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Low-Cost Robotic Guide Based on a Motor Imagery Brain–Computer Interface for Arm Assisted Rehabilitation

Author

Listed:
  • Eduardo Quiles

    (Instituto de Automática e Informática Industrial, Universitat Politècnica de València, 46022 València, Spain)

  • Ferran Suay

    (Departament de Psicobiologia, Facultat de Psicologia, Universitat de València, 46010 València, Spain)

  • Gemma Candela

    (Departament de Psicobiologia, Facultat de Psicologia, Universitat de València, 46010 València, Spain)

  • Nayibe Chio

    (Instituto de Automática e Informática Industrial, Universitat Politècnica de València, 46022 València, Spain
    Facultad de Ingeniería, Ingeniería Mecatrónica, Universidad Autónoma de Bucaramanga, Bucaramanga 680003, Colombia)

  • Manuel Jiménez

    (Facultad de Educación, Universidad Internacional de la Rioja, 26006 Logroño, Spain)

  • Leandro Álvarez-Kurogi

    (Facultad de Educación, Universidad Internacional de la Rioja, 26006 Logroño, Spain)

Abstract

Motor imagery has been suggested as an efficient alternative to improve the rehabilitation process of affected limbs. In this study, a low-cost robotic guide is implemented so that linear position can be controlled via the user’s motor imagination of movement intention. The patient can use this device to move the arm attached to the guide according to their own intentions. The first objective of this study was to check the feasibility and safety of the designed robotic guide controlled via a motor imagery (MI)-based brain–computer interface (MI-BCI) in healthy individuals, with the ultimate aim to apply it to rehabilitation patients. The second objective was to determine which are the most convenient MI strategies to control the different assisted rehabilitation arm movements. The results of this study show a better performance when the BCI task is controlled with an action–action MI strategy versus an action–relaxation one. No statistically significant difference was found between the two action–action MI strategies.

Suggested Citation

  • Eduardo Quiles & Ferran Suay & Gemma Candela & Nayibe Chio & Manuel Jiménez & Leandro Álvarez-Kurogi, 2020. "Low-Cost Robotic Guide Based on a Motor Imagery Brain–Computer Interface for Arm Assisted Rehabilitation," IJERPH, MDPI, vol. 17(3), pages 1-16, January.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:3:p:699-:d:311665
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    References listed on IDEAS

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    1. Elisabeth V C Friedrich & Christa Neuper & Reinhold Scherer, 2013. "Whatever Works: A Systematic User-Centered Training Protocol to Optimize Brain-Computer Interfacing Individually," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-1, September.
    2. Konstantina Kilteni & Benjamin Jan Andersson & Christian Houborg & H. Henrik Ehrsson, 2018. "Motor imagery involves predicting the sensory consequences of the imagined movement," Nature Communications, Nature, vol. 9(1), pages 1-9, December.
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