Three state virtual keyboards which differentiate contact events between released, touched, and pressed states have the potential to improve overall typing experience and reduce the gap between virtual keyboards and physical keyboards. Incorporating force sensitivity, three-state virtual keyboards can utilize a force threshold to better classify a contact event. However, our limited knowledge of how force plays a role during typing on virtual keyboards limits further progress. Through a series of studies we observe that using a uniform threshold is not an optimal approach. Furthermore, the force being applied while typing varies significantly across the keys and among participants. As such, we propose three different approaches to further improve the uniform threshold. We show that a carefully selected non-uniform threshold function could be sufficient in delineating typing events on a three-state keyboard. Finally, we conclude our work with lessons learned, suggestion for future improvements, and comparisons with current methods available.

Supporting eyes-free interaction, mobility and encumbrance, while providing a broad set of commands on a smartwatch display is a difficult, yet important, task. Bezel-to-bezel (B2B) gestures are valuable for rapid command invocation during eyes-free operation, however we lack knowledge regarding B2B interactions on circular devices during common usage scenarios. We aim to improve our understanding of the dynamics of B2B interactions in these scenarios by conducting two studies and a third analysis: First, we explore the performance of B2B in a seated position; second, we explore the effect of mobility and encumbrance on the B2B interaction; finally, we improve on the B2B accuracies by calculating features and utilizing machine learning. With the limited interaction capabilities on smartwatches and the importance of the scenario of use, we conclude with applications and design guidelines for improved utilization of B2B that enables effective smartwatch control while in common, mobile and eyes-free scenarios.

We present BezelGlide, a novel suite of bezel interaction techniques, designed to minimize screen occlusion and ‘fat finger’ effects, when interacting with common graphs on smartwatches. To explore the design of BezelGlide, we conducted two user studies. First, we quantified the amount of screen occlusion experienced when interacting with the smartwatch bezel. Next, we designed two techniques that involve gliding the finger along the smartwatch bezel for graph interaction. Full BezelGlide (FBG) and Partial BezelGlide (PBG), use the full or a portion of the bezel, respectively, to reduce screen occlusion while scanning a line chart for data. In the common value detection task, we find that PBG outperforms FBG and Shift, a touchscreen occlusion-free technique, both quantitatively and subjectively, also while mobile. We finally illustrate the generzability potential of PBG to interact with common graph types making it a valuable interaction technique for smartwatch users.

Fingertip computing has seen increased interest through miniaturized smart-rings for augmenting digital peripherals. One key advantages of such always-available input devices is the non-necessity to hold a device for interaction, as it remains affixed to a finger for access when needed. Such a wearable device makes it possible to interaction with content even when the hand is encumbered, by grasping or holding objects. Our investigation aims at understanding the properties of this fundamental smart-ring advantage. We designed a smart-ring prototype, ARO (in-Air, on-Ring, on-Object interaction), which facilitates input while grasping objects. To better identify interaction possibilities, we present the results of an elicitation study through which we grouped various forms of micro-gestures possible with ARO while holding objects under different grasp requirements. We then explored the ability for users to perform different navigation tasks (i.e. zooming and panning) using the smart-ring with encumbered hands. In our studies, users were most efficient when using either In-air or On-ring interactions, in comparisons to gestures detected On-object. Furthermore, In-air was the most preferred by our participants. Based on our findings, we conclude with recommendations for the design of future smart-rings and fingertip devices at large, to allow efficient interaction while hands are encumbered.

Multiple embedded sensors enable smartwatch apps to amass large amounts of interrelated time-series data simultaneously, such as heart rate, oxygen levels or steps walked. Visualizing multiple interlinked datasets is possible on smartphones but remains challenging on small smartwatch displays. We propose a new technique, the Space-Filling Line Graph (SF-LG), that preserves the key visual properties of time-series graphs while making available space on the display to augment such graphs with additional information. Results from our first study (N=30) suggest that, while SF-LG makes available additional space on the small display, it also enables effective (i.e. quick and accurate) comprehension of key line graph tasks. We next implement a greedy algorithm to embed auxiliary information in the most suitable regions on the display. In a second study (N=27), we find that participants are efficient at locating and linking interrelated content using SF-LG in comparison to two baselines approaches. We conclude with guidelines for smartwatch space maximization for visual displays.