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1.
J Neuroeng Rehabil ; 14(1): 104, 2017 10 12.
Article in English | MEDLINE | ID: mdl-29025427

ABSTRACT

BACKGROUND: Brain injury survivors often present upper-limb motor impairment affecting the execution of functional activities such as reaching. A currently active research line seeking to maximize upper-limb motor recovery after a brain injury, deals with the combined use of functional electrical stimulation (FES) and mechanical supporting devices, in what has been previously termed hybrid robotic systems. This study evaluates from the technical and clinical perspectives the usability of an integrated hybrid robotic system for the rehabilitation of upper-limb reaching movements after a brain lesion affecting the motor function. METHODS: The presented system is comprised of four main components. The hybrid assistance is given by a passive exoskeleton to support the arm weight against gravity and a functional electrical stimulation device to assist the execution of the reaching task. The feedback error learning (FEL) controller was implemented to adjust the intensity of the electrical stimuli delivered on target muscles according to the performance of the users. This control strategy is based on a proportional-integral-derivative feedback controller and an artificial neural network as the feedforward controller. Two experiments were carried out in this evaluation. First, the technical viability and the performance of the implemented FEL controller was evaluated in healthy subjects (N = 12). Second, a small cohort of patients with a brain injury (N = 4) participated in two experimental session to evaluate the system performance. Also, the overall satisfaction and emotional response of the users after they used the system was assessed. RESULTS: In the experiment with healthy subjects, a significant reduction of the tracking error was found during the execution of reaching movements. In the experiment with patients, a decreasing trend of the error trajectory was found together with an increasing trend in the task performance as the movement was repeated. Brain injury patients expressed a great acceptance in using the system as a rehabilitation tool. CONCLUSIONS: The study demonstrates the technical feasibility of using the hybrid robotic system for reaching rehabilitation. Patients' reports on the received intervention reveal a great satisfaction and acceptance of the hybrid robotic system. TRIAL REGISTRATION: Retrospective trial registration in ISRCTN Register with study ID ISRCTN12843006 .


Subject(s)
Brain Injuries/rehabilitation , Robotics/instrumentation , Stroke Rehabilitation/methods , Adult , Female , Humans , Male , Middle Aged , Movement/physiology , Neural Networks, Computer , Retrospective Studies , Upper Extremity/physiology
2.
Annu Int Conf IEEE Eng Med Biol Soc ; 2016: 6381-6384, 2016 Aug.
Article in English | MEDLINE | ID: mdl-28269708

ABSTRACT

Reaching and grasping are two of the most affected functions after stroke. Hybrid rehabilitation systems combining Functional Electrical Stimulation with Robotic devices have been proposed in the literature to improve rehabilitation outcomes. In this work, we present the combined use of a hybrid robotic system with an EEG-based Brain-Machine Interface to detect the user's movement intentions to trigger the assistance. The platform has been tested in a single session with a stroke patient. The results show how the patient could successfully interact with the BMI and command the assistance of the hybrid system with low latencies. Also, the Feedback Error Learning controller implemented in this system could adjust the required FES intensity to perform the task.


Subject(s)
Brain-Computer Interfaces , Movement/physiology , Robotics/methods , Stroke Rehabilitation/methods , Stroke/physiopathology , Aged , Exoskeleton Device , Feedback , Hand Strength , Humans , Learning , Male , Rotation
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