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EVA: EVAluating at-home rehabilitation exercises using augmented reality and low-cost sensors

Virtual Reality volume 24, pages 567–581 (2020)Cite this article

Abstract

Over one billion people in the world live with some form of disability. This is incessantly increasing due to aging population and chronic diseases. Among the emerging social needs, rehabilitation services are the most required. However, they are scarce and expensive what considerably limits access to them. In this paper, we propose EVA, an augmented reality platform to engage and supervise rehabilitation sessions at home using low-cost sensors. It also stores the user’s statistics and allows therapists to tailor the exercise programs according to their performance. This system has been evaluated in both qualitative and quantitative ways obtaining very promising results.

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Acknowledgements

This work has been supported by the Spanish Government TIN2016-76515R Grant, supported with Feder funds. Edmanuel Cruz is funded by a Panamenian grant for Ph.D. studies IFARHU and SENACYT 270-2016-207. This work has also been supported by a Spanish grant for PhD studies ACIF/2017/243 and FPU16/00887. Thanks also to Nvidia for the generous donation of a Titan Xp and a Quadro P6000.

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  1. University Institute for Computer Research, Universidad de Alicante, Alicante, Spain

    Felix Escalona, Ester Martinez-Martin, Edmanuel Cruz, Miguel Cazorla & Francisco Gomez-Donoso

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  1. Felix Escalona
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  2. Ester Martinez-Martin
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  3. Edmanuel Cruz
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  4. Miguel Cazorla
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  5. Francisco Gomez-Donoso
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Correspondence to Francisco Gomez-Donoso.

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Escalona, F., Martinez-Martin, E., Cruz, E. et al. EVA: EVAluating at-home rehabilitation exercises using augmented reality and low-cost sensors. Virtual Reality 24, 567–581 (2020). https://doi.org/10.1007/s10055-019-00419-4

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  • DOI: https://doi.org/10.1007/s10055-019-00419-4

Keywords

  • Rehabilitation exercises
  • Deep learning
  • Augmented reality
  • Human–computer interaction
  • 3D visualization
  • Low-cost sensors