Juan Carlos Fraile
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Recent Grants
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Desarrollo de nueva tecnología de electroencefalografía para sistemas Brain Computer Interface asistenciales
Open Date: 2022-06-01
Close Date: 2024-06-01
Grant: Close
Electrificación de la movilidad en minas chilenas: desarrollo de estrategias y servicios de gestión para movilidad sostenible.
Open Date: 2022-01-01
Close Date: 2024-01-01
Grant: Close
Desarrollo y ensayos clínicos de una plataforma de rehabilitación para acelerar la recuperación de pacientes con secuelas neuromotoras producidas por el COVID
Open Date: 2021-09-01
Close Date: 2022-12-01
Grant: Close
Surgical Multi-Robot Coordination - Robotic Anastomosis Competence Evaluation
Open Date: 2020-06-01
Close Date: 2022-12-01
Grant: Close
Platform for Neuromotor and Cognitive Rehabilitation through Active Therapies in People Who Have Suffered a Cerebrovascular Accident
Open Date: 2020-01-01
Close Date: 2023-12-01
Articles (17)
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2025
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2025
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2025
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2025
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2024
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2024
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2024
The effectiveness of EMG biofeedback with neurorehabilitation robotic platforms has not been previously addressed. The present work evaluates the influence of an EMG-based visual biofeedback on the user performance when performing EMG-driven bilateral exercises with a robotic hand exoskeleton. Eighteen healthy subjects were asked to perform 1-min randomly generated sequences of hand gestures (rest, open and close) in four different conditions resulting from the combination of using or not (1) EMG-based visual biofeedback and (2) kinesthetic feedback from the exoskeleton movement. The user performance in each test was measured by computing similarity between the target gestures and the recognized user gestures using the L2 distance. Statistically significant differences in the subject performance were found in the type of provided feedback (p-value 0.0124). Pairwise comparisons showed that the L2 distance was statistically significantly lower when only EMG-based visual feedback was present (2.89 ± 0.71) than with the presence of the kinesthetic feedback alone (3.43 ± 0.75, p-value = 0.0412) or the combination of both (3.39 ± 0.70, p-value = 0.0497). Hence, EMG-based visual feedback enables subjects to increase their control over the movement of the robotic platform by assessing their muscle activation in real time. This type of feedback could benefit patients in learning more quickly how to activate robot functions, increasing their motivation towards rehabilitation.
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2023
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2023
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2022
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2022
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2021
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2021
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2021
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2021
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2020
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2020
Collaborators (6)
Enrique Bauzano
Profesor Ayudante Doctor
Universidad de Valladolid Escuela de Ingenierías Industriales
Victor Muñoz-Martínez
Full Professor
University of Malaga
Eusebio de la Fuente López
Profesor Titular de Universidad
Universidad de Valladolid
Paula Gordaliza
Assistant Professor (Profesor Ayudante Doctor)
Universidad de Navarra
Jose Maria Sabater-Navarro
Full professor
Miguel Hernandez University
Isabel García Morales
Profesor Titular de Universidad (Departamento de Ingeniería de Sistemas y Automática)
University of Malaga
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