651 research outputs found

    Prevalent Elements of Consumer Wellbeing in Wearable Technology Use: An Interdisciplinary Systematic Review and Future Research Agenda

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    The impact of wearable technology (wearables) on user wellbeing requires closer examination given the growth in adoption across multiple domains including workplaces, leisure, and healthcare. This paper consolidates research on consumer wellbeing and wearables through an interdisciplinary systematic review of 23 empirical journal articles from psychology, information technology and business domains. Our analysis highlights the principal conceptualisations of wellbeing and offers insights into theories, methods, and key variables in these studies. The findings reveal an overemphasis on adoption and usage of wearables in the literature; a narrow definition of wellbeing; and a limited range of theoretical and methodological perspectives. We propose that future research should be holistic, drawing on mainstream wellbeing theories and examining micro, meso, and macro level conceptualisations of wellbeing. Employing diverse methodologies such as longitudinal, time sampling, cross-sectional, qualitative, and quantitative approaches, and randomised control trials. We develop a framework outlining avenues for future research to extend current understanding in this research domain

    Australian Physical Activity Clinical Practice Guideline for people with moderate to severe traumatic brain injury: Technical Report

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    Background In 2020, the World Health Organization (WHO) released updated physical activity and sedentary behaviour guidelines, which for the first-time included a guideline for people living with disability. The disability guideline is based on evidence from the general population and eight common health conditions causing disability, but did not include people with traumatic brain injury (TBI), nor did it consider the rehabilitation phase of recovery from injury. In 2019, the Australian federal government launched the Traumatic Brain Injury Mission. The Mission was tasked with providing $50 million over 10 years under the Medical Research Future Fund (MRFF) to support research. The goal of the Mission is to better predict recovery outcomes after a TBI, identify the most effective care and treatments, and reduce barriers to support people to live their best possible life after TBI. In 2021, our team was funded through the MRFF TBI Mission to develop an Australian Physical Activity Clinical Practice Guideline for people living with moderate to severe TBI (msTBI). The overarching project to guide the development of the guideline was called BRIDGES (BRain Injury: Developing GuidElineS for physical activities). Objective To develop an Australian clinical practice guideline to support the clinical decision-making of health professionals working with people with msTBI and increase uptake of safe and beneficial physical activity by people living with msTBI. Methods The overarching BRIDGES project was guided by the Exploration Preparation Implementation Sustainment (EPIS) framework. We used a Grading of Recommendations Assessment, Development and Evaluation (GRADE) ADOLOPMENT approach to determine whether to ‘adapt’ or ‘adopt’ the WHO guideline or develop de novo recommendations. We established guideline leadership and development groups, conducted a rapid systematic review to identify direct evidence in TBI, and reviewed guidelines in other relevant health conditions (i.e., stroke, cerebral palsy) to identify indirect evidence. To further inform guideline development and implementation considerations, we conducted an audit of brain injury services in Australia and qualitative consultations with key stakeholders, including people with msTBI. Results Direct evidence for the prescription of physical activity for people with msTBI is limited. The clinical practice guideline developed incorporates 10 de novo evidence-based recommendations with additional good practice points and precautionary practice points to guide clinical decision-making. The physical activity recommended is aerobic exercise, strength training, mobility training, sport and physical recreation, and promotion of physical activity. The physical activity is recommended for children, adolescents, adults, and older adults across the continuum of rehabilitation. Conclusion While there remain evidence gaps that require further research, and further work on how the guideline can be implemented into clinical practice is needed, physical activity interventions tailored to the individual’s goals and needs should be standard clinical practice for health professionals working with people with msTBI in Australian rehabilitation, community, home, and school (for children and adolescents) settings

    Differences in well-being:the biological and environmental causes, related phenotypes, and real-time assessment

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    Well-being is a complex, and multifaceted construct that includes feeling good and functioning well. There is a growing global recognition of well-being as an important research topic and public policy goal. Well-being is related to less behavioral and emotional problems, and is associated with many positive aspects of daily life, including longevity, higher educational achievement, happier marriage, and more productivity at work. People differ in their levels of well-being, i.e., some people are in general happier or more satisfied with their lives than others. These individual differences in well-being can arise from many different factors, including biological (genetic) influences and environmental influences. To enhance the development of future mental health prevention and intervention strategies to increase well-being, more knowledge about these determinants and factors underlying well-being is needed. In this dissertation, I aimed to increase the understanding of the etiology in a series of studies using different methods, including systematic reviews, meta-analyses, twin designs, and molecular genetic designs. In part I, we brought together all published studies on the neural and physiological factors underlying well-being. This overview allowed us to critically investigate the claims made about the biology involved in well-being. The number of studies on the neural and physiological factors underlying well-being is increasing and the results point towards potential correlates of well-being. However, samples are often still small, and studies focus mostly on a single biomarker. Therefore, more well-powered, data-driven, and integrative studies across biological categories are needed to better understand the neural and physiological pathways that play a role in well-being. In part II, we investigated the overlap between well-being and a range of other phenotypes to learn more about the etiology of well-being. We report a large overlap with phenotypes including optimism, resilience, and depressive symptoms. Furthermore, when removing the genetic overlap between well-being and depressive symptoms, we showed that well-being has unique genetic associations with a range of phenotypes, independently from depressive symptoms. These results can be helpful in designing more effective interventions to increase well-being, taking into account the overlap and possible causality with other phenotypes. In part III, we used the extreme environmental change during the COVID-19 pandemic to investigate individual differences in the effects of such environmental changes on well-being. On average, we found a negative effect of the pandemic on different aspects of well-being, especially further into the pandemic. Whereas most previous studies only looked at this average negative effect of the pandemic on well-being, we focused on the individual differences as well. We reported large individual differences in the effects of the pandemic on well-being in both chapters. This indicates that one-size-fits-all preventions or interventions to maintain or increase well-being during the pandemic or lockdowns will not be successful for the whole population. Further research is needed for the identification of protective factors and resilience mechanisms to prevent further inequality during extreme environmental situations. In part IV, we looked at the real-time assessment of well-being, investigating the feasibility and results of previous studies. The real-time assessment of well-being, related variables, and the environment can lead to new insights about well-being, i.e., results that we cannot capture with traditional survey research. The real-time assessment of well-being is therefore a promising area for future research to unravel the dynamic nature of well-being fluctuations and the interaction with the environment in daily life. Integrating all results in this dissertation confirmed that well-being is a complex human trait that is influenced by many interrelated and interacting factors. Future directions to understand individual differences in well-being will be a data-driven approach to investigate the complex interplay of neural, physiological, genetic, and environmental factors in well-being

    AktivitÀtstracker im Alltag: Charakteristika von Motivation und User Diversity zur ErklÀrung individueller Nutzungstrajektorien

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    Die fortlaufend stĂ€rkere Durchdringung unseres Alltags mit digitalen Technologien wird besonders deutlich durch tragbare GerĂ€te wie Smartphones, auf die jederzeit zugegriffen werden kann. Noch einen Schritt weiter gehen körpernah getragene, vernetzte Self-Tracking-Systeme wie AktivitĂ€tstracker, welche kontinuierlich Bewegungsdaten und physiologische Parameter erfassen, algorithmisch aufbereiten und an die Nutzer*innen als quantifiziertes Feedback, oft zur Verhaltensmodifikation, zurĂŒckmelden. Diese spezifische Form der Interaktion zwischen Mensch und Technologie – körpernah, kontinuierlich, quantifiziert, vernetzt und persuasiv – ist fĂŒr die Ingenieurpsychologie besonders relevant, da sie eine sehr enge Verbindung von Körper und Technik erfordert und spezifische Herausforderungen fĂŒr die StĂ€rkung der Selbstbestimmung ihrer Nutzer*innen bereithĂ€lt. Einerseits dienen AktivitĂ€tstracker der erleichterten Selbstreflexion durch Sichtbarmachung von ZusammenhĂ€ngen, die zuvor verborgen blieben, wie etwa zwischen sportlicher AktivitĂ€t und Ruheherzfrequenz. Andererseits sollen AktivitĂ€tstracker die Motivation fĂŒr körperliche VerhaltensĂ€nderungen steigern. Die Nutzung von AktivitĂ€tstrackern bewegt sich also potenziell in einem Spannungsfeld zwischen der Steigerung von Selbstbestimmung durch erweitertes Wissen sowie Aufzeigen von Handlungsoptionen und der EinschrĂ€nkung der Selbstbestimmung durch persuasive Strategien zur Motivationssteigerung. Dieses Spannungsfeld bedingt neue AnsĂ€tze zur Beziehungsgestaltung zwischen Mensch und Trackingsystem. In der empirischen Forschung zur Nutzung von AktivitĂ€tstrackern wird hĂ€ufig darauf hingewiesen, dass ein Großteil der Nutzenden nach wenigen Wochen oder Monaten den kontinuierlichen Gebrauch beendet. Dieser Befund deutet daraufhin, dass Barrieren existieren, die die Langzeitnutzung unwahrscheinlicher machen. Des Weiteren wird immer wieder ĂŒber negative Effekte der Trackernutzung berichtet, beispielsweise Stress. Allerdings ist auch bekannt, dass zahlreiche andere Personen ihr Trackingsystem ĂŒber Jahre hinweg intensiv und erfolgreich gebrauchen. Es lĂ€sst sich also in Bezug auf die Nutzungstrajektorien eine bedeutsame Varianz feststellen, die es zu erklĂ€ren gilt, um Self-Tracking-Anwendungen fĂŒr diverse Nutzende gewinnbringend zu gestalten. Um diesem Vorhaben gerecht zu werden, ist es unabdingbar zu verstehen, welche individuellen Differenzen in der Gruppe der Nutzer*innen die Interaktion mit dem AktivitĂ€tstracker, insbesondere in Bezug auf motivationale Aspekte, prĂ€gen. Dieser Herausforderung stellt sich die vorliegende Dissertation und greift dazu auf etablierte Theorien und Konzepte der Persönlichkeits- und Sozialpsychologie zurĂŒck. Da der theoriegeleitete Einbezug von Personenmerkmalen in die ingenieurpsychologische Forschung noch wenig vorangetrieben war, bestand zu Beginn des Promotionsvorhabens die Notwendigkeit, ein Konstrukt zu konzeptualisieren, welches zum einen auf einem stabilen psychologischen Theoriefundament steht und zum anderen spezifisch auf den Kontext der Mensch-Technik-Interaktion zugeschnitten ist. Im Rahmen der vorliegenden Dissertation wurde aus diesem Grund an der Herleitung der interaktionsbezogenen TechnikaffinitĂ€t (ATI) als kontextspezifische Variante der Denkfreude und ihrer Messbarmachung gearbei-tet. Insgesamt umfassten die Datenerhebungen zur Bestimmung der GĂŒtekriterien der ATI-Skala fĂŒnf DatensĂ€tze mit ĂŒber 1500 Teilnehmenden. Das Resultat der Skalenentwicklung ist ein unidimensionales, ökonomisches, reliables und valides Erhebungsinstrument der interaktionsbezogenen TechnikaffinitĂ€t (Artikel 1). Als relativ stabiles Persönlichkeitsmerkmal, das die Motivation zur Auseinandersetzung mit Technik grundlegend beeinflusst, wurde ATI in die folgenden Studien zur Interaktion zwischen Mensch und AktivitĂ€tstracker miteinbezogen. Um die alltĂ€gliche, individuelle Mensch-Tracker-Interaktion umfassend zu verstehen und erklĂ€ren zu können, wie es zu den unterschiedlichen NutzungsverlĂ€ufen kommt, mĂŒssen verschiedene Phasen der Nutzung untersucht werden. ZunĂ€chst ist zu klĂ€ren, welche Motivatoren Menschen eigentlich dazu veranlassen, mit der Trackernutzung zu beginnen. Weiterhin ist die Nutzungsphase selbst zu beleuchten, um zu beschreiben, wie sich die oben beschriebene, spezifische Form der Trackerinteraktion auf die Nutzungserfahrung und anhaltende Motivation auswirkt und wie sich negative Nutzungskonsequenzen bemerkbar machen. Schließlich sind zum VerstĂ€ndnis der Nutzungstrajektorien die GrĂŒnde fĂŒr den Abbruch zu berĂŒcksichtigen, sodass auch die Phase nach der Nutzung relevant ist. Da sich diese Dissertation dezidiert damit beschĂ€ftigt, wie sich die Interaktion mit AktivitĂ€tstrackern im Alltag gestaltet, ist die Untersuchung der Nutzung in Stichproben von tatsĂ€chlichen bzw. ehemaligen AktivitĂ€tstracker-Nutzer*innen angezeigt. Aus diesem Grund wurden zwei Online-Erhebungen durchgefĂŒhrt, um ebendiese Stichproben zu erreichen. Das Ziel der ersten Studie (N = 210) war die quantitative Analyse von Nutzungsmotivationen sowie unintendierten, negativen Effekten der Trackernutzung im Alltagsgebrauch. Es zeigte sich, dass das Tracken sowohl zum Selbstzweck (intrinsische Motivation) als auch zur Erreichung eines externen Ziels (extrinsische Motivation) durchgefĂŒhrt wird und diese Motivationstypen oft gleichzeitig auftreten. DarĂŒber hinaus konnte gezeigt werden, dass negative Effekte in Form von Motivationsverlusten in Bezug auf die Trackernutzung und die körperliche AktivitĂ€t eine Rolle im Alltag vieler Nutzer*innen spielen. Die Wahrscheinlichkeit des Auftretens dieser Effekte wird teilweise von Personenmerkmalen wie ATI und der Nutzungsmotivation bestimmt (Artikel 2). Die zweite Studie nahm ehemalige Nutzer*innen (N = 159) in den Blick und fokussierte auf die Erfassung der GrĂŒnde fĂŒr den Nutzungsabbruch sowie die StabilitĂ€t der Abbruchentscheidung. Die Ergebnisse machten deutlich, dass zahlreiche Nutzungsbarrieren fĂŒr die Entscheidung, den Tracker abzulegen, ausschlaggebend sind. Außerdem sind die Abbruchentscheidungen oft nicht permanent, was auf eine episodische Trackernutzung hindeutet (Artikel 3). Schließlich wurden wiederum Personenmerkmale und außerdem Interaktionscharakteristika in Betracht gezogen, um die große Varianz hinsichtlich AbbruchgrĂŒnden und -permanenz zu erklĂ€ren. Die Analysen offenbarten unter anderem, dass eine episodische Nutzung (d. h. nicht endgĂŒltige Beendigung) wahrscheinlicher ist, wenn sich die Nutzungsmotivation durch einen hohen Grad an Selbstbestimmung auszeichnet (Artikel 4). Abschließend betonen die Befunde der Dissertation die zentrale Rolle der wahrgenommenen Selbstbestimmung im Kontext der Mensch-Tracker-Interaktion und geben Anlass fĂŒr Designrichtlinien, die die Beziehung zwischen Trackingsystem und Nutzer*in mit all ihren gegenseitigen AbhĂ€ngigkeiten und individuellen Merkmalen berĂŒcksichtigen, um so die Selbstbestimmung zu erhalten oder sogar durch vertieftes Selbstwissen zu stĂ€rken.The ongoing permeation of our daily life with digital technologies is particularly evident in wearable devices such as smartphones, which can be accessed at any time. Wearable, connected self-tracking systems such as activity trackers go even a step further. They continuously record movement data and physiological parameters, process them algorithmically and provide quantified feedback to the user, often for behavioral modification. This specific form of interaction between humans and technology – close to the body, continuous, quantified, connected, and persuasive – is particularly relevant for engineering psychology, as it requires a very close connection between body and technology and poses specific challenges for strengthening the self-determination of its users. That is, on the one hand, activity trackers serve to facilitate self-reflection by revealing relationships which were previously hidden, such as the relationship between physical activity and resting heart rate. On the other hand, activity trackers are intended to enhance motivation for physical behavioral changes. The use of activity trackers thus potentially moves in a field of tension between the increase of self-determination through expanded knowledge as well as the identification of behavioral options and the restriction of self-determination through persuasive strategies to increase motivation. This tension requires new approaches to the design of relationships between people and tracking systems. Empirical research on activity tracker usage often highlights that a large proportion of users stop continuous use after a few weeks or months. This finding suggests the existence of barriers that make long-term use less likely. Furthermore, negative effects of tracker use, such as stress, are repeatedly reported. However, it is also known that many other users have enjoyed intensive and successful use of their tracking system for many years. Thus, a significant variance in usage trajectories can be observed, which needs to be explained in order to make self-tracking applications beneficial for diverse users. To meet this goal, it is essential to understand which individual differences in the group of users shape the interaction with their activity tracker, especially with respect to motivational aspects. This dissertation addresses this challenge by drawing on established theories and concepts of personality and social psychology. At the beginning of the dissertation project, the theory-based inclusion of personal characteristics in engineering psychology had not yet been sufficiently advanced. Thus, there was a need to conceptualize a construct which, on the one hand, stands on a stable psychological theoretical foundation and, on the other hand, is specifically tailored to the context of human-technology interaction. For this reason, the conceptualization of affinity for technology interaction (ATI) as a context-specific variant of need for cognition and its measurability took place within the context of the dissertation. In total, the data collection to determine the quality criteria of the ATI scale comprised five data sets with over 1500 participants. The result of the scale development is a unidimensional, economical, reliable, and valid survey instrument of ATI (Article 1). As a relatively stable personality trait that fundamentally influences motivation to engage with technology, ATI was included in subsequent studies of human-activity tracker interaction. In order to comprehensively understand the everyday, individual human-tracker interaction and to be able to explain how the various usage patterns occur, different phases of usage must be examined. First, it must be clarified which motivators actually cause a person to start using a tracker. Furthermore, the usage phase itself must be examined to describe how the specific form of tracker interaction described above affects the usage experience and ongoing motivation, and how negative usage consequences become apparent. Finally, to understand usage trajectories, the reasons for discontinuation need to be considered, hence the post-usage phase is also relevant. Since this dissertation decidedly focuses on the interaction with activity trackers in everyday life, the investigation of actual or former activity tracker users is indicated. For this reason, two online surveys were conducted to assess these actual (former) users. The aim of the first study (N = 210) was to quantitatively analyze motivations for usage as well as unintended, negative effects of tracker usage in daily use. It was shown that tracking is performed both for an end in itself (intrinsic motivation) and to achieve an external goal (extrinsic motivation), and that these motivation types often occur simultaneously. Furthermore, it was shown that negative effects in terms of motivation losses with respect to tracker use as well as physical activity play a role in many users' daily lives. The likelihood of these effects occurring is partly determined by personal characteristics such as ATI and motivation for usage (Article 2). The second study examined former users (N = 159) and focused on the reasons for discontinuing use and the stability of abandonment. The results indicated that numerous barriers to use are decisive for the decision to discontinue tracking. In addition, abandonment decisions are often not permanent, suggesting episodic tracker use (Article 3). Finally, person and interaction characteristics were considered to explain the large variance in abandonment reasons and permanence. The analyses revealed, among other things, that episodic use (i.e., not definitive termination) is more likely when the motivation for usage is characterized by a high degree of self-determination (Article 4). In conclusion, the findings of the dissertation emphasize the central role of perceived self-determination in the context of human-tracker interaction and give rise to design guidelines that take into account the relationship between the tracking system and the user with all its interdependencies and individual characteristics in order to preserve or even strengthen self-determination through deeper self-knowledge

    Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5

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    This ïŹfth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different ïŹelds of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modiïŹed Proportional ConïŹ‚ict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classiïŹers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identiïŹcation of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classiïŹcation. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classiïŹcation, and hybrid techniques mixing deep learning with belief functions as well

    Stress detection in lifelog data for improved personalized lifelog retrieval system

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    Stress can be categorized into acute and chronic types, with acute stress having short-term positive effects in managing hazardous situations, while chronic stress can adversely impact mental health. In a biological context, stress elicits a physiological response indicative of the fight-or-flight mechanism, accompanied by measurable changes in physiological signals such as blood volume pulse (BVP), galvanic skin response (GSR), and skin temperature (TEMP). While clinical-grade devices have traditionally been used to measure these signals, recent advancements in sensor technology enable their capture using consumer-grade wearable devices, providing opportunities for research in acute stress detection. Despite these advancements, there has been limited focus on utilizing low-resolution data obtained from sensor technology for early stress detection and evaluating stress detection models under real-world conditions. Moreover, the potential of physiological signals to infer mental stress information remains largely unexplored in lifelog retrieval systems. This thesis addresses these gaps through empirical investigations and explores the potential of utilizing physiological signals for stress detection and their integration within the state-of-the-art (SOTA) lifelog retrieval system. The main contributions of this thesis are as follows. Firstly, statistical analyses are conducted to investigate the feasibility of using low-resolution data for stress detection and emphasize the superiority of subject-dependent models over subject-independent models, thereby proposing the optimal approach to training stress detection models with low-resolution data. Secondly, longitudinal stress lifelog data is collected to evaluate stress detection models in real-world settings. It is proposed that training lifelog models on physiological signals in real-world settings is crucial to avoid detection inaccuracies caused by differences between laboratory and free-living conditions. Finally, a state-of-the-art lifelog interactive retrieval system called \lifeseeker is developed, incorporating the stress-moment filter function. Experimental results demonstrate that integrating this function improves the overall performance of the system in both interactive and non-interactive modes. In summary, this thesis contributes to the understanding of stress detection applied in real-world settings and showcases the potential of integrating stress information for enhancing personalized lifelog retrieval system performance

    Eating Behavior In-The-Wild and Its Relationship to Mental Well-Being

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    The motivation for eating is beyond survival. Eating serves as means for socializing, exploring cultures, etc. Computing researchers have developed various eating detection technologies that can leverage passive sensors available on smart devices to automatically infer when and, to some extent, what an individual is eating. However, despite their significance in eating literature, crucial contextual information such as meal company, type of food, location of meals, the motivation of eating episodes, the timing of meals, etc., are difficult to detect through passive means. More importantly, the applications of currently developed automated eating detection systems are limited. My dissertation addresses several of these challenges by combining the strengths of passive sensing technologies and EMAs (Ecological Momentary Assessment). EMAs are a widely adopted tool used across a variety of disciplines that can gather in-situ information about individual experiences. In my dissertation, I demonstrate the relationship between various eating contexts and the mental well-being of college students and information workers through naturalistic studies. The contributions of my dissertation are four-fold. First, I develop a real-time meal detection system that can detect meal-level episodes and trigger EMAs to gather contextual data about one’s eating episode. Second, I deploy this system in a college student population to understand their eating behavior during day-to-day life and investigate the relationship of these eating behaviors with various mental well-being outcomes. Third, based on the limitations of passive sensing systems to detect short and sporadic chewing episodes present in snacking, I develop a snacking detection system and operationalize the definition of snacking in this thesis. Finally, I investigate the causal relationship between stress levels experienced by remote information workers during their workdays and its effect on lunchtime. This dissertation situates the findings in an interdisciplinary context, including ubiquitous computing, psychology, and nutrition.Ph.D

    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 GerĂ€teklassen wie Tablets, Smartphones oder Smartwatches erobern unseren Alltag. Diese Entwicklung birgt aber auch Probleme, denn die vorherrschenden berĂŒhrungsempfindlichen OberflĂ€chen berĂŒcksichtigen kaum haptische QualitĂ€ten und erfordern daher die volle Aufmerksamkeit ihrer Nutzer:innen. Im Vergleich zu traditionellen Werkzeugen und analogen Schnittstellen bleiben die menschlichen FĂ€higkeiten 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 GegenstĂ€nde des Alltags digital zu erweitern und anhand geeigneter Designparameter und EntwurfsrĂ€ume systematisch zu untersuchen. In dieser Dissertation wird daher untersucht, wie MaterialitĂ€t und DigitalitĂ€t nahtlos ineinander ĂŒbergehen können. Es soll erforscht werden, wie kĂŒnftige Benutzungsschnittstellen nĂŒtzliche digitale Funktionen bereitstellen können, ohne ihre physischen Eigenschaften und vertrauten Nutzungsmuster in der realen Welt zu verlieren. Die Entwicklung solcher hybriden AnsĂ€tze wirft jedoch ĂŒbergreifende 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 unterstĂŒtzen? FĂŒr eine systematische Untersuchung stĂŒtzt 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 ĂŒber visuelle Erweiterungen von UhrarmbĂ€ndern bis hin zu neuartigen Prototyping-Tools fĂŒr intelligente KleidungsstĂŒcke. Um neue DesignansĂ€tze aufzuzeigen, integrieren nahezu alle visuelles Feedback und haptische Eingaben, um Alternativen zu Standard-EingabemodalitĂ€ten auf starren Pixelbildschirmen zu schaffen. Die Dissertation hat gezeigt, wie wertvoll es sein kann, bekannte, analoge Anwendungen zu ĂŒberdenken und sie dabei gleichzeitig mit Bedacht digital zu erweitern. Dabei umfasst die vorliegende Arbeit sowohl realisierte technische Forschungsplattformen als auch ĂŒbergreifende konzeptionelle Arbeiten, Nutzerstudien und technische Experimente sowie die Analyse existierender Forschungsarbeiten
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