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

Eduardo Quiles, Ferran Suay, Gemma Candela, Nayibe Chio, Manuel Jiménez and Leandro Álvarez-Kurogi
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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
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

IJERPH, 2020, vol. 17, issue 3, 1-16

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.

Keywords: robotic rehabilitation; robot-assisted therapy; brain computer interfaces in neurorehabilitation; EEG sensors (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
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