Technical advancements allow for increasingly sophisticated methods of self-tracking. Despite this, the ways in which we interact with our numerical representations seem not to have progressed equally, making it challenging to use the data in meaningful ways. This prevents us from making the most of self-tracking in order to facilitate a healthier lifestyle and self-improvement. In this study, we show how Dourish’s Embodied Interaction can motivate acting based on self-tracked data, with the example of walking. We conducted evaluations with experts and users of a software prototype that is built on the notion of embodiment. Based on the results, we draw a number of conclusions about the usefulness of Embodied Interaction in this area: That digital applications can support physical activity through providing context, motivation and feedback; that self-tracking applications should focus on goals rather than data; that motivation might be increased by placing the users efforts in a context that transcends them as individuals; and that Embodied Interaction offers a rich field of possibilities which are yet to be discovered.

In recent years, it is becoming more common for people to use applications or devices that keep track of their activities, such as fitness activities, places they visit, the music they listen to, and pictures they take. These data are used by the services for various purposes, but usually there are limitations for the users to explore or interact with them. This project investigates a new approach of visualizing such Quantified Self data, in a meaningful and enjoyable way that gives the users insights into their data. This thesis discusses the feasibility of creating a system that allows users to connect the activity tracking applications they already use, analyse the amount of activities, and then present the resulting information. The visualization of the information is done with an avatar that maps the different activities the user is engaged with, along with the activity levels, as graphical features. Within the scope of this work, several user studies were conducted and a system prototype was implemented to explore how to build, using web technologies, such a system that aggregates and analyses personal activity data, and also to determine what kind of data should and can be collected, to provide meaningful information to the users. Furthermore, it was investigated how a possible design for the avatar could look like, to be clearly understood by the users.

Complex diseases such as cancer, cardiovascular diseases and diabetes are often diagnosed too late, which significantly impairs treatment options and, in turn, lowers patient’s survival rate drastically and increases the costs significantly. Moreover, the growth of medical data is faster than the ability of healthcare systems to utilize them. Almost 80% of medical data are unstructured, but they are clinically relevant. On the other hand, technological advancements have made it possible to create different  igital health solutions where healthcare and ICT meet. Also, some individuals have already started to measure their body function parameters, track their health status, research their symptoms and even intervene in treatment options which means a great deal of data is being produced and also indicates that patient-driven health care models are transforming how health care functions. These models include quantified self-tracking, consumer-personalized-medicine and health social networks. This research aims to present an open innovation digital health platform which creates value  y using the overlaps between healthcare, information technology and artificial intelligence. This platform could potentially be utilized for early detection of complex diseases by leveraging Big Data technology which could improve awareness by recognizing pooled symptoms of a specific disease. This would enable individuals to effortlessly and quantitatively track and become aware of changes in their health, and through a dialog with a doctor, achieve diagnosis at a significantly earlier stage. This thesis focuses on a case study of the platform for detecting breast cancer at a  ignificantly earlier stage. A qualitative research method is implemented through reviewing the literature, determining the knowledge gap, evaluating the need, performing market research, developing a conceptual prototype and presenting the open innovation platform. Finally, the value creation, applications and challenges of such platform are investigated, analysed and discussed based on the collected data from interviews and surveys. This study combines an explanatory and an analytical research approach, as it aims not only to describe the case, but also to explain the value creation for different stakeholders in the value chain. The findings indicate that there is an urgent need for early diagnosis of complex diseases such as breast cancer) and also handling direct and indirect consequences of late diagnosis. A significant outcome of this research is the conceptual prototype which was developed based on the general proposed concept through a customer development process. According to the conducted surveys, 95% of the cancer patients and 84% of the healthy individuals are willing to use the proposed platform. The results indicate that it can create significant values for patients, doctors, academic institutions, hospitals and even healthy individuals.

I Abstract (in English): Diploma thesis Visual lifelogging: automatic memories and picturing ordinary deals with the topic of visual lifelogging in the context of current visual culture. It describes visual lifelogging in the context of photography and as an amplification of human abilities. Diploma thesis deals with history and lifelogging as a whole and it describes its forms, describes the tools of lifelogging and it deals also with topics of surveillance and its contrary, sousveillance. It explores visual lifelogging mostly from the photographic point of view and it deals with the use of different technologies to augment human memory or other human abilities.

This thesis is examining in which way the quantified self approach can have the effect on motivation in the process of education. The aim of this thesis is to determine whether the usage of application which is tracking and recording the study progress can have the influence on motivation of users and moreover, to evaluate the most effective motivational techniques used in these kinds of applications. Firstly, terms like motivation, self-regulated learning and the Quantified Self movement are clarified. Moreover, some of the researches from the field of tracking of educational and self-educational progress are described. Furthermore, various of motivational techniques are examined. In the part of the research, by the in-depth interviews it is examined the influence of the application Todait on the motivation of users and by the quantitative survey of questionnaire it is inquired what other functions would users prefer.

Cette thèse sur travaux explore l’adoption des technologies et des pratiques de quantification de soi avec un positionnement critique. Il s’agit de mieux comprendre l’expérience des utilisateurs avec les technologies de quantification de soi, telles que les bracelets connectés, et de questionner la contribution réelle de ces technologies au bien-être et à la santé des individus. Le premier essai présente une revue de la littérature systématique sur la quantification de soi et un agenda de recherche pour les chercheurs en management. Le deuxième essai est une étude qualitative qui révèle les relations de pouvoir qu’entretiennent les utilisateurs avec la technologie. Le troisième essai s’intéresse aux mécanismes sous-jacents qui guident la décision de l’utilisateur afin d’identifier les facteurs d’adoption d’une technologie de quantification de soi. / This thesis by articles explores the adoption of technologies and practices of quantified-self with a critical stance. The aim is to have a better understanding of users' experiences with self-quantization technologies, such as connected bracelets, and to question the real contribution of these technologies to the well-being and health of individuals. The first essay presents a systematic literature review on quantified-self and a research agenda for business researchers. The second essay is a qualitative study that reveals the power relationships that users have with technology. The third essay focuses on the underlying mechanisms that guide the user's decision in order to identify the factors that lead to the adoption of a quantified-self technology.

Användandet av bärbar teknologi förväntas öka och bli den största trenden inom träning ochhälsa. Klädesplagg, accessoarer och plåster används för att avslöja värden om allt frånhjärtfrekvens till sömnmönster till dietvanor. I takt med det ökande intresset för fysiologiskadata börjar även bärbar teknologi för kognitiva värden träda fram i form avkonsumenttillgängliga EEG-scanners. Aktörer som Muse, Neurosky och Emotiv ledermarknaden framåt och tillåter personer läsa av sina hjärnfrekvenser direkt hemifrån soffan.Syftet med studien är att undersöka intresse och förväntningar på kognitivt mätbar bärbarteknologi. Vidare är syftet även att utveckla en prototyp för att demonstrera hur en applikationtill denna typ av teknologi skulle kunna tänkas se ut, samt bidra till forskning ochmarknadsutveckling inom området. Studien är primärt utförd med en kvalitativ metod i form av en fokusgrupp, en semistrukturerad intervju och ett användbarhetstest, men visar även påkvantitativa inslag i form av ett enkätutskick där 139 anonyma respondenter deltog.Studiens slutsats pekar på ett intresse bland potentiella konsumenter för en mindre synlig bärbar teknologisk produkt med möjlighet att mäta värden som stressnivåer. Ett mindre intresse uttrycktes för delningsfunktioner och mätande av emotionella tillstånd. Produktens applikation förväntas vara lättförståelig och erbjuda både enklare och mer detaljerade data. De potentiella konsumenterna förväntar även att applikationen tydligt visualiserar vilka värden som mäts, samt att förbättringsförslag finns att tillgå. / The use of wearable devices is expected to increase and become the largest trend in fitness.Clothes, accessories and patches are used to reveal values ranging from heart rate to sleeppatterns to diet habits. In keeping with the growing interest in physiological data, portabletechnology for cognitive values are also emerging in the form of consumer-accessible EEGscanners. Actors like Muse, Neurosky and Emotiv are leading the market forward and allowspeople to read their brain frequencies directly from the couch in their home.The purpose of this study is to investigate the interest and expectations of cognitive measurable portable technology. Furthermore, the aim is also to develop a prototype to demonstrate how an application for this kind of technology could look, as well as contribute to research and market development in the area. The study was primarily done with a qualitative method in the form of a focus group, a semi-structured interview and a usability test, but also shows quantitative elements in the form of a poll where 139 anonymous respondents participated. The study's conclusion points to an interest among potential consumers for a less visible portable technological product with the ability to measure values such as stress levels. A lesser interest was expressed for sharing functions and measurement of emotional states. The product's application is expected to be easily understood and offers both simpler and more detailed data. Potential consumers also expect the application to clearly visualize which values are measured and that improvement proposals are available.

Transport systems account for a large part of the worlds CO2 emissions. In order to reach goals, set to lower emissions, we need to travel less by car and increase the use of sustainable means of transportation. Through the use of self-tracking devices and by visualizing the data collected, individuals can learn about, and discover, habits, patterns and practices amongst themselves. In this thesis, the question of how much individuals know about their own CO2 emissions created from the modes of transportation they use on an everyday basis, is explored. The paper examines how a visualization of personal movement and transport data affects individuals' understanding of their own CO2 emission as well as their motivation towards using more sustainable modes of transportation. A two-week user-study was conducted with 15 participants. The participants tracked their movements and transports using a mobile application on a smart phone, and their data was presented in a web-application. Prior and post to the user-study, a self-evaluation questionnaire based on the COM-B model was handed out. Results showed that participants' understanding increased regarding putting their emission amounts in relation to what is low and what is high between transportation modes. An increased awareness of personal transportation patterns and what the environmental impact the choice of transport mode has, was indicated. Further, participants' motivation towards using more sustainable modes of transportation seems to be dependent on realizing if they have low or high emissions but also if there exist available alternative transport options to switch to. / Transportsystem står för en stor del av världens koldioxidutsläpp. För att nå utsatta utsläppsmål måste färre resor göras med bil och användandet av hållbara transportmedel öka hos individer. Genom att börja spåra sig själv inom olika områden, och genom att bli presenterad sin insamlade data, kan individer upptäcka och lära sig om vanor, mönster och praxis bland dem själva. I denna avhandling undersöks hur mycket individer vet om sina egna koldioxidutsläpp som skapas av de transportmedel som de använder dagligen. I studien undersöks hur en visualisering av personlig rörelse- och transportdata påverkar individens förståelse av sitt eget koldioxidavtryck samt dennes motivation till att använda mer hållbara transportmedel. En användarstudie genomfördes med 15 deltagare över två veckor. Under denna period fick deltagarna spåra sina förflyttningar och vilka transportmedel som användes med hjälp av en applikation på en smart telefon. Det insamlade transportdata presenterades därefter i en webb- applikation med avseende på deltagarnas koldioxidutsläpp. Innan och efter användarstudien fick deltagarna svara på ett självutvärderingsformulär baserat på beteendemodellen COM-B. Resultaten visade att deltagarnas förståelse ökade när det gäller att sätta sina utsläppsmängder i förhållande till vad som är lågt respektive högt mellan olika transportmedel. En ökad medvetenhet om personliga transportmönster och hur stor miljöpåverkan valet av transportläge har, indikerades. Vidare verkar deltagarnas motivation att använda mer hållbara transportmedel vara beroende utav om de inser att de har låga eller höga utsläpp, men också om det finns tillgängliga, alternativa, transportmedel att byta till.

This thesis investigates the relation between human and smartwatch by exploring the experiences of four Swedish long-distance runners who use digital technology to self-track their running activities. By examining the participating runners’ use of their smartwatches and smartwatch data as postphenomenological human-technology relations (Ihde, 1990), this thesis offers a perspective on the use of wearable self-tracking technology as augmenting human experience through digital data. The empirical material was gathered through semi-structured interviews with the participating runners. In the analysis of the material, a computer-assisted qualitative data analysis software is used to transcribe and code the material following a concept-driven approach influenced by Ritchie and Lewis’ Thematic Framework Method (2003). The coded transcripts are summarized in thematic charts based on postphenomenological human-technology relations developed by Ihde (1990) and Verbeek (2008) along with an understanding of data influenced by the field of critical data studies and adjacent work (e.g. Iliadis & Russo, 2016; Kitchin, 2014; van Dijck, 2014; Edmond et al., 2022). The runner-smartwatch relations that are analyzed in this thesis showcase how the digital data produced in self-tracking practices become part of the self-tracker’s experiences by being incorporated in a runner-data assemblage. Viewing the runner-smartwatch relation as a type of augmentation relation (Verbeek, 2008), this thesis further suggests that the digital data function as an augmenting layer through which the running activity is experienced.

Industrie 4.0 und aktuelle Entwicklungen in dem Bereich der produzierenden Unternehmen erfordern hohe Anpassungsleistungen von Menschen und von Maschinen gleichermaßen. In Smart Factories werden Produktionsmitarbeiter zu Wissensarbeitern. Dazu bedarf es neben neuen, intelligenten, technischen Lösungen auch neuer Ansätze für Arbeitsorganisation, Trainings- und Qualifizierungskonzepte, die mit adaptierbaren technischen Systemen flexibel zusammenarbeiten. Das durch die EU geförderte Projekt Factory2Fit entwickelt Lösungen für die Mensch-Technik-Interaktion in automatisierten Produktionssystemen, welche eine hohe Anpassungsfähigkeit an die Fähigkeiten, Kompetenzen und Präferenzen der individuellen Mitarbeiter bieten und damit gleichzeitig den Herausforderungen einer höchst kundenindividuellen Produktion gewachsen sind. Im vorliegenden Beitrag werden die grundlegenden Ziele und Ideen des Projektes vorgestellt sowie die Ansätze des Quantified-self im Arbeitskontext, die adaptive Automatisierung inklusive der verschiedenen Level der Automation sowie die spezifische Anwendung des partizipatorischen Designs näher beleuchtet. In den nächsten Arbeitsschritten innerhalb des Projektes gilt es nun, diese Konzepte um- und einzusetzen sowie zu validieren. Die interdisziplinäre Arbeitsweise sowie der enge Kontakt zwischen Wissenschafts-, Entwicklungs- und Anwendungspartnern sollten dazu beitragen, den Herausforderungen bei der Realisierung erfolgreich zu begegnen und zukunftsträchtige Smart Factory-Lösungen zu implementieren. Das Projekt Factory2Fit wird im Rahmen von Horizon 2020, dem EU Rahmenprogramm für Forschung und Innovation (H2020/2014-2020), mit dem Förderkennzeichen 723277 gefördert.