Humans communicate by writing, often taking notes that assist thinking. With the growing popularity of collaborative Virtual Reality (VR) applications, it is imperative that we better understand aspects that affect writing in these virtual experiences. On-air writing in VR is a popular writing paradigm due to its simplicity in implementation without any explicit needs for specialized hardware. A host of factors can affect the efficacy of this writing paradigm and in this work, we delved into investigating the same. Along these lines, we investigated the effects of a combination of factors on users’ on-air writing performance, aiming to understand the circumstances under which users can both effectively and efficiently write in VR. We were interested in studying the effects of the following factors: 1) input modality: brush vs. near-field raycast vs. pointing gesture, 2) inking trigger method: haptic feedback vs. button based trigger, and 3) canvas geometry: plane vs. hemisphere. To evaluate the writing performance, we conducted an empirical evaluation with thirty participants, requiring them to write the words we indicated under different combinations of these factors. Dependent measures including the writing speed, accuracy rates, perceived workloads, etc. were analyzed. Results revealed that the brush based input modality produced the best results in writing performance, that haptic feedback was not always effective over button based triggering, and that there are trade-offs associated with the different types of canvas geometries used. This work attempts at laying a foundation for future investigations that seek to understand and further improve the on-air writing experience in immersive virtual environments.

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Cybersickness (CS) is one of the challenges that has hindered the widespread adoption of Virtual Reality and its applications. Consequently, a number of studies have focused on extensively understanding and reducing CS. Inspired by previous work that has sought to reduce CS using foveated rendering and Field of View (FOV) restrictions, we investigated how the presence and size of a static central window in peripheral FOV blurring affects CS. To facilitate this peripheral FOV blur, we applied a Gaussian blur effect in the display peripheral region, provisioning a full-resolution central window. Thirty participants took part in a three-session, within-subjects experiment, performing search and spatial updating tasks in a first-person, slow-walking, maze-traveling scenario. Two different central window sizes (small and large) were tested against a baseline condition that didn’t feature display peripheral blurring. Results revealed that the baseline condition produced higher levels of CS than both conditions with a central window. While there were no significant differences between the small and large windows, we observed interaction effects suggesting an influence of window size on “adaptation to CS.” When the central window is small, adaptation to CS seems to take more time but is more pronounced. The interventions had no effect on spatial updating and presence, but were detectable when the blurred area was larger (small central window). Lower sickness levels observed in both window conditions supports the use of peripheral FOV blurring to reduce CS, reducing our dependence on eye tracking. This being said, researchers must strive to find the right balance between window size and detectability to ensure seamless virtual experiences.

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