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Catching Virtual Throws: An Immersive Virtual Reality Setup to Evaluate Human Predictive Skills

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Augmented Reality, Virtual Reality, and Computer Graphics (AVR 2018)

Abstract

We present and validate a novel and portable IVR setup conceived for studying the predictive mechanisms associated to action observation. The setup implements an interactive throwing-catching task in which participants have to intercept balls thrown from a virtual character. To validate the setup, we performed a preliminary experiment in which participants had to intercept balls thrown by different throwers, under different ball/thrower visibility conditions. Non-expert adult participants were able to extract information from an observed throwing action to improve their interceptive performances. This ability was modulated by the throwing strategy (e.g. throwing from a fixed stance with respect to throwing with stepping corresponded to worse interceptive performances). These preliminary results validate our setup as a novel tool for exploring how humans access and make use of information from observed actions to optimize interpersonal interactions. Importantly, the proposed setup could be used as a tool for early diagnosis of pathologies in which predictive skills are progressively impaired.

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Acknowledgments

This work was supported by Horizon 2020 Robotics Program CogIMon (ICT-23-2014 under grant Agreement 644727), by the Italian Education, University and Research Ministry (PRIN grant 2015HFWRYY), and by the Italian Space Agency (contract n. I/006/06/0).

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Correspondence to Antonella Maselli .

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Maselli, A., Cesqui, B., Tommasino, P., Dhawan, A., Lacquaniti, F., d’Avella, A. (2018). Catching Virtual Throws: An Immersive Virtual Reality Setup to Evaluate Human Predictive Skills. In: De Paolis, L., Bourdot, P. (eds) Augmented Reality, Virtual Reality, and Computer Graphics. AVR 2018. Lecture Notes in Computer Science(), vol 10850. Springer, Cham. https://doi.org/10.1007/978-3-319-95270-3_19

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  • DOI: https://doi.org/10.1007/978-3-319-95270-3_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95269-7

  • Online ISBN: 978-3-319-95270-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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