Abstract
Humans’ cognitive and affective states are constantly subject to regular and sudden changes. The origins of these changes are multiple and unpredictable. Virtual Reality (VR) game environments could represent an immersive unconstrained experimental context in which game designers could control a wide range of parameters that act on these states. In this paper, we propose to track and adapt to individuals’ frustration and excitement levels in real time while interacting with a VR environment. We developed “AmbuRun”, a VR game designed to modify the speed and the difficulty in real time. A neural agent was created to control these parameters within the game using an intervention strategy that was intended to induce appropriate modifications of the players ‘excitement and frustration level. An experimental study involving 20 participants was conducted to evaluate our neurofeedback approach. Results showed that intelligent control through neurofeedback of speed and difficulty affected excitement and frustration before and after the agent action.
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References
Yates, M., Kelemen, A., Sik Lanyi, C.: Virtual reality gaming in the rehabilitation of the upper extremities post-stroke. Brain Inj. 30, 855–863 (2016)
Biocca, F.: The Cyborg’s Dilemma: Progressive Embodiment in Virtual Environments [1]. J. Comput.-Mediat. Commun. 3 (2006)
Alvarez, R.P., Johnson, L., Grillon, C.: Contextual-specificity of short-delay extinction in humans: Renewal of fear-potentiated startle in a virtual environment. Learn. Mem. 14, 247–253 (2007)
Bohil, C.J., Alicea, B., Biocca, F.A.: Virtual reality in neuroscience research and therapy. Nat. Rev., Neurosci. (2011)
Benlamine, M.S, Chaouachi, M., Frasson, C.: Dufresne, Aude: Predicting Spontaneous Facial Expressions from EEG. Intell. Tutoring Syst. (2016)
Chaouachi, M., Jraidi, I., Frasson, C.: MENTOR: a physiologically controlled tutoring system. In: Ricci, F., Bontcheva, K., Conlan, O., Lawless, S. (eds.) User Modeling, Adaptation and Personalization, pp. 56–67. Springer International Publishing, Cham (2015)
Lecuyer, A., Lotte, F., Reilly, R.B., Leeb, R., Hirose, M., Slater, M.: Brain-Computer Interfaces, Virtual Reality, and Videogames. Computer 41, 66–72 (2008)
McFarland, D.J., Sarnacki, W.A., Wolpaw, J.R.: Electroencephalographic (EEG) control of three-dimensional movement. J. Neural Eng. 7, 036007 (2010)
Gorini, A., Riva, G.: Virtual reality in anxiety disorders: the past and the future. Expert Rev. Neurother. 8, 215–233 (2008)
Rose, F.D., Brooks, B.M., Rizzo, A.A.: Virtual Reality in Brain Damage Rehabilitation: Review. Cyberpsychol. Behav. 8, 241–262 (2005)
D’Mello, S., Olney, A., Williams, C., Hays, P.: Gaze tutor: A gaze-reactive intelligent tutoring system. Int. J. Hum.-Comput. Stud. 70, 377–398 (2012)
Chaouachi, M., Jraidi, I., Frasson, C.: Adapting to learners’ mental states using a physiological computing approach. In: FLAIRS 2015 Twenty-Eighth Int. Flairs Conf. (2015)
Ghali, R., Ben Abdessalem, H., Frasson, C.: Improving Intuitive Reasoning Through Assistance Strategies in a Virtual Reality Game (2017)
Sherlin, L.H., Arns, M., Lubar, J., Heinrich, H., Kerson, C., Strehl, U., Sterman, M.B.: Neurofeedback and Basic Learning Theory: Implications for Research and Practice. J. Neurother. 15, 292–304 (2011)
Van Doren, J., Heinrich, H., Bezold, M., Reuter, N., Kratz, O., Horndasch, S., Berking, M., Ros, T., Gevensleben, H., Moll, G.H., Studer, P.: Theta/beta neurofeedback in children with ADHD: Feasibility of a short-term setting and plasticity effects. Int. J. Psychophysiol. 112, 80–88 (2017)
Heinrich, H., Gevensleben, H., Strehl, U.: Annotation: Neurofeedback ? train your brain to train behaviour. J. Child Psychol. Psychiatry 48, 3–16 (2007)
Duric, N.S., Elgen, I., Assmus, J.: Self-reported efficacy of neurofeedback treatment in a clinical randomized controlled study of ADHD children and adolescents. Neuropsychiatr. Dis. Treat., 1645 (2014)
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Ben Abdessalem, H., Frasson, C. (2017). Real-time Brain Assessment for Adaptive Virtual Reality Game : A Neurofeedback Approach. In: Frasson, C., Kostopoulos, G. (eds) Brain Function Assessment in Learning. BFAL 2017. Lecture Notes in Computer Science(), vol 10512. Springer, Cham. https://doi.org/10.1007/978-3-319-67615-9_12
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DOI: https://doi.org/10.1007/978-3-319-67615-9_12
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