Modern smartphones are built with capacitive-sensing touchscreens, which can detect anything that is conductive or has a dielectric differential with air. The human finger is an example of such a dielectric, and works wonderfully with such touchscreens. However, touch interactions are disrupted by raindrops, water smear, and wet fingers because capacitive touchscreens cannot distinguish finger touches from other conductive materials. When users' screens get wet, the screen's usability is significantly reduced. RainCheck addresses this hazard by filtering out potential touch points caused by water to differentiate fingertips from raindrops and water smear, adapting in real-time to restore successful interaction to the user. Specifically, RainCheck uses the low-level raw sensor data from touchscreen drivers and employs precise selection techniques to resolve water-fingertip ambiguity. Our study shows that RainCheck improves gesture accuracy by 75.7%, touch accuracy by 47.9%, and target selection time by 80.0%, making it a successful remedy to interference caused by rain and other water.

We present FlickBoard, which combines a touchpad and a keyboard into the same interaction area to reduce hand movement between a separate keyboard and touchpad. Our main contribution is automatic mode switching between typing and pointing, and the first system capable of combining a trackpad and a keyboard into an single interaction area without the need for external switches. We developed a prototype by embedding a 58x20 capacitive sensing grid into a soft keyboard cover, and used machine learning to distinguish between moving a cursor (touchpad mode) and entering text (keyboard mode). We conducted experimental studies that show automatic mode switching classification accuracies of 98% are achievable with our technology. Finally, our prototype has a thin profile and can be placed over existing keyboards.

Smart glasses, such as Google Glass, provide always-available displays not offered by console and mobile gaming devices, and could potentially offer a pervasive gaming experience. However, research on input for games on smart glasses has been constrained by the available sensors to date. To help inform design directions, this paper explores user-defined game input for smart glasses beyond the capabilities of current sensors, and focuses on the interaction in public settings. We conducted a user-defined input study with 24 participants, each performing 17 common game control tasks using 3 classes of interaction and 2 form factors of smart glasses, for a total of 2448 trials. Results show that users significantly preferred non-touch and non-handheld interaction over using handheld input devices, such as in-air gestures. Also, for touch input without handheld devices, users preferred interacting with their palms over wearable devices (51% vs 20%). In addition, users preferred interactions that are less noticeable due to concerns with social acceptance, and preferred in-air gestures in front of the torso rather than in front of the face (63% vs 37%).

We present TouchSense, which provides additional touchscreen input vocabulary by distinguishing the areas of users' finger pads contacting the touchscreen. It requires minimal touch input area and minimal movement, making it especially ideal for wearable devices such as smart watches and smart glasses. For example, users of a calculator application on a smart watch could tap normally to enter numbers, and tap with the right side of their fingers to enter the operators (e.g. , -, =). Results from two human-factor studies showed that users could tap a touchscreen with five or more distinct areas of their finger pads. Also, they were able to tap with more distinct areas closer to their fingertips. We developed a TouchSense smart watch prototype using inertial measurement sensors, and developed two example applications: a calculator and a text editor. We also collected user feedback via an explorative study.

Smart Glasses offer the opportunity to use head mounted sensors, such as gyroscope and accelerometers, to enable new types of game interaction. To better understand game play experience on Smart Glasses, we recruited 24 participants to play four current games on Google Glass that uses different interaction methods, including gyroscope, voice, touchpad, and in-air gesture. Study results showed that participants were concerned with comfort and social acceptance. Also, their favorite input method was gyroscope, and their favorite game type was First-Person Shooter (FPS) game. Hence, we implemented a FPS game on Google Glass using gyroscope for changing the viewport, and divide FPS controls into four categories: (a)Viewport Control, (b)Aim Control, (c)Fire Control, (d) Move Control. We implemented multiple control method in each category to evaluate and explore glass game control design.