RT info:eu-repo/semantics/article
T1 Interaction with a hand rehabilitation exoskeleton in EMG-driven bilateral therapy: Influence of visual biofeedback on the users’ performance
A1 Cisnal de la Rica, Ana
A1 Gordaliza Pastor, Paula
A1 Pérez Turiel, Javier
A1 Fraile Marinero, Juan Carlos
K1 Biofeedback
K1 Biorretroalimentación
K1 Biological control systems
K1 Sistemas de control biológico
K1 Biomedicine
K1 Electromyography
K1 Electromiografía
K1 Human robot interaction
K1 Rehabilitation technology
K1 Robotics
K1 Robotics in medicine
K1 Robótica
K1 Robotic exoskeletons
K1 Neuromuscular diseases - Treatment
K1 Enfermedades neuromusculares - Tratamiento
K1 32 Ciencias Médicas
K1 6103.08 Rehabilitación
K1 3314 Tecnología Médica
AB 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.
PB MDPI
SN 1424-8220
YR 2023
FD 2023
LK https://uvadoc.uva.es/handle/10324/63594
UL https://uvadoc.uva.es/handle/10324/63594
LA eng
NO Sensors, 2023, Vol. 23, Nº. 4, 2048
NO Producción Científica
DS UVaDOC
RD 21-nov-2024