Cybersickness Analysis Using Symbolic Machine Learning Algorithms
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, Machine learning, Cybersickness, Games
Referências
Ahir, K., Govani, K., Gajera, R., and Shah, M. (2020). Application on virtual reality for enhanced education learning, military training and sports. Augmented Human Research, 5(1):7.
Bernadini, F. C. (2006). Combinação de classificadores simbólicos utilizando medidas de regras de conhecimento e algoritmos genéticos. Technical report, Universidade de São Paulo.
Bouyer, G., Chellali, A., and Lécuyer, A. (2017). Inducing self-motion sensations in driving simulators using force-feedback and haptic motion. In Virtual Reality (VR), 2017 IEEE, pages 84–90. IEEE.
Budhiraja, P., Miller, M. R., Modi, A. K., and Forsyth, D. (2017). Rotation blurring: Use of artificial blurring to reduce cybersickness in virtual reality first person shooters. arXiv preprint arXiv:1710.02599.
Calvelo, M., Piñeiro, Á., and Garcia-Fandino, R. (2020). An immersive journey to the molecular structure of sars-cov-2: Virtual reality in covid-19. Computational and Structural Biotechnology Journal.
Carrión, M., Santorum, M., Benavides, J., Aguilar, J., and Ortiz, Y. (2019). Developing a virtual reality serious game to recreational therapy using iplus methodology. In 2019 International Conference on Virtual Reality and Visualization (ICVRV), pages 133– 137. IEEE.
Curry, C., Li, R., Peterson, N., and Stoffregen, T. A. (2020). Cybersickness in virtual reality head-mounted displays: Examining the influence of sex differences and vehicle control. International Journal of Human–Computer Interaction, pages 1–7.
Davis, S., Nesbitt, K., and Nalivaiko, E. (2014). A systematic review of cybersickness. In Proceedings of the 2014 Conference on Interactive Entertainment, pages 1–9. ACM.
Dennison, M. S. and D’Zmura, M. (2017). Cybersickness without the wobble: experimental results speak against postural instability theory. Applied ergonomics, 58:215–223.
Drucker, H., Burges, C. J., Kaufman, L., Smola, A. J., and Vapnik, V. (1997). Support vector regression machines. In Advances in neural information processing systems, pages 155–161.
Flach, P. (2012). Machine Learning: The Art and Science of Algorithms That Make Sense of Data. Cambridge.
Garcia-Agundez, A., Reuter, C., Becker, H., Konrad, R., Caserman, P., Miede, A., and Göbel, S. (2019). Development of a classifier to determine factors causing cybersickness in virtual reality environments. Games for health journal, 8(6):439–444.
Grassini, S. and Laumann, K. (2020). Are modern head-mounted displays sexist? a systematic review on gender differences in hmd-mediated virtual reality. Frontiers in Psychology, 11.
Graves, A., Mohamed, A.-r., and Hinton, G. (2013). Speech recognition with deep recurrent neural networks. In 2013 IEEE international conference on acoustics, speech and signal processing, pages 6645–6649. IEEE.
Jeong, D., Yoo, S., and Yun, J. (2019). Cybersickness analysis with EEG using deep learning algorithms. In 2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR), pages 827–835. IEEE.
Jin, W., Fan, J., Gromala, D., and Pasquier, P. (2018). Automatic prediction of cybersickness for virtual reality games. In 2018 IEEE Games, Entertainment, Media Conference (GEM), pages 1–9. IEEE.
Kemeny, A., Chardonnet, J.-R., and Colombet, F. (2020). Getting Rid of Cybersickness: In Virtual Reality, Augmented Reality, and Simulators. Springer Nature.
Kim, J., Kim, W., Oh, H., Lee, S., and Lee, S. (2019). A deep cybersickness predictor based on brain signal analysis for virtual reality contents. In Proceedings of the IEEE International Conference on Computer Vision, pages 10580–10589.
Kolasinski, E. M. (1995). Simulator sickness in virtual environments. Technical report, DTIC Document.
Kühnapfel, U., Cakmak, H. K., and Maaß, H. (2000). Endoscopic surgery training using virtual reality and deformable tissue simulation. Computers & graphics, 24(5):671– 682.
Lawrence, S., Giles, C. L., Tsoi, A. C., and Back, A. D. (1997). Face recognition: A convolutional neural-network approach. IEEE transactions on neural networks, 8(1):98– 113.
Liang, H.-N., Lu, F., Shi, Y., Nanjappan, V., and Papangelis, K. (2019). Evaluating the effects of collaboration and competition in navigation tasks and spatial knowledge acquisition within virtual reality environments. Future Generation Computer Systems, 95:855–866.
Maree, C. and Omlin, C. W. (2020). Towards responsible ai for financial transactions. In 2020 IEEE Symposium Series on Computational Intelligence (SSCI), pages 16–21. IEEE.
Melo, M., Vasconcelos-Raposo, J., and Bessa, M. (2018). Presence and cybersickness in immersive content: effects of content type, exposure time and gender. Computers & Graphics, 71:159–165.
Mousavi, M., Jen, Y. H., and Musa, S. N. B. (2013). A review on cybersickness and usability in virtual environments. In Advanced Engineering Forum, volume 10, pages 34–39. Trans Tech Publ.
Porcino, T. (2021). Cybersickness Dataset. https://github.com/tmp1986/UFFCSData. Accessed: 2021-04-03.
Porcino, T., Rodrigues, E. O., Bernardini, F., Trevisan, D., and Clua, E. (2021a). Identifying cybersickness causes in virtual reality games using symbolic machine learning algorithms. Entertainment Computing, page 100473.
Porcino, T., Rodrigues, E. O., Bernardini, F., Trevisan, D., and Clua, E. (2021b). A symbolic machine learning approach for cybersickness potential-cause estimation. In International Conference on Entertainment Computing, pages 115–126. Springer.
Porcino, T., Rodrigues, E. O., Silva, A., Clua, E., and Trevisan, D. (2020a). 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), pages 1–8. IEEE.
Porcino, T., Trevisan, D., and Clua, E. (2020b). Minimizing cybersickness in headmounted display systems: causes and strategies review. In 2020 22nd Symposium on Virtual and Augmented Reality (SVR), pages 154–163. IEEE.
Porcino, T., Trevisan, D., and Clua, E. (2021c). Cybersickness analysis using symbolic machine learning algorithms. In Anais Estendidos do XXIII Simpósio de Realidade Virtual e Aumentada, pages 3–4. SBC.
Porcino, T., Trevisan, D., and Clua, E. (2021d). A cybersickness review: causes, strategies, and classification methods. Journal on Interactive Systems, 12(1):269–282.
Porcino, T., Trevisan, D., and Clua, E. (2021e). An experimental methodology to capture user and gameplay data tied to cybersickness. In Proceedings of the 1st XR in Games Workshop. SBC.
Porcino, T. M., Clua, E., Trevisan, D., Vasconcelos, C. N., and Valente, L. (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, pages 1–6. IEEE.
Ramsey, A., Nichols, S., and Cobb, S. (1999). Virtual reality induced symptoms and effects (vrise) in four different virtual reality display conditions. In Proceedings of HCI International (the 8th International Conference on Human-Computer Interaction) on Human-Computer Interaction: Ergonomics and User Interfaces-Volume I-Volume I, pages 142–146. L. Erlbaum Associates Inc.
Rebenitsch, L. and Owen, C. (2016). Review on cybersickness in applications and visual displays. Virtual Reality, 20(2):101–125.
Rizzo, A., Parsons, T. D., Lange, B., Kenny, P., Buckwalter, J. G., Rothbaum, B., Difede, J., Frazier, J., Newman, B., Williams, J., et al. (2011). Virtual reality goes to war: A brief review of the future of military behavioral healthcare. Journal of clinical psychology in medical settings, 18(2):176–187.
Rodrigues, E., Conci, A., and Panos, L. (2018). Morphological classifiers. Pattern Recognition, 84:82–96.
Sak, H., Senior, A.W., and Beaufays, F. (2014). Long short-term memory recurrent neural network architectures for large scale acoustic modeling.
Statista, A. (2020). The statistics portal. Web site: [link].
Studios, B. G. (2015). The elder scrolls v: Skyrim. Bethesda Game Studios.
Van Waveren, J. (2016). The asynchronous time warp for virtual reality on consumer hardware. In Proc. 22nd ACM Conference on Virtual Reality Software and Technology, pages 37–46.
Bernadini, F. C. (2006). Combinação de classificadores simbólicos utilizando medidas de regras de conhecimento e algoritmos genéticos. Technical report, Universidade de São Paulo.
Bouyer, G., Chellali, A., and Lécuyer, A. (2017). Inducing self-motion sensations in driving simulators using force-feedback and haptic motion. In Virtual Reality (VR), 2017 IEEE, pages 84–90. IEEE.
Budhiraja, P., Miller, M. R., Modi, A. K., and Forsyth, D. (2017). Rotation blurring: Use of artificial blurring to reduce cybersickness in virtual reality first person shooters. arXiv preprint arXiv:1710.02599.
Calvelo, M., Piñeiro, Á., and Garcia-Fandino, R. (2020). An immersive journey to the molecular structure of sars-cov-2: Virtual reality in covid-19. Computational and Structural Biotechnology Journal.
Carrión, M., Santorum, M., Benavides, J., Aguilar, J., and Ortiz, Y. (2019). Developing a virtual reality serious game to recreational therapy using iplus methodology. In 2019 International Conference on Virtual Reality and Visualization (ICVRV), pages 133– 137. IEEE.
Curry, C., Li, R., Peterson, N., and Stoffregen, T. A. (2020). Cybersickness in virtual reality head-mounted displays: Examining the influence of sex differences and vehicle control. International Journal of Human–Computer Interaction, pages 1–7.
Davis, S., Nesbitt, K., and Nalivaiko, E. (2014). A systematic review of cybersickness. In Proceedings of the 2014 Conference on Interactive Entertainment, pages 1–9. ACM.
Dennison, M. S. and D’Zmura, M. (2017). Cybersickness without the wobble: experimental results speak against postural instability theory. Applied ergonomics, 58:215–223.
Drucker, H., Burges, C. J., Kaufman, L., Smola, A. J., and Vapnik, V. (1997). Support vector regression machines. In Advances in neural information processing systems, pages 155–161.
Flach, P. (2012). Machine Learning: The Art and Science of Algorithms That Make Sense of Data. Cambridge.
Garcia-Agundez, A., Reuter, C., Becker, H., Konrad, R., Caserman, P., Miede, A., and Göbel, S. (2019). Development of a classifier to determine factors causing cybersickness in virtual reality environments. Games for health journal, 8(6):439–444.
Grassini, S. and Laumann, K. (2020). Are modern head-mounted displays sexist? a systematic review on gender differences in hmd-mediated virtual reality. Frontiers in Psychology, 11.
Graves, A., Mohamed, A.-r., and Hinton, G. (2013). Speech recognition with deep recurrent neural networks. In 2013 IEEE international conference on acoustics, speech and signal processing, pages 6645–6649. IEEE.
Jeong, D., Yoo, S., and Yun, J. (2019). Cybersickness analysis with EEG using deep learning algorithms. In 2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR), pages 827–835. IEEE.
Jin, W., Fan, J., Gromala, D., and Pasquier, P. (2018). Automatic prediction of cybersickness for virtual reality games. In 2018 IEEE Games, Entertainment, Media Conference (GEM), pages 1–9. IEEE.
Kemeny, A., Chardonnet, J.-R., and Colombet, F. (2020). Getting Rid of Cybersickness: In Virtual Reality, Augmented Reality, and Simulators. Springer Nature.
Kim, J., Kim, W., Oh, H., Lee, S., and Lee, S. (2019). A deep cybersickness predictor based on brain signal analysis for virtual reality contents. In Proceedings of the IEEE International Conference on Computer Vision, pages 10580–10589.
Kolasinski, E. M. (1995). Simulator sickness in virtual environments. Technical report, DTIC Document.
Kühnapfel, U., Cakmak, H. K., and Maaß, H. (2000). Endoscopic surgery training using virtual reality and deformable tissue simulation. Computers & graphics, 24(5):671– 682.
Lawrence, S., Giles, C. L., Tsoi, A. C., and Back, A. D. (1997). Face recognition: A convolutional neural-network approach. IEEE transactions on neural networks, 8(1):98– 113.
Liang, H.-N., Lu, F., Shi, Y., Nanjappan, V., and Papangelis, K. (2019). Evaluating the effects of collaboration and competition in navigation tasks and spatial knowledge acquisition within virtual reality environments. Future Generation Computer Systems, 95:855–866.
Maree, C. and Omlin, C. W. (2020). Towards responsible ai for financial transactions. In 2020 IEEE Symposium Series on Computational Intelligence (SSCI), pages 16–21. IEEE.
Melo, M., Vasconcelos-Raposo, J., and Bessa, M. (2018). Presence and cybersickness in immersive content: effects of content type, exposure time and gender. Computers & Graphics, 71:159–165.
Mousavi, M., Jen, Y. H., and Musa, S. N. B. (2013). A review on cybersickness and usability in virtual environments. In Advanced Engineering Forum, volume 10, pages 34–39. Trans Tech Publ.
Porcino, T. (2021). Cybersickness Dataset. https://github.com/tmp1986/UFFCSData. Accessed: 2021-04-03.
Porcino, T., Rodrigues, E. O., Bernardini, F., Trevisan, D., and Clua, E. (2021a). Identifying cybersickness causes in virtual reality games using symbolic machine learning algorithms. Entertainment Computing, page 100473.
Porcino, T., Rodrigues, E. O., Bernardini, F., Trevisan, D., and Clua, E. (2021b). A symbolic machine learning approach for cybersickness potential-cause estimation. In International Conference on Entertainment Computing, pages 115–126. Springer.
Porcino, T., Rodrigues, E. O., Silva, A., Clua, E., and Trevisan, D. (2020a). 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), pages 1–8. IEEE.
Porcino, T., Trevisan, D., and Clua, E. (2020b). Minimizing cybersickness in headmounted display systems: causes and strategies review. In 2020 22nd Symposium on Virtual and Augmented Reality (SVR), pages 154–163. IEEE.
Porcino, T., Trevisan, D., and Clua, E. (2021c). Cybersickness analysis using symbolic machine learning algorithms. In Anais Estendidos do XXIII Simpósio de Realidade Virtual e Aumentada, pages 3–4. SBC.
Porcino, T., Trevisan, D., and Clua, E. (2021d). A cybersickness review: causes, strategies, and classification methods. Journal on Interactive Systems, 12(1):269–282.
Porcino, T., Trevisan, D., and Clua, E. (2021e). An experimental methodology to capture user and gameplay data tied to cybersickness. In Proceedings of the 1st XR in Games Workshop. SBC.
Porcino, T. M., Clua, E., Trevisan, D., Vasconcelos, C. N., and Valente, L. (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, pages 1–6. IEEE.
Ramsey, A., Nichols, S., and Cobb, S. (1999). Virtual reality induced symptoms and effects (vrise) in four different virtual reality display conditions. In Proceedings of HCI International (the 8th International Conference on Human-Computer Interaction) on Human-Computer Interaction: Ergonomics and User Interfaces-Volume I-Volume I, pages 142–146. L. Erlbaum Associates Inc.
Rebenitsch, L. and Owen, C. (2016). Review on cybersickness in applications and visual displays. Virtual Reality, 20(2):101–125.
Rizzo, A., Parsons, T. D., Lange, B., Kenny, P., Buckwalter, J. G., Rothbaum, B., Difede, J., Frazier, J., Newman, B., Williams, J., et al. (2011). Virtual reality goes to war: A brief review of the future of military behavioral healthcare. Journal of clinical psychology in medical settings, 18(2):176–187.
Rodrigues, E., Conci, A., and Panos, L. (2018). Morphological classifiers. Pattern Recognition, 84:82–96.
Sak, H., Senior, A.W., and Beaufays, F. (2014). Long short-term memory recurrent neural network architectures for large scale acoustic modeling.
Statista, A. (2020). The statistics portal. Web site: [link].
Studios, B. G. (2015). The elder scrolls v: Skyrim. Bethesda Game Studios.
Van Waveren, J. (2016). The asynchronous time warp for virtual reality on consumer hardware. In Proc. 22nd ACM Conference on Virtual Reality Software and Technology, pages 37–46.
Publicado
31/07/2022
Como Citar
PORCINO, Thiago; TREVISAN, Daniela; CLUA, Esteban.
Cybersickness Analysis Using Symbolic Machine Learning Algorithms. In: CONCURSO DE TESES E DISSERTAÇÕES (CTD), 35. , 2022, Niterói.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 51-60.
ISSN 2763-8820.
DOI: https://doi.org/10.5753/ctd.2022.222026.
