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Title: Improving one-handed interaction with touchscreen smartphones
Author: Seipp, Karsten
ISNI:       0000 0004 5360 8597
Awarding Body: Goldsmiths College (University of London)
Current Institution: Goldsmiths College (University of London)
Date of Award: 2015
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One-handed operation of touchscreen smartphones presents challenges such as hard-to-reach targets and the thumb occluding the interface. There are two main approaches to address these challenges: Modification of the graphical user interface (GUI) and extension of the device's input modalities using its sensors. Previous work has presented techniques addressing a specific problem in isolation, but has failed to provide one solution which tackles all main challenges of thumb interaction together. This thesis examines whether this can be done. To establish the background, the thesis finds that users prefer convenience over efficiency and confirms that they predominantly use one hand. To detect mode of operation, the thesis presents an approach to classify a user's finger with a high degree of accuracy using a single touch. Following the first research avenue, the thesis presents a thumb-optimised GUI that increases usability and efficiency of one-handed website operation. Following the second avenue of research, the thesis presents a novel one-handed input technique for smartphones, using a set of three off-screen gestures. Both approaches address the most common problems of one-handed smartphone operation via the thumb largely successfully, but fail to completely solve the problem of interface occlusion. The thesis adds to the literature in the field of visual perception, input classification, GUI optimisation, and input techniques. Readers learn that visual search strategies of the desktop world may also apply to the mobile world and that eye gaze position may have a greater impact on target acquisition time than Fitts's law. The one-touch finger classification technique provides an additional layer of context and new opportunities for improving the human-machine dialogue. The thumb-optimised GUI presents practitioners with a potential blueprint for translating classical WIMP UI elements into thumb-friendly touch interfaces while the novel input technique provides a new layer of complexity for off-screen interaction.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral