arXiv subjects

Daniela Trevisan

Publications and source records attributed to Daniela Trevisan.

6 recordsLinked to original sources

arXiv2026

A Symbolic Machine Learning Approach for Cybersickness Potential-Cause Estimation

Virtual reality (VR) and head-mounted displays are constantly gaining popularity in various fields such as education, military, entertainment, and bio/medical informatics. Although such technologies provide a high sense of immersion, they can also trigger symptoms of discomfort. This condition is called cybersickness (CS) and is quite popular in recent publications in the virtual reality context. This work proposes a novel experimental analysis using symbolic machine learning that ranks potential causes for CS. We estimate the CS causes and rank them according to their impact on the classification capabilities of CS. The experiments are performed using two distinct virtual reality games. We were able to identify that acceleration triggered cybersickness more frequently in a race game in contrast to a flight game. Furthermore, participants less experienced with VR are more prone to feel discomfort and this variable has a greater impact in the race game in contrast to the flight game, where the acceleration is not controlled by the user.

cs.HC↗

arXiv2026

Identifying cybersickness causes in virtual reality games using symbolic machine learning algorithms

Virtual reality (VR) and head-mounted displays are constantly gaining popularity in various fields such as education, military, entertainment, and health. Although such technologies provide a high sense of immersion, they can also trigger symptoms of discomfort. This condition is called cybersickness (CS) and is quite popular in recent virtual reality publications. This work proposes a novel experimental analysis using symbolic machine learning to rank potential causes of CS in VR games. We estimate CS causes and rank them according to their impact using classical machine learning. Experiments are performed using two virtual reality games and 6 experimental protocols along with 37 valid samples from a total of 88 volunteers. Our results show that rotation and acceleration triggered cybersickness more frequently in a flight game in contrast to a race game. We could also observe that subjects that are less experienced with VR are more prone to feel discomfort. Former experience plays a more important role on the race game, as this game provides more liberty to the user in terms of controllers, more displacement alternatives and a more user-controlled acceleration. Furthermore, different causes that trigger discomfort arise based on short or long term VR exposures. We suggest strategies for mitigating CS for these two scenarios: short and long term exposure experiences and compare the two highlighted scenarios (race and flight).

cs.HC↗

arXiv2026

Using the gameplay and user data to predict and identify causes of cybersickness manifestation in virtual reality games

Virtual reality (VR) is an imminent trend in games, education, entertainment, military, and health applications, as the use of head-mounted displays is accessible to everyone. While VR provides immersive experiences, it still does not offer an entirely perfect situation, mainly due to cybersickness (CS) issues. In this work, we propose a novel approach for predicting upcoming CS symptoms. Our solution is able to suggest whether the user of VR is entering into an illness situation. We adopted random forest classifiers and validated our solution using 16 different machine-learning techniques, which presented the best results. For training purposes, we built our own dataset through a CS profile questionnaire that we also propose in the present work. The questionnaire is focused on registering and identifying the user's susceptibility to CS, considering their historical conditions and also their response to the immersive environment developed by us. In this method, 86 individuals are selected and the developed questionnaire was put to them on different days, and the answers are compiled as dataset. Our proposal also identifying attributes responsible (causes and individual's parameters) for the observed stressful and uncomfortable situations.

cs.HC↗

arXiv2022

A guideline proposal for minimizing cybersickness in VR-based serious games and applications

Head-mounted displays (HMDs) are popular immersive tools in general, not limited to entertainment but also for education, military, and serious games for health. While these displays have strong popularity, they still have user experience issues, triggering possible symptoms of discomfort to users. This condition is known as cybersickness (CS) and is one of the most popular research topics tied to virtual reality (VR) issues. We first present the main strategies focused on minimizing cybersickness problems in virtual reality. Following this, we propose a guideline framework based on CS causes such as locomotion, acceleration, the field of view, depth of field, degree of freedom, exposition use time, latency-lag, static rest frame, and camera rotation. Additionally, serious games applications and broader categories of games can also adopt it. Additionally, we categorized the imminent challenges for CS minimization into four different items. Conclusively, this work contributes as a consulting reference to enable VR developers and designers to optimize their VR users' experience and VR serious games.

cs.HC↗

arXiv2020

Automatic Recommendation of Strategies for Minimizing Discomfort in Virtual Environments

Virtual reality (VR) is an imminent trend in games, education, entertainment, military, and health applications, as the use of head-mounted displays is becoming accessible to the mass market. Virtual reality provides immersive experiences but still does not offer an entirely perfect situation, mainly due to Cybersickness (CS) issues. In this work, we first present a detailed review about possible causes of CS. Following, we propose a novel CS prediction solution. Our system is able to suggest if the user may be entering in the next moments of the application into an illness situation. We use Random Forest classifiers, based on a dataset we have produced. The CSPQ (Cybersickness Profile Questionnaire) is also proposed, which is used to identify the player's susceptibility to CS and the dataset construction. In addition, we designed two immersive environments for empirical studies where participants are asked to complete the questionnaire and describe (orally) the degree of discomfort during their gaming experience. Our data was achieved through 84 individuals on different days, using VR devices. Our proposal also allows us to identify which are the most frequent attributes (causes) in the observed discomfort situations.

cs.HC↗

arXiv2016

Minimizing cyber sickness in head mounted display systems: design guidelines and applications

We are experiencing an upcoming trend of using head mounted display systems in games and serious games, which is likely to become an established practice in the near future. While these systems provide highly immersive experiences, many users have been reporting discomfort symptoms, such as nausea, sickness, and headaches, among others. When using VR for health applications, this is more critical, since the discomfort may interfere a lot in treatments. In this work we discuss possible causes of these issues, and present possible solutions as design guidelines that may mitigate them. In this context, we go deeper within a dynamic focus solution to reduce discomfort in immersive virtual environments, when using first-person navigation. This solution applies an heuristic model of visual attention that works in real time. This work also discusses a case study (as a first-person spatial shooter demo) that applies this solution and the proposed design guidelines.

cs.HC↗