Alphanumeric text entry is a challenge for Virtual Reality (VR) applications. VR enables new capabilities, impossible in the real world, such as an unobstructed view of the keyboard, without occlusion by the user's physical hands. Several hand representations have been proposed for typing in VR on standard physical keyboards. However, to date, these hand representations have not been compared regarding their performance and effects on presence for VR text entry. Our work addresses this gap by comparing existing hand representations with minimalistic fingertip visualization. We study the effects of four hand representations (no hand representation, inverse kinematic model, fingertip visualization using spheres and video inlay) on typing in VR using a standard physical keyboard with 24 participants. We found that the fingertip visualization and video inlay both resulted in statistically significant lower text entry error rates compared to no hand or inverse kinematic model representations. We found no statistical differences in text entry speed.
 Symbolic input, including text and numeric input, can be an important user task in applications of virtual environments (VEs). However, very little research has been performed to support this task in immersive VEs. This paper presents the results of an empirical evaluation of four text input techniques for immersive VEs. The techniques include the Pinch Keyboard (a typing emulation technique using pinch gloves), a one-hand chord keyboard, a soft keyboard using a pen & tablet, and speech. The experiment measured both task performance and usability characteristics of the four techniques. Results indicate that the speech technique is the fastest, while the pen & tablet keyboard produces the fewest errors. However, no single technique exhibited high levels of performance, usability and user satisfaction. Belt is a novel unobtrusive input device for wearable displays that incorporates a touch surface encircling the user's hip. The wide input space is leveraged for a horizontal spatial mapping of quickly accessible information and applications. We discuss social implications and interaction capabilities for unobtrusive touch input and present our hardware implementation and a set of applications that benefit from the quick access time. In a qualitative user study with 14 participants we found out that for short interactions (2-4 seconds), most of the surface area is considered as appropriate input space, while for longer interactions (up to 10 seconds), the front areas above the trouser pockets are preferred. 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 ). Text input is an important part of the data annotation process, where text is used to capture ideas and comments. For text entry in immersive virtual environments, for which standard keyboards usually do not work, various approaches have been proposed. While these solutions have mostly proven effective, there still remain certain shortcomings making further investigations worthwhile. Motivated by recent research, we propose the speech-based multimodal text entry system SWIFTER, which strives for simplicity while maintaining good performance. In an initial user study, we compared our approach to smartphone-based text entry within a CAVE-like virtual environment. Results indicate that SWIFTER reaches an average input rate of 23.6 words per minute and is positively received by users in terms of user experience. 