, Worldwide Semiannual Augmented and Virtual Reality Spending Guide, 2016.

C. Chang, W. Pan, L. Tseng, and T. A. Stoffregen, Postural activity and motion sickness during video game play in children and adults, Experimental Brain Research, vol.217, issue.2, pp.299-309, 2012.

J. T. Reason, Motion sickness adaptation: a neural mismatch model, Journal of the Royal Society of Medicine, vol.71, issue.11, pp.819-829, 1978.

M. Mousavi, Y. H. Jen, and S. N. Musa, A Review on Cybersickness and Usability in Virtual Environments, Advanced Engineering Forum, vol.10, pp.34-39, 2013.

C. Diels and P. A. Howarth, Frequency characteristics of visually induced motion sickness, Human Factors, vol.55, issue.3, pp.595-604, 2013.

M. E. St, S. Pierre, A. W. Banerjee, E. R. Hoover, and . Muth, The effects of 0.2Hz varying latency with 20-100ms varying amplitude on simulator sickness in a helmet mounted display, Displays, vol.36, issue.8, 2015.

A. S. Fernandes and S. K. Feiner, Combating VR sickness through subtle dynamic field-ofview modification, 2016 IEEE Symposium on 3D User Interfaces (3DUI), pp.201-210, 2016.

A. C. Paillard, Motion sickness susceptibility in healthy subjects and vestibular patients: effects of gender, age and trait-anxiety, Journal of Vestibular Research: Equilibrium & Orientation, vol.23, issue.4-5, pp.203-209, 2013.

L. L. Arns and M. M. Cerney, The relationship between age and incidence of cybersickness among immersive environment users, IEEE Proceedings. VR 2005. Virtual Reality, pp.267-268, 2005.

A. Cuomo-granston and P. D. Drummond, Migraine and motion sickness: what is the link?, Progress in Neurobiology, vol.91, issue.4, pp.300-312, 2010.

G. Bertolini and D. Straumann, Moving in a Moving World: A Review on Vestibular Motion Sickness, Frontiers in Neurology, vol.7, 2016.

C. M. Oman, A heuristic mathematical model for the dynamics of sensory conflict and motion sickness, Acta Oto-Laryngologica, vol.392, pp.1-44, 1982.

E. M. Kolasinski, U. S. For-the, B. , and S. , Simulator sickness in virtual environments, Sciences, 1995.

R. S. Kennedy, N. E. Lane, K. S. Berbaum, and M. G. , Simulator Sickness Questionnaire: An Enhanced Method for Quantifying Simulator Sickness, The International Journal of Aviation Psychology, vol.3, issue.3, 1993.

B. Keshavarz and H. Hecht, Validating an efficient method to quantify motion sickness, Human Factors, vol.53, issue.4, pp.415-426, 2011.

B. Patrão, S. Pedro, and P. Menezes, How to Deal with Motion Sickness in Virtual Reality, Sciences and Technologies of Interaction (SciTecIN'15), 2015.

P. J. Gianaros, K. S. Quigley, E. R. Muth, M. E. Levine, R. C. Vasko et al., Relationship between temporal changes in cardiac parasympathetic activity and motion sickness severity, Psychophysiology, vol.40, issue.1, pp.39-44, 2003.

M. S. Dennison, A. Z. Wisti, and M. D'zmura, Use of physiological signals to predict cybersickness, Displays, vol.44, pp.42-52, 2016.

S. Ohyama, Autonomic responses during motion sickness induced by virtual reality, Auris Nasus Larynx, vol.34, issue.3, pp.303-306, 2007.

Y. H. Nam, Y. Y. Kim, H. T. Kim, H. D. Ko, and K. S. Park, Automatic detection of nausea using bio-signals during immersion in a virtual reality environment, 2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol.2, p.2013, 2001.

S. B. Kotsiantis, Supervised Machine Learning: A Review of Classification Techniques, Proceedings of the 2007 Conference on Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies, pp.3-24, 2007.

J. Bell, Machine Learning: Hands-On for Developers and Technical Professionals, 2014.

S. D. Kreibig, Autonomic nervous system activity in emotion: a review, Biological Psychology, vol.84, issue.3, pp.394-421, 2010.

W. Boucsein, Electrodermal Activity, 2011.

J. J. Braithwaite, D. G. Watson, R. Jones, and M. Rowe, A guide for analysing electrodermal activity (EDA) & skin conductance responses (SCRs) for psychological experiments, Psychophysiology, vol.49, issue.1, pp.1017-1034, 2013.

L. He, D. Jiang, L. Yang, E. Pei, P. Wu et al., Multimodal Affective Dimension Prediction Using Deep Bidirectional Long Short-Term Memory Recurrent Neural Networks, Proceedings of the 5th International Workshop on Audio/Visual Emotion Challenge, pp.73-80, 2015.