While many modern gaming environments provide haptic feedback, laptop keyboard gaming remains largely without rich tactile interaction, despite a rapidly growing audience. In this paper, we propose the HapPalm interface, a novel laptop interface concept that delivers rich spatio-temporal vibrotactile feedback through the palmrest area, allowing players to feel game events with their palms. Our prototype uses dual 4×6 linear resonant actuator arrays. To render various game events with the HapPalm interface, our first study aims to create a haptic pattern dataset. Iterative design workshops identified 11 haptic pattern templates, of which our second study validated that they convincingly convey diverse game events. Our final study embedded these patterns into a custom game, showing that spatial haptics significantly improved fun, immersion, realism, and presence compared to non-spatial or no-haptic conditions. HapPalm interface demonstrates that palmrest-based haptics can enrich keyboard-only laptop gaming, providing an expressive and immersive tactile channel for future laptop interfaces.

Interacting with desktop GUIs often requires users to perform concurrent operations, such as scrolling through a document while selecting text or switching applications during file transfer. Although wheel mice support these tasks with a scroll wheel, touchpads lack this feature. In this paper, we introduce ThumbSwipe, an input technique for touchpads that enables concurrent operations by leveraging the thumb’s dexterity. We conducted two experiments to evaluate its performance for continuous and discrete input tasks. The first experiment demonstrated that ThumbSwipe achieves input throughputs comparable to those of cursor operations using the index or middle finger on a touchpad. The second experiment confirmed ThumbSwipe’s efficiency for discrete input tasks. Additionally, a third experiment assessed ThumbSwipe’s advantages in typical unimanual concurrent operation scenarios, showing improvements in touchpad user experience regarding task completion time, task load, and subjective usability ratings.

Multi-touch mice have been proposed to integrate the rich input vocabulary of multi-touch gestures into traditional computer mice. However, incorporating multi-finger gestures into a mouse introduces a design conflict: Mice are optimized for low friction to support smooth cursor navigation, whereas touch gestures require high friction for stability. In this paper, we present AutoPark—the concept of a multi-touch mouse that dynamically adjusts its friction based on user intent. AutoPark mouse operates in a low-friction mode for cursor movement and shifts to a high-friction state for multi-touch interactions. Our first user study measured the shear forces during touch gestures, confirming that conventional friction levels of mousepads are insufficient to maintain gesture input stability on a mouse. We developed an AutoPark prototype and conducted controlled experiments, comparing it with both conventional low-friction and gesture-favored high-friction setups. The results demonstrate that AutoPark enhances gesture stability while maintaining comparable pointing performance in our study tasks, supporting a richer gesture input vocabulary within mouse-based GUI interactions.

We introduce Pro-Tact, a novel eyes-free pointing technique for interacting with out-of-view (OoV) VR menus. This technique combines rapid rough pointing using proprioception with fine-grain adjustments through tactile exploration, enabling menu interaction without visual attention. Our user study demonstrated that Pro-Tact allows users to select menu items accurately (95% accuracy for 54 items) in an eyes-free manner, with reduced fatigue and sickness compared to eyes-engaged interaction. Additionally, we observed that participants voluntarily interacted with OoV menus eyes-free when Pro-Tact’s tactile feedback was provided in practical VR application usage contexts. This research contributes by introducing the novel interaction technique, Pro-Tact, and quantitatively evaluating its benefits in terms of performance, user experience, and user preference in OoV menu interactions.

Children acquire an understanding of the world by asking “why” and “how” questions. Conversational agents (CAs) like smart speakers or voice assistants can be promising respondents to children’s questions as they are more readily available than parents or teachers. However, CAs’ answers to “why” and “how” questions are not designed for children, as they can be difficult to understand and provide little interactivity to engage the child. In this work, we propose design guidelines for creating interactive dialogues that promote children’s engagement and help them understand explanations. Applying these guidelines, we propose DAPIE, a system that answers children’s questions through interactive dialogue by employing an AI-based pipeline that automatically transforms existing long-form answers from online sources into such dialogues. A user study (N=16) showed that, with DAPIE, children performed better in an immediate understanding assessment while also reporting higher enjoyment than when explanations were presented sentence-by-sentence.