful word, resulting in higher accuracy.</p><p dir="ltr">Efforts are further made to decoding functional Near-Infrared Spectroscopy (fNIRS) signal, which encodes rich brain dynamics like the cognitive load. We have proposed a novel Multi-view Multi-channel Graph Neural Network (mmGNN). More specifically, we propose to mine the multi-channel fNIRS dynamics with a multi-stage GNN that can effectively extract the channel- specific patterns, propagate patterns among channels, and fuse patterns for high-level abstraction. Further, we boost the learning capability with multi-view learning to mine pertinent patterns in temporal, spectral, time-frequency, and statistical domains.</p><p dir="ltr">Massive-device systems, like wearable massive-sensor computers and Internet of Things (IoTs), are promising in the era of big data. The crucial challenge is about how to maximize the efficiency under coupling constraints like energy budget, computing, and communication. We propose a deep reinforcement learning framework, with a pattern booster and a learning adaptor. This framework has demonstrated optimally maximizes the energy utilization and computing efficiency on the local massive devices under a one-center fifteen-device circumstance.</p><p dir="ltr">Our research and findings are expected to greatly advance the intelligent, real-time, and efficient big data harnessing, leveraging deep learning, edge computing, and efficiency optimization.</p>

This report covers the design research process and results of the 9-week Thesis Project I.A hands-on, Research Through Design approach led the project through an iterative process with a focus on creating functional prototypes and validation with experts to answer the research question: How could proprioceptive wearable technology assist in improving the quality of life for patients of Parkinson’s Disease? Within this main question, focus points have been placed on designing for comfort (i.e. wearability) and well-being with attention to aesthetics. The project builds upon the theories of Design for well-being, Embodied Interaction and Wearable technology and is supported by research on proprioception, Parkinson’s Disease, postural instability and sensory stimuli. The result is a series of models, sketches and prototypes and this report covering the process. The final concept and prototype is a system that monitors upper body posture and provides vibro-tactile feedback on strategically placed areas of the body to guide the patient towards the desired posture.

Wearable technology has made a positive impact in the consumer industry with its focus on adult fitness. Devices and applications are pervasive, inexpensive and are in high demand. Our nation struggles with obesity and health concerns related to poor fitness. However, the research on such technology has been more focused on adults. Therefore, the need to investigate wearable technology for fitness improvement with children is essential. Children lead increasingly sedentary lifestyles through TV watching, technology-use and a reduction in physical activities. Further, our society is exposed to quick food loaded with calories. These factors contribute to the growing epidemic of childhood obesity. The need to educate students early, on their ability to monitor their fitness, is the focus of this research. This dissertation investigated the impact of an integrated technology-enhanced physical education model with 127 fifth grade students over an 11-week period. A detailed analysis, looking at theoretical perspectives across multiple data collections was conducted. This study answered the questions, 1. To what extent can students improve their performance with technology-enhanced physical education? 2. To what extent can students learn to self-monitor their performance levels? How do affective components impact teaching and learning with a technology-enhanced physical education model? Results showed that technology-enhanced physical education does improve performance measures, does improve students' ability to self-regulate and positively impacts student and teachers' affective states. However long term results were inconclusive, stimulating multiple, potential opportunities for continued research.

This thesis explores a concept by Sonvox AB called VoiceUp. The concept is that of a mobile application that communicates with a wearable voice measuring device and visualizes voice information in a way that helps singers. Sonvox current main product is VoxLog—a system for long-term voice monitoring, mostly used for research purposes. Sonvox believes that their voice analysis technology could be relevant to a larger audience. The main goal for the thesis is to explore if a wearable voice measuring device could be relevant to singers, and in what ways. To do this, a needs analysis was conducted where song teachers and singers were interviewed. In order to draw statistical conclusions about the occurrence of needs, a survey was conducted where people with an interest for singing were the targeted respondents. Based on the result from the needs analysis, the VoiceUp concept was refined, resulting in an idea of a product that measures and visualizes how much the user sings and speaks with the aim to increase singers motivation to practice singing more regularly. Based on theory related to self-tracking, a design proving the concept was created, resulting in a mockup and a simple prototype. The mockup and the prototype can together be seen as one example of how self-tracking technology could be relevant to singers.

The field of soft electronics is rapidly growing as there is an increased demand for health monitoring using wearable electronics that conforms to biological tissue. To promote sustainability and reduce electronic waste, it is of interest to find ways to reuse low-value-added commodities, such as protein-rich byproducts, for materials in high-value-added technologies that are degradable at end of use. One recognised byproduct from meat production is the abundant protein collagen, or the hydrolysed derivative gelatine. To overcome the limited mechanical properties of gelatine, it can be functionalised with a polymer with previous use in tissue-engineering and battery encapsulation, namely Poly(Glycerol Sebacate)(PGS), to generate the copolymer PGS-G. The work described in this thesis focuses on PGS and PGS-G polymer characterisation by utilising ATR-FTIR and DSC, but also on material characterisation of mechanical and hydration properties, ionic conductivity, and degradation. The results indicate that the successfully synthesised PGS and PGS-G polymers should not be crosslinked completely to achieve the most flexible mechanical properties, but also that crosslinking density should be tuned to suit the application. Moreover, incorporation of gelatine in PGS resulted in increased hydrophilicity for PGS-G. Finally, it was concluded that PGS is suitable for encapsulation whereas PGS-G could be used as an active component. Future work should include degradation studies in vivo and under environmental aerobic conditions to ensure that the polymers are fully biodegradable. / Mjuk elektronik är ett nytt forskningsområde som utvecklas starkt i takt med den ökade efterfrågan på hälsoövervakning med innovativ elektronik som är mjuk och töjbar vilket möjliggör smidig integrering i biologisk vävnad. För att främja hållbarhet och minska elektroniskt avfall så är det av intresse att återanvända lågt värderade handelsvaror, såsom proteinrika restprodukter från industrin, till att skapa funktionella material för värdeskapande teknologier vilka är nedbrytbara efter användning. En välkänd restprodukt från köttproduktion är proteinet kollagen och dess hydrolyserade derivat gelatin. För att förbättra de mekaniska egenskaperna hos gelatin så kan det funktionaliseras med en polymer, vid namn Poly(Glycerol Sebacate)(PGS), som tidigare har använts för att skapa substitut till biologisk vävnad och batteriinkapsling. Denna reaktion genererar den nya polymeren PGS-G. I det här examensarbetet beskrivs karaktärisering av polymererna PGS och PGS-G, som utfördes med ATR-FTIR och DSC, samt karaktärisering av materialets mekaniska och hydrerande egenskaper men även dess ledningsförmåga och nedbrytbarhet. Resultaten indikerar att polymererna PGS och PGS-G ej bör tvärbindas fullständigt för att uppnå optimala mekaniska egenskaper med avseende på flexibilitet men också att tvärbindningen ska justeras beroende på tillämpningen. Vidare bidrar inkorporeringen av gelatin i PGS till en ökad hydrofilicitet i PGS-G. Slutligen visades det att PGS är lämpligt för inkapsling medan PGS-G kan användas som en aktiv komponent. Innan tillämpning behöver ytterligare studier genomföras med avseende på nedbrytbarhet, dels in vivo, dels i aerobiska förhållanden, för att säkerhetsställa att polymererna är fullständigt nedbrytbara.

This thesis focuses on self-tracking, which mean monitoring and recording information about oneself using digital technologies and its use by runners in the Czech Republic. The main aim of this thesis is to describe the Czech running community through a detailed sociological analysis, and to answer a question: Why runners use self-tracking and how they benefit from it? The theoretical part firstly deals with the topic of self-tracking itself, then examines the uses and gratifications theory and the theory of online communities. The analytical part is devoted to description, analysis and interpretation of the results of the author's own survey, in which 844 runners of whom 754 practice self-tracking participated. Several hypotheses concerning sociodemographic structure, running characteristics, motivation, gratifications and safety were formulated. Five key motives (self-control, orientation to result, self-improvement, habit and social interaction) that lead runners to use self-tracking devices were identified through exploratory factor analysis. The motives vary based on gender and running characteristics (experience with running, runner's level, frequency of running, trainer) that also represent the main influencing factor for self-tracking in general. Self-tracking is closely related to sharing...

Das weite Feld der Digitalisierung findet in Deutschland unter dem Begriff "Industrie 4.0" erste Anwendungen in der Arbeitswelt. Die vorliegende Bachelorarbeit untersucht industrielle Assistenzsysteme. Diese können in ganz unterschiedler Art und Weise dem Mitarbeiter zur Verfügung gestellt werden. Unterstützung bei der Verrichtung von Arbeitsaufgaben ist das Ziel. Dabei können die Systeme als tragbare Kleinstcomputer am Körper eingesetzt werden, oder als umfassendes Verarbeitungssystem von Produktionsdaten im Unternehmen implementiert werden. Betrachtet werden zwei prägnante Beispiele aus diesem Bereich der Assistenz für den Mitarbeiter im produzierenden Unternehmen. Eine ständig wachsende Menge von Assistenzsystemen am Markt lässt sich bislang nur anhand von Werbung und Produktvorstellungen charakterisieren. Das Ziel dieser Arbeit ist es, die beiden Beispielsysteme nach Gesichtspunkten der Arbeitswissenschaft zu untersuchen. Tauglichkeit für das Tagesgeschäft, ergonomische und mitarbeiterfreundliche Bedienung werden betrachtet. In den theoretischen Grundlagen wird ein allgemeines Verständnis der Begriffe aus dem Bereich der Digitalisierung aufgebaut. Weiterhin wird ein Überblick über die verwendeten Beispielsysteme ausgehend von deren Produktvorstellungen gegeben. Diese Systeme werden mit qualitativen Forschungsmethoden durch einen Experten der Branche evaluiert. Kernaussagen aus verschiedenen Bereichen, wie beispielsweise Ergonomie und Einsetzbarkeit werden abgeleitet. / The broad field of digitalisation finds its first applications in the German working environment under the term "Industry 4.0". This bachelor thesis examines industrial assistance systems that can be made available to employees in many different ways, with the goal to support the performance of work tasks. The systems can be used as portable microcomputers on the body or implemented as a comprehensive processing system for company production data. The thesis examines two concise examples from this area of employee assistance in manufacturing companies. To date, a constantly growing number of assistance systems on the market can only be characterised by advertising and product concepts. The aim of this thesis is to analyize the two example systems from an ergonomics point of view as well as suitability for day-to-day business and employee-friendly operations. In the theoretical basics, a general understanding of terms from the field of digitalisation is developed. Furthermore, an overview of the example systems utilized is provided based on their product presentations. These systems are evaluated by an industry expert using qualitative research method to determine core statements from various areas, such as ergonomics and usability.