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European Conference on Technology Enhanced Learning

EC-TEL 2017: Data Driven Approaches in Digital Education pp 593–597Cite as

Towards Personalized Vibrotactile Support for Learning Aikido

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10474))

Abstract

Aikido is a defensive martial art that involves the acquisition of specific motor skills by practicing the techniques over and over with another learner. Most of existing technological support to learn martial arts track learner’s postures or gestures with optical caption techniques and deliver non-personalized visual support about the performance. This paper proposes a sensor-based learning environment that aims to track body and mind interactions when learning Aikido techniques and deliver personalized vibrotactile support when learners’ movements differ from the expected performance.

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Author information

Authors and Affiliations

  1. aDeNu Research Group, Artificial Intelligence Department, Computer Science School, UNED, Madrid, Spain

    Olga C. Santos

Authors
  1. Olga C. Santos
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Corresponding author

Correspondence to Olga C. Santos .

Editor information

Editors and Affiliations

  1. Jean Moulin Lyon 3 University, Lyon, France

    Élise Lavoué

  2. German Institute for International Educational Research, Goethe University, Frankfurt, Germany

    Hendrik Drachsler

  3. KU Leuven, Leuven, Belgium

    Katrien Verbert

  4. University of Toulouse, Toulouse, France

    Julien Broisin

  5. Pontificia Universidad, Santiago de Chile, Chile

    Mar Pérez-Sanagustín

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Santos, O.C. (2017). Towards Personalized Vibrotactile Support for Learning Aikido. In: Lavoué, É., Drachsler, H., Verbert, K., Broisin, J., Pérez-Sanagustín, M. (eds) Data Driven Approaches in Digital Education. EC-TEL 2017. Lecture Notes in Computer Science(), vol 10474. Springer, Cham. https://doi.org/10.1007/978-3-319-66610-5_70

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  • DOI: https://doi.org/10.1007/978-3-319-66610-5_70

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-66609-9

  • Online ISBN: 978-3-319-66610-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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