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

Abstracto


  • AUTHORS

    • Escalona, F.,
    • Martinez-Martin, E.,
    • M., Gomez-Donoso,
    • F. View Correspondence

    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. © 2019, Springer-Verlag London Ltd., part of Springer Nature.

fecha de publicación

  • 2020

Palabras clave

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

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