Thesis (M.S. in Engineering Science)--Naval Postgraduate School, December 2003. / Thesis advisor(s): David C. Jenn, D. Curtis Schleher. Includes bibliographical references (p. 95-96). Also available online.

Gestural interfaces are user interfaces controlled by users’ gestures, such as taps, flicks and swipes, without the aid of a conventional pointing device, such as a mouse or a touchpad. The development of touch screen technology has resulted in an increasing number of inventive gestural interfaces. However, recent studies have shown that well-established interaction design principles are generally not followed, or even violated by gestural interfaces. As a result, severe usability issues start to surface: the absence of signifiers for operative gestures, the weakening of visual feedback, the inability to discover every possible actions in the interface, as well as the lack of consistency, all of which are undermining the user experience of these interfaces thus need to be addressed. Further analysis of existing gestural interfaces suggests that the sole dependence on gestural input makes interface design unnecessarily complicated, which in turn makes it challenging to establish a standard. Therefore, an approach to supplement gestures with user attention is proposed. By incorporating eye gaze as a new input modality into gestural interactions, this novel type of interfaces can interact with users in a more intelligent and natural way by collecting input that reflects the users’ interest and intention, which makes the interfaces attentive. To demonstrate the viability of this approach, a system was built to utilise eye-tracking techniques to detect visual attention of users and deliver input data to the applications on a mobile device. A paradigm for attentive gestural interfaces was introduced to provide insights into how such interfaces can be designed. A software prototype with attentive gestural interfaces was created according to the paradigm. It has been found in an experiment that the new type of interfaces helped users learn a new application faster, and modestly increased their accuracy when completing tasks. This provided evidence that attentive gestural interfaces can improve usability in terms of learnability and effectiveness This study is focused on interfaces of mobile devices whose major input mechanism is a touch screen, which are commonly seen and widely adopted. Despite the fact that eye-tracking capability is not generally available on these devices, this study demonstrates that it has great potential to facilitate interfaces that are both gestural and attentive, and it can enable new possibilities for future user interfaces. / published_or_final_version / Computer Science / Master / Master of Philosophy

abstract / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / Community Medicine / Master / Master of Philosophy

published_or_final_version / Architecture / Master / Master of Philosophy

The proliferation of collaborative computer applications in the past decade has resulted in a corresponding increase in the need for multi-user interfaces. The current research seeks to contribute to the design of a user-centered multi-user interface for a group ranking task. User requirements were identified by observing groups perform the ranking task in a non-computer environment. A design was proposed based on these identified requirements. The user-centered design was compared to preliminary designs based on the intuitions of programmers. The conclusions indicate that an analysis of observations in the non-computer environment does yield insight beyond the initial intuition of programmers. A prototype based on the user-centered design was implemented. Informal user evaluation was performed by observing users working with the prototype and obtaining verbal feedback both on the ease of use of the system and on possible improvements. The informal user evaluation provides evidence for the usefulness of user-centered design. The evaluation also suggests that not all features identified were found useful and not all features necessary were identified.

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