Cybersickness Analysis Using Symbolic Machine Learning Algorithms

• Thiago Porcino Universidade Federal Fluminense
• Daniela Trevisan Universidade Federal Fluminense
• Esteban Clua Universidade Federal Fluminense

DOI: https://doi.org/10.5753/svr_estendido.2021.17647

Resumo

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 VR 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 on the classical machine learning classification task. Experiments are performed using two VR games and 6 experimental protocols along with 37 valid samples from a total of 88 volunteers.

Palavras-chave: virtual reality, head-mounted displays, cybersickness, games, machine learning

Referências

Andras Kemeny, Jean-Rémy Chardonnet, and Florent Colombet. 2020. Getting Rid of Cybersickness: In Virtual Reality, Augmented Reality, and Simulators. Springer Nature.

Thiago Porcino. [n.d.]. Cybersickness Dataset. https://github.com/tmp1986/UFFCSData. Accessed: 2021-04-03.

Thiago Porcino, Flavia Bernardini, Erick O. Rodrigues, Alexandre Silva, Esteban Clua, and Daniela Trevisan. 2021. A symbolic machine learning approach for cybersickness potential-cause estimation. In International Conference on Entertainment Computing. Springer [Accepted].

Thiago Porcino, Erick O. Rodrigues, Flavia Bernardini, Daniela Trevisan, and Esteban Clua. 2021. A cybersickness review: causes, strategies, and classification methods. SBC Journal on Interactive Systems [Submitted] (2021).

Thiago Porcino, Erick O. Rodrigues, Flavia Bernardini, Daniela Trevisan, and Esteban Clua. 2021. Identifying Cybersickness Causes in Virtual Reality Games Using Symbolic Machine Learning Algorithms. Entertainment Computing [Submitted] (2021).

Thiago Porcino, Erick O. Rodrigues, Alexandre Silva, Esteban Clua, and Daniela Trevisan. 2020. Using the gameplay and user data to predict and identify causes of cybersickness manifestation in virtual reality games. In 2020 IEEE 8th International Conference on Serious Games and Applications for Health (SeGAH). IEEE, 1–8.

Thiago Porcino, Daniela Trevisan, and Esteban Clua. 2020. Minimizing cybersickness in head-mounted display systems: causes and strategies review. In 2020 22nd Symposium on Virtual and Augmented Reality (SVR). IEEE, 154–163.

Thiago Porcino, Daniela Trevisan, and Esteban Clua. 2021. An experimental methodology to capture user and gameplay data tied to cybersickness. In Proceedings of the 1st XR in Games Workshop. SBC.

Thiago M Porcino, Esteban Clua, Daniela Trevisan, Cristina N. Vasconcelos, and Luis Valente. 2017. Minimizing cyber sickness in head mounted display systems: design guidelines and applications. In Serious Games and Applications for Health (SeGAH), 2017 IEEE 5th International Conference on. IEEE, 1–6.