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Feedback-Error Learning for Gait Rehabilitation Using a Powered Knee Orthosis: First Advances

AuthorsNuno Fernandes, Pedro; Carvalho, Simão; Figueiredo, Joana; Moreno, Juan Camilo ; Santos, Cristina P.
Keywordsadaptive control
control engineering computing
gait analysis
learning (artificial intelligence)
patient rehabilitation
three-term control
trajectory control
Issue Date22-Feb-2019
PublisherInstitute of Electrical and Electronics Engineers
Citation2019 IEEE 6th Portuguese Meeting on Bioengineering (ENBENG) in Lisbon, Portugal, 22 February 2019.
AbstractPowered assistive devices have been playing a major role in gait rehabilitation. Hereby, the development of time-effective control strategies to manage such devices is a key concern to rehabilitation engineering. This paper presents a real-time Feedback-Error Learning control strategy, by means of an Artificial Neural Network as a feedforward controller to acquire the inverse model of the plant, and a Proportional-Integral-Derivative feedback controller to guarantee stability and handle with disturbances. A Powered Knee Orthosis was used as the assistive device and a trajectory generator assistive strategy, previously acquired through an inertial system, was applied. A validation with one subject walking in a treadmill at 1 km/h with the Powered Knee Orthosis controlled by the Feedback-Error Learning control was performed. Evidences on the control behavior presented good performances, with the Artificial Neural Network taking 90 seconds to learn the inverse model, which enabled a decrease in the angular position error by 75% and eliminated the phase delay, when compared to solo Proportional-Integral-Derivative feedback controller. Robust reactions to external disturbances were also achieved. The implemented Feedback-Error Learning strategy proves to be a time-effective asset to control assistive powered devices.
DescriptionTrabajo presentado en 2019 IEEE 6th Portuguese Meeting on Bioengineering (ENBENG) en Lisboa, Portugal, el 22 de Febrero de 2019.
Publisher version (URL)http://dx.doi.org/10.1109/ENBENG.2019.8692502
Identifiersdoi: 10.1109/ENBENG.2019.8692502
isbn: 978-1-5386-8506-8
Appears in Collections:(IC) Comunicaciones congresos
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