Behaviour-aware mobile touch interfaces
| dc.contributor.author | Buschek, Daniel | |
| dc.date.accessioned | 2023-09-03T11:47:52Z | |
| dc.date.available | 2023-09-03T11:47:52Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | Mobile touch devices have become ubiquitous everyday tools for communication, information, as well as capturing, storing and accessing personal data. They are often seen as personal devices, linked to individual users, who access the digital part of their daily lives via hand-held touchscreens. This personal use and the importance of the touch interface motivate the main assertion of this thesis: Mobile touch interaction can be improved by enabling user interfaces to assess and take into account how the user performs these interactions. This thesis introduces the new term "behaviour-aware" to characterise such interfaces. These behaviour-aware interfaces aim to improve interaction by utilising behaviour data: Since users perform touch interactions for their main tasks anyway, inferring extra information from said touches may, for example, save users' time and reduce distraction, compared to explicitly asking them for this information (e.g. user identity, hand posture, further context). Behaviour-aware user interfaces may utilise this information in different ways, in particular to adapt to users and contexts. Important questions for this research thus concern understanding behaviour details and influences, modelling said behaviour, and inference and (re)action integrated into the user interface. In several studies covering both analyses of basic touch behaviour and a set of specific prototype applications, this thesis addresses these questions and explores three application areas and goals: 1) Enhancing input capabilities – by modelling users' individual touch targeting behaviour to correct future touches and increase touch accuracy. The research reveals challenges and opportunities of behaviour variability arising from factors including target location, size and shape, hand and finger, stylus use, mobility, and device size. The work further informs modelling and inference based on targeting data, and presents approaches for simulating touch targeting behaviour and detecting behaviour changes. 2) Facilitating privacy and security – by observing touch targeting and typing behaviour patterns to implicitly verify user identity or distinguish multiple users during use. The research shows and addresses mobile-specific challenges, in particular changing hand postures. It also reveals that touch targeting characteristics provide useful biometric value both in the lab as well as in everyday typing. Influences of common evaluation assumptions are assessed and discussed as well. 3) Increasing expressiveness – by enabling interfaces to pass on behaviour variability from input to output space, studied with a keyboard that dynamically alters the font based on current typing behaviour. Results show that with these fonts users can distinguish basic contexts as well as individuals. They also explicitly control font influences for personal communication with creative effects. This thesis further contributes concepts and implemented tools for collecting touch behaviour data, analysing and modelling touch behaviour, and creating behaviour-aware and adaptive mobile touch interfaces. Together, these contributions support researchers and developers in investigating and building such user interfaces. Overall, this research shows how variability in mobile touch behaviour can be addressed and exploited for the benefit of the users. The thesis further discusses opportunities for transfer and reuse of touch behaviour models and information across applications and devices, for example to address tradeoffs of privacy/security and usability. Finally, the work concludes by reflecting on the general role of behaviour-aware user interfaces, proposing to view them as a way of embedding expectations about user input into interactive artefacts. | en |
| dc.description.uri | https://edoc.ub.uni-muenchen.de/22728/ | en |
| dc.identifier.doi | 10.5282/edoc.22728 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/42252 | |
| dc.language.iso | en | |
| dc.publisher | Ludwig-Maximilians-Universität München, Fakultät für Mathematik, Informatik und Statistik | |
| dc.relation.ispartofseries | Dissertationen Ludwig-Maximilians-Universität München, Fakultät für Mathematik, Informatik und Statistik (Prof. F. Alt) | |
| dc.subject | Human-Computer Interaction | |
| dc.subject | Machine Learning | |
| dc.subject | Mobile Touch Devices | |
| dc.subject | User Studies | |
| dc.title | Behaviour-aware mobile touch interfaces | en |
| dc.type | Text/Dissertation | |
| gi.citation.publisherPlace | München |
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