ABSTRACT
We present BrainX3 as a novel immersive and interactive technology for exploration of large biological data, which in this paper is customized towards brain networks. Unlike traditional machine-inference systems, BrainX3 posits a two-way coupling of human intuition to powerful machine computation to tackle the big data challenge.
Furthermore, through unobtrusive wearable sensors, BrainX3 can infer user's states in terms of arousal and cognitive workload, thus changing the visualization and the sonification parameters to boost the exploration process.
- J. Beatty and B. Lucero-Wagoner. Pupillary System. In J. T. Cacioppo, L. Tassinary, and G. Berntson, editors, Handbook of Psychophysiology, chapter 6, pages 142--162. Cambridge University Press, New York, NY, USA, 2nd edition, 2000.Google Scholar
- U. Bernardet, A. Väljamäe, M. Inderbitzin, S. Wierenga, A. Mura, and P. F. M. J. Verschure. Quantifying human subjective experience and social interaction using the eXperience Induction Machine. Brain research bulletin, 85:305--312, Nov. 2010.Google Scholar
- A. Betella, R. Carvalho, J. Sanchez-palencia, U. Bernardet, and P. F. M. J. Verschure. Embodied Interaction with Complex Neuronal Data in Mixed-Reality. In Virtual Reality International Conference (VRIC 2012), 2012. Google ScholarDigital Library
- A. Betella, E. Martínez, R. Zucca, X. D. Arsiwalla, P. Omedas, S. Wierenga, A. Mura, J. Wagner, F. Lingenfelser, E. André, D. Mazzei, A. Tognetti, A. Lanatà, D. De Rossi, and P. F. M. J. Verschure. Advanced interfaces to stem the data deluge in mixed reality: placing human (un)consciousness in the loop. In ACM SIGGRAPH 2013 Posters, SIGGRAPH '13, pages 68:1---_68:1, New York, NY, USA, 2013. ACM. Google ScholarDigital Library
- A. Betella, D. Pacheco, R. Zucca, X. D. Arsiwalla, P. Omedas, A. Lanatà, D. Mazzei, A. Tognetti, A. Greco, N. Carbonaro, J. Wagner, F. Lingenfelser, E. André, D. De Rossi, and P. F. M. J. Verschure. Interpreting Psychophysiological States Using Unobtrusive Wearable Sensors in Virtual Reality. In ACHI2014: The Seventh International Conference on Advances in Computer-Human Interactions, pages 331--336, Barcelona, Spain, 2014.Google Scholar
- R. Cetnarski, A. Betella, H. Prins, S. Koudier, and P. F. M. J. Verschure. Subliminal Response Priming in mixed reality: The ecological validity of a classic paradigm of perception. Presence: Teleoperators and Virtual Environments, In Press. Google ScholarDigital Library
- P. Hagmann, L. Cammoun, X. Gigandet, R. Meuli, C. J. Honey, V. J. Wedeen, and O. Sporns. Mapping the Structural Core of Human Cerebral Cortex. PLoS Biology, 6(7):15, 2008.Google Scholar
- D. A. Keim. Information visualization and visual data mining. Visualization and Computer Graphics, IEEE Transactions on, 8(1):1--8, 2002. Google ScholarDigital Library
- S. Lee, J. Seo, G. J. Kim, and C. mo Park. Evaluation of pointing techniques for ray casting selection in virtual environments. In Third International Conference on Virtual Reality and Its Application in Industry, pages 38--44, 2003.Google ScholarCross Ref
- P. Papachristodoulou, A. Betella, and P. F. M. J. Verschure. Sonification of Large Datasets in a 3D Immersive Environment: A Neuroscience Case Study. In ACHI2014: The Seventh International Conference on Advances in Computer-Human Interactions, pages 35--40, Barcelona, Spain, 2014.Google Scholar
- P. Stein, M. Bosner, R. Kleiger, and B. Conger. Heart rate variability: a measure of cardiac autonomic tone. American Heart Journal, 127(5):1376--1381, 1994.Google ScholarCross Ref
- P. F. M. J. Verschure. Distributed Adaptive Control: A theory of the Mind, Brain, Body Nexus. Biologically Inspired Cognitive Architectures, 1:55--72, July 2012.Google ScholarCross Ref
- J. Wagner, F. Lingenfelser, T. Baur, I. Damian, F. Kistler, and E. André. The Social Signal Interpretation (SSI) Framework Multimodal Signal Processing and Recognition in Real-Time. In Proceedings of the 21st ACM International Conference on Multimedia, pages 21--25, 2013. Google ScholarDigital Library
- K. Wolf. What I grasp is what I control: interacting through grasp releases. In Proceedings of the Sixth International Conference on Tangible, Embedded and Embodied Interaction, TEI '12, pages 389--390, New York, NY, USA, 2012. ACM. Google ScholarDigital Library
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