Low-Cost Robotic Guide Based on a Motor Imagery Brain–Computer Interface for Arm Assisted Rehabilitation
by
Eduardo Quiles 1,*
, Ferran Suay 2, Gemma Candela 2, Nayibe Chio 1,3, 
Manuel Jiménez 4 and Leandro Álvarez-Kurogi 4
Eduardo Quiles 1,*, Ferran Suay 2, Gemma Candela 2, Nayibe Chio 1,3, Manuel Jiménez 4 and Leandro Álvarez-Kurogi 4
1
Instituto de Automática e Informática Industrial, Universitat Politècnica de València, 46022 València, Spain
2
Departament de Psicobiologia, Facultat de Psicologia, Universitat de València, 46010 València, Spain
3
Facultad de Ingeniería, Ingeniería Mecatrónica, Universidad Autónoma de Bucaramanga, Bucaramanga 680003, Colombia
4
Facultad de Educación, Universidad Internacional de la Rioja, 26006 Logroño, Spain
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(3), 699; https://doi.org/10.3390/ijerph17030699
Received: 23 December 2019 / Revised: 10 January 2020 / Accepted: 17 January 2020 / Published: 21 January 2020
(This article belongs to the Special Issue Application of Robotic Devices for Neurologic Rehabilitation)
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.
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Keywords:
robotic rehabilitation; robot-assisted therapy; brain computer interfaces in neurorehabilitation; EEG sensors
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MDPI and ACS Style
Quiles, E.; Suay, F.; Candela, G.; Chio, N.; Jiménez, M.; Álvarez-Kurogi, L. Low-Cost Robotic Guide Based on a Motor Imagery Brain–Computer Interface for Arm Assisted Rehabilitation. Int. J. Environ. Res. Public Health 2020, 17, 699.
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