A Deep Motion Sickness Predictor Induced by Visual Stimuli in Virtual Reality

VR.net: A Real-world Dataset for Virtual Reality Motion Sickness Research

Researchers have used machine learning approaches to identify motion sickness in VR experience. These approaches would certainly benefit from an accurately labeled, real-world, diverse dataset that enables the development of generalizable ML models. We introduce 'VR.net', a dataset comprising 165-hour gameplay videos from 100 real-world games spanning ten diverse genres, evaluated by 500 participants. VR.net accurately assigns 24 motion sickness-related labels for each video frame, such as camera/object movement, depth of field, and motion flow. Building such a dataset is challenging since manual labeling would require an infeasible amount of time. Instead, we implement a tool to automatically and precisely extract ground truth data from 3D engines' rendering pipelines without accessing VR games' source code. We illustrate the utility of VR.net through several applications, such as risk factor detection and sickness level prediction. We believe that the scale, accuracy, and diversity of VR.net can offer unparalleled opportunities for VR motion sickness research and beyond.We also provide access to our data collection tool, enabling researchers to contribute to the expansion of VR.net.

CyPVICS: A framework to prevent or minimise cybersickness in immersive virtual clinical simulation

Cybersickness is a global issue affecting users of immersive virtual reality. However, there is no agreement on the exact cause of cybersickness. Taking into consideration how it can differ greatly from one person to another, it makes it even more difficult to determine the exact cause or find a solution. Because cybersickness excludes so many prospective users, including healthcare professionals, from using immersive virtual reality as a learning tool, this research sought to find solutions in existing literature and construct a framework that can be used to prevent or minimise cybersickness during immersive virtual clinical simulation (CyPVICS). The Bestfit Framework by Carrol and authors were used to construct the CyPVICS framework. The process started by conducting two separate literature searchers using the BeHEMoTh (for models, theories, and frameworks) and SPIDER (for primary research articles) search techniques. Once the literature searches were completed the models, theories and framework were used to construct a priori framework. The models' theories and frameworks were analysed to determine aspects relevant to causes, reducing, eliminating, and detecting cybersickness. The priori framework was expanded by, first coding the findings of the primary research study into the existing aspects of the priori framework. Once coded the aspects that could not be coded were added in the relevant category, for example causes. After reviewing 1567 abstracts and titles as part of the BeHEMoTh search string,19 full text articles, a total of 15 papers containing models, theories, and frameworks, were used to construct the initial CyPVICS framework. Once the initial CyPVICS was created, a total 904 primary research studies (SPIDER) were evaluated, based on their titles and abstracts, of which 100 were reviewed in full text. In total, 67 articles were accepted and coded to expand the initial CyPVICS framework. This paper presents the CyPVICS framework for use, not only in health professions' education, but also in other disciplines, since the incorporated models, theories, frameworks, and primary research studies were not specific to virtual clinical simulation.

An old approach to a novel problem: effect of combined balance therapy on virtual reality induced motion sickness: a randomized, placebo controlled, double-blinded study

BACKGROUND

The objective of this study was to investigate the impact of a rehabilitation program aimed at addressing vestibular and proprioceptive deficits, which are believed to underlie the pathophysiology of motion sickness.

METHODS

A total of 121 medical students with motion sickness participated in this study and were randomly divided into intervention (n = 60) and placebo control (n = 61) groups. The intervention group underwent combined balance, proprioception, and vestibular training three times a week for 4 weeks, while the control group received placebo training. The study assessed various measurements, including the Virtual reality sickness questionnaire (VRSQ), tolerance duration, enjoyment level measured by VAS, stability levels using Biodex, and balance with the Flamingo balance test (FBT). All measurements were conducted both at baseline and 4 weeks later.

RESULTS

There was no significant difference in pre-test scores between the intervention and control groups, suggesting a similar baseline in both groups (p > 0.05). The results showed a significant improvement in VRSQ, tolerance duration, VAS, Biodex, and FBT scores in the intervention group (p < 0.05). While, the control group showed a significant increase only in VAS scores after 4 weeks of training (p < 0.05). A statistically significant improvement was found between the groups for VRSQ (p < 0.001), tolerance duration (p < 0.001), VAS (p < 0.001), Biodex (p = 0.015), and FBT scores (p < 0.05), in favor of the intervention group.

CONCLUSIONS

A combined balance training program for motion sickness proves to be effective in reducing motion sickness symptoms, enhancing user enjoyment, and extending the usage duration of virtual reality devices while improving balance and stability. In contrast, placebo training did not alter motion sickness levels. These findings offer valuable insights for expanding the usage of virtual reality, making it accessible to a broader population.

Progressive Contextual Aggregation Empowered by Pixel-wise Confidence Scoring for Image Inpainting

Image inpainting methods leverage the similarity of adjacent pixels to create alternative content. However, as the invisible region becomes larger, the pixels completed in the deeper hole are difficult to infer from the surrounding pixel signal, which is more prone to visual artifacts. To help fill this void, we adopt an alternative progressive hole-filling scheme that hierarchically fills the corrupted region in the feature and image spaces. This technique allows us to utilize reliable contextual information of the surrounding pixels, even for large hole samples, and then gradually complete the details as the resolution increases. For a more realistic representation of the completed region, we devise a pixel-wise dense detector. By distinguishing each pixel as whether it is a masked region or not, and passing the gradient to all resolutions, the generator further enhances the potential quality of the compositing. Furthermore, the completed images at different resolutions are then merged using a proposed structure transfer module (STM) that incorporates fine-grained local and coarse-grained global interactions. In this new mechanism, each completed image at the different resolutions attends its closest composition at fine granularity adjacent image and thus can capture the global continuity by interacting both short- and long-range dependencies. By comparing our solutions qualitatively and quantitatively with state-of-the-art methods, we conclude that our model exhibits a significantly improved visual quality, even in the case of large holes.

Effect of spatial distortions in head-mounted displays on visually induced motion sickness

Incomplete optical distortion correction in VR HMDs leads to spatial dynamic distortion, which is a potential cause of VIMS. A perception experiment is designed for the investigation with three spatial distortion levels, with the subjective SSQ, five-scale VIMS level rating, and objective postural instability adopted as the evaluation metrics. The results show that the factor of spatial distortion level has a significant effect on all metrics increments (p<0.05). As the spatial distortion level drops off, the increments of VIMS symptoms decrease. The study highlights the importance of perfect spatial distortion correction in VR HMDs for eliminating the potential VIMS aggravation effect.

Beyond Perceptual Thresholds and Personal Preference: Towards Novel Research Questions and Methodologies of Quality of Experience Studies on Light Field Visualization

With the upcoming emergence of the IEEE P3333.1.4 standard, the first ever standardization document on the subjective quality assessment of light field visualization, we are approaching a major milestone of light field Quality of Experience (QoE). The research efforts leading up to this point have answered the fundamental questions regarding perceptual thresholds and personal preference, and best practices regarding research methodologies have been formed. However, in order to introduce successful and efficient light field systems and services, research questions beyond perceptual thresholds and personal preference must be addressed, along with the associated methodologies. In this paper, we propose a comprehensive set of novel research questions and methodologies regarding light field QoE. Our work also provides a detailed discussion of related factors, particularly those that extend to test participants and thus may affect the results of subjective studies.

The Influence of Walking Height and Width on the Gait

Walking stability is an important factor that is related to working accidents at height. The understanding of the relationship between walking stability and walking conditions remains an unmet need. Therefore, this study aimed to investigate the effect of path height, width, and asymmetric conditions on the pressure and time information of the foot-ground interaction during walking. 12 subjects were required to walk at two height, three width, and asymmetric conditions. Plantar pressures during walking were measured with the F-scan insole sensors. The total pressures were normalized with body weight, and the temporal parameters were normalized with stance time. When the walking height increased, the plantar pressure at the "heel strike" phase did not change significantly, while that at "heel rise" and "toe off" phases significantly increased, and the "heel rise" occurred earlier, indicating a greater foot-ground interaction at the forefoot part of the sole. As the path width increased from 0.6 m to 1.2 m, the foot-ground interaction as well as the asymmetric effect approached to that of overground walking. The findings could help improve the risk assessment and footwear design.