201 research outputs found

    Blending the Material and Digital World for Hybrid Interfaces

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    The development of digital technologies in the 21st century is progressing continuously and new device classes such as tablets, smartphones or smartwatches are finding their way into our everyday lives. However, this development also poses problems, as these prevailing touch and gestural interfaces often lack tangibility, take little account of haptic qualities and therefore require full attention from their users. Compared to traditional tools and analog interfaces, the human skills to experience and manipulate material in its natural environment and context remain unexploited. To combine the best of both, a key question is how it is possible to blend the material world and digital world to design and realize novel hybrid interfaces in a meaningful way. Research on Tangible User Interfaces (TUIs) investigates the coupling between physical objects and virtual data. In contrast, hybrid interfaces, which specifically aim to digitally enrich analog artifacts of everyday work, have not yet been sufficiently researched and systematically discussed. Therefore, this doctoral thesis rethinks how user interfaces can provide useful digital functionality while maintaining their physical properties and familiar patterns of use in the real world. However, the development of such hybrid interfaces raises overarching research questions about the design: Which kind of physical interfaces are worth exploring? What type of digital enhancement will improve existing interfaces? How can hybrid interfaces retain their physical properties while enabling new digital functions? What are suitable methods to explore different design? And how to support technology-enthusiast users in prototyping? For a systematic investigation, the thesis builds on a design-oriented, exploratory and iterative development process using digital fabrication methods and novel materials. As a main contribution, four specific research projects are presented that apply and discuss different visual and interactive augmentation principles along real-world applications. The applications range from digitally-enhanced paper, interactive cords over visual watch strap extensions to novel prototyping tools for smart garments. While almost all of them integrate visual feedback and haptic input, none of them are built on rigid, rectangular pixel screens or use standard input modalities, as they all aim to reveal new design approaches. The dissertation shows how valuable it can be to rethink familiar, analog applications while thoughtfully extending them digitally. Finally, this thesis’ extensive work of engineering versatile research platforms is accompanied by overarching conceptual work, user evaluations and technical experiments, as well as literature reviews.Die Durchdringung digitaler Technologien im 21. Jahrhundert schreitet stetig voran und neue Geräteklassen wie Tablets, Smartphones oder Smartwatches erobern unseren Alltag. Diese Entwicklung birgt aber auch Probleme, denn die vorherrschenden berührungsempfindlichen Oberflächen berücksichtigen kaum haptische Qualitäten und erfordern daher die volle Aufmerksamkeit ihrer Nutzer:innen. Im Vergleich zu traditionellen Werkzeugen und analogen Schnittstellen bleiben die menschlichen Fähigkeiten ungenutzt, die Umwelt mit allen Sinnen zu begreifen und wahrzunehmen. Um das Beste aus beiden Welten zu vereinen, stellt sich daher die Frage, wie neuartige hybride Schnittstellen sinnvoll gestaltet und realisiert werden können, um die materielle und die digitale Welt zu verschmelzen. In der Forschung zu Tangible User Interfaces (TUIs) wird die Verbindung zwischen physischen Objekten und virtuellen Daten untersucht. Noch nicht ausreichend erforscht wurden hingegen hybride Schnittstellen, die speziell darauf abzielen, physische Gegenstände des Alltags digital zu erweitern und anhand geeigneter Designparameter und Entwurfsräume systematisch zu untersuchen. In dieser Dissertation wird daher untersucht, wie Materialität und Digitalität nahtlos ineinander übergehen können. Es soll erforscht werden, wie künftige Benutzungsschnittstellen nützliche digitale Funktionen bereitstellen können, ohne ihre physischen Eigenschaften und vertrauten Nutzungsmuster in der realen Welt zu verlieren. Die Entwicklung solcher hybriden Ansätze wirft jedoch übergreifende Forschungsfragen zum Design auf: Welche Arten von physischen Schnittstellen sind es wert, betrachtet zu werden? Welche Art von digitaler Erweiterung verbessert das Bestehende? Wie können hybride Konzepte ihre physischen Eigenschaften beibehalten und gleichzeitig neue digitale Funktionen ermöglichen? Was sind geeignete Methoden, um verschiedene Designs zu erforschen? Wie kann man Technologiebegeisterte bei der Erstellung von Prototypen unterstützen? Für eine systematische Untersuchung stützt sich die Arbeit auf einen designorientierten, explorativen und iterativen Entwicklungsprozess unter Verwendung digitaler Fabrikationsmethoden und neuartiger Materialien. Im Hauptteil werden vier Forschungsprojekte vorgestellt, die verschiedene visuelle und interaktive Prinzipien entlang realer Anwendungen diskutieren. Die Szenarien reichen von digital angereichertem Papier, interaktiven Kordeln über visuelle Erweiterungen von Uhrarmbändern bis hin zu neuartigen Prototyping-Tools für intelligente Kleidungsstücke. Um neue Designansätze aufzuzeigen, integrieren nahezu alle visuelles Feedback und haptische Eingaben, um Alternativen zu Standard-Eingabemodalitäten auf starren Pixelbildschirmen zu schaffen. Die Dissertation hat gezeigt, wie wertvoll es sein kann, bekannte, analoge Anwendungen zu überdenken und sie dabei gleichzeitig mit Bedacht digital zu erweitern. Dabei umfasst die vorliegende Arbeit sowohl realisierte technische Forschungsplattformen als auch übergreifende konzeptionelle Arbeiten, Nutzerstudien und technische Experimente sowie die Analyse existierender Forschungsarbeiten

    Forensic investigation of small-scale digital devices: a futuristic view

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    Small-scale digital devices like smartphones, smart toys, drones, gaming consoles, tablets, and other personal data assistants have now become ingrained constituents in our daily lives. These devices store massive amounts of data related to individual traits of users, their routine operations, medical histories, and financial information. At the same time, with continuously evolving technology, the diversity in operating systems, client storage localities, remote/cloud storages and backups, and encryption practices renders the forensic analysis task multi-faceted. This makes forensic investigators having to deal with an array of novel challenges. This study reviews the forensic frameworks and procedures used in investigating small-scale digital devices. While highlighting the challenges faced by digital forensics, we explore how cutting-edge technologies like Blockchain, Artificial Intelligence, Machine Learning, and Data Science may play a role in remedying concerns. The review aims to accumulate state-of-the-art and identify a futuristic approach for investigating SSDDs

    Artificial Intelligence for Cognitive Health Assessment: State-of-the-Art, Open Challenges and Future Directions

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    The subjectivity and inaccuracy of in-clinic Cognitive Health Assessments (CHA) have led many researchers to explore ways to automate the process to make it more objective and to facilitate the needs of the healthcare industry. Artificial Intelligence (AI) and machine learning (ML) have emerged as the most promising approaches to automate the CHA process. In this paper, we explore the background of CHA and delve into the extensive research recently undertaken in this domain to provide a comprehensive survey of the state-of-the-art. In particular, a careful selection of significant works published in the literature is reviewed to elaborate a range of enabling technologies and AI/ML techniques used for CHA, including conventional supervised and unsupervised machine learning, deep learning, reinforcement learning, natural language processing, and image processing techniques. Furthermore, we provide an overview of various means of data acquisition and the benchmark datasets. Finally, we discuss open issues and challenges in using AI and ML for CHA along with some possible solutions. In summary, this paper presents CHA tools, lists various data acquisition methods for CHA, provides technological advancements, presents the usage of AI for CHA, and open issues, challenges in the CHA domain. We hope this first-of-its-kind survey paper will significantly contribute to identifying research gaps in the complex and rapidly evolving interdisciplinary mental health field

    A Mobile Health Platform for Automated Diet Monitoring Using Continuous Glucose Monitors and Context-Aware Machine Learning

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    Automated diet monitoring, an important tool in preventing healthy individuals and those with pre-diabetes from developing Type 2 Diabetes, requires automatic eating detection and estimation of the macronutrient contents of ingested food. While signals from continuous glucose monitors may track the post-prandial glucose response (glucose response after eating) and use this for estimation of nutritional information, the proper identification and segmentation of these periods of eating require additional sensing modalities and contextual information. In this work, we developed a framework for machine learning modeling to detect eating periods, properly segment post-prandial glucose responses, and estimate nutritional content from these segments in real-world environments using data captured from a continuous glucose monitor and augmented with con-textual data from smartwatch wearable sensors. Using a custom-developed platform, we conduct a human subject study where participants were free to eat what they wished, when they wished, logging data and wearing a set of sensors. To aid future, just-in-time diet monitoring applications, we found that contextual data improved eating moment detection and thus enables real-time macronutrient estimation

    Towards using Cough for Respiratory Disease Diagnosis by leveraging Artificial Intelligence: A Survey

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    Cough acoustics contain multitudes of vital information about pathomorphological alterations in the respiratory system. Reliable and accurate detection of cough events by investigating the underlying cough latent features and disease diagnosis can play an indispensable role in revitalizing the healthcare practices. The recent application of Artificial Intelligence (AI) and advances of ubiquitous computing for respiratory disease prediction has created an auspicious trend and myriad of future possibilities in the medical domain. In particular, there is an expeditiously emerging trend of Machine learning (ML) and Deep Learning (DL)-based diagnostic algorithms exploiting cough signatures. The enormous body of literature on cough-based AI algorithms demonstrate that these models can play a significant role for detecting the onset of a specific respiratory disease. However, it is pertinent to collect the information from all relevant studies in an exhaustive manner for the medical experts and AI scientists to analyze the decisive role of AI/ML. This survey offers a comprehensive overview of the cough data-driven ML/DL detection and preliminary diagnosis frameworks, along with a detailed list of significant features. We investigate the mechanism that causes cough and the latent cough features of the respiratory modalities. We also analyze the customized cough monitoring application, and their AI-powered recognition algorithms. Challenges and prospective future research directions to develop practical, robust, and ubiquitous solutions are also discussed in detail.Comment: 30 pages, 12 figures, 9 table

    A study of the use of technology in teaching students with executive function difficulties (EFD) in the Kingdom of Saudi Arabia: Teachers’ and parents’ perspectives

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    This qualitative multiple case study explores teachers' and parents' views of the use of technology in addressing executive function difficulties (EFD) in primary schools in Saudi Arabia. Executive functioning skills (EFS) are crucial high cognitive functions that control thoughts, emotions, and actions, and determine the ability of students to adapt to different social settings in both mainstream educational and home contexts. Primary executive functions, such as cognitive flexibility (CF), working memory (WM), inhibitory control (IC), and attention are critical components of behavioural and cognitive development and have a strong association with academic performance. The rapid rate of technological integration in special education, notably in primary schools, calls for greater understanding of the role technology can play in addressing EFD. This study draws on data collected via 21 semi- structured interviews with teachers and parents and 18 classroom observations in three primary schools in Saudi Arabia to explore how technology was employed in the classroom to support students with EFD. Thematic analysis followed by cross-case analysis was informed by theoretical perspectives by Vygotsky’s cognitive development theory and the concepts of scaffolding and the zone of proximal development. The findings show that teachers and parents hold positive opinions about the role of technology in addressing EFD. Although there was a lack of awareness about the term ‘executive function difficulties (EFD)’ amongst both parents and teachers, they were familiar with the underlying challenges. Gaps in knowledge were also identified in relation to effective and context-specific uses of technology and interventions for students with EFD. Variability in students' manifestation of EFD, the choice of technological affordances, and the accommodations required in mainstream classrooms are important considerations for the effective use of technology. However, the analysis identified various challenges which limit teachers' optimal use of technology and their ability to determine the relevant affordances and accommodations. In light of these findings, and from a constructivist paradigm, recommendations for teachers, for practice, and for policymakers are made to address these challenges and promote more effective use of technology to support students with EFD in Saudi schools. The research fundamentally contributes to understanding EFD and its potential to regulate difficulties in different neurodevelopmental groups in the Saudi context. This research is the first of its kind in the Saudi context and presents meaningful implications for future research, specifically to expand the body of evidence on how EF skills may provide competencies in relation to Theory of Mind (ToM), and how technology may function as a mediating tool. The findings also raise crucial questions to be addressed in future studies to explore the underpinning mechanisms of EF-ToM association, and how use of technology can facilitate in the context of behavioural synchronisation, so as to lead to improvement in EFD using the concept of ToM. The thesis suggests potential recommendations for teachers, policymakers, and the educational ministry to address gaps in EFD. These recommendations include developing EFD-specific technological affordances, capabilities, and functions, enabling customisation of applications with EFD-specific design specifications and features, and catering to the training and development needs of teachers through teacher-oriented programs, workshops and conferences. This will enhance their knowledge base of EFD and improve the overall educational experience in the Saudi context

    Accessibility of Health Data Representations for Older Adults: Challenges and Opportunities for Design

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    Health data of consumer off-the-shelf wearable devices is often conveyed to users through visual data representations and analyses. However, this is not always accessible to people with disabilities or older people due to low vision, cognitive impairments or literacy issues. Due to trade-offs between aesthetics predominance or information overload, real-time user feedback may not be conveyed easily from sensor devices through visual cues like graphs and texts. These difficulties may hinder critical data understanding. Additional auditory and tactile feedback can also provide immediate and accessible cues from these wearable devices, but it is necessary to understand existing data representation limitations initially. To avoid higher cognitive and visual overload, auditory and haptic cues can be designed to complement, replace or reinforce visual cues. In this paper, we outline the challenges in existing data representation and the necessary evidence to enhance the accessibility of health information from personal sensing devices used to monitor health parameters such as blood pressure, sleep, activity, heart rate and more. By creating innovative and inclusive user feedback, users will likely want to engage and interact with new devices and their own data

    Evaluating footwear “in the wild”: Examining wrap and lace trail shoe closures during trail running

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    Trail running participation has grown over the last two decades. As a result, there have been an increasing number of studies examining the sport. Despite these increases, there is a lack of understanding regarding the effects of footwear on trail running biomechanics in ecologically valid conditions. The purpose of our study was to evaluate how a Wrap vs. Lace closure (on the same shoe) impacts running biomechanics on a trail. Thirty subjects ran a trail loop in each shoe while wearing a global positioning system (GPS) watch, heart rate monitor, inertial measurement units (IMUs), and plantar pressure insoles. The Wrap closure reduced peak foot eversion velocity (measured via IMU), which has been associated with fit. The Wrap closure also increased heel contact area, which is also associated with fit. This increase may be associated with the subjective preference for the Wrap. Lastly, runners had a small but significant increase in running speed in the Wrap shoe with no differences in heart rate nor subjective exertion. In total, the Wrap closure fit better than the Lace closure on a variety of terrain. This study demonstrates the feasibility of detecting meaningful biomechanical differences between footwear features in the wild using statistical tools and study design. Evaluating footwear in ecologically valid environments often creates additional variance in the data. This variance should not be treated as noise; instead, it is critical to capture this additional variance and challenges of ecologically valid terrain if we hope to use biomechanics to impact the development of new products

    FIT FOR USE ASSESSMENT OF BIOZEN AS A BIOMETRIC SENSOR CONCENTRATOR FOR REMOTE PATIENT MONITORING

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    In recent years, COVID-19 highlighted the importance of virtual health solutions with regard to improving patient health and conserving valuable hospital resources. Currently, the Defense Health Agency (DHA) does not own a remote patient-monitoring solution and relies on external commercial entities to provide the application and services. This could potentially lead to the DHA not retaining complete data ownership when patient data would reside on or traverse through commercial remote patient-monitoring solutions. This thesis evaluates BioZen, a DHA-owned biomedical sensor concentrator designed to run on a mobile phone, as a remote patient-monitoring tool. From this analysis, several key measures of effectiveness and measures of performance for remote patient-monitoring tools are identified and operationalized to measure the overall value BioZen brings to the DHA. Based on this research, it was found that the current build of BioZen, 2.0.0, is unable to meet any of the measures outlined in the study as a remote patient-monitoring tool. A future build of BioZen, or any remote patient-monitoring tool, could then be assessed using the measures of effectiveness and measures of performance within this study to determine the overall value brought to the DHA.Defense Health Agency, 7700 Arlington Boulevard, Falls Church, VA 22042Captain, United States ArmyLieutenant, United States NavyApproved for public release. Distribution is unlimited
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