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Bio-Inspired Adaptive Control for Active Knee Exoprosthetics.
IEEE Trans Neural Syst Rehabil Eng ; 25(12): 2355-2364, 2017 12.
Article in En | MEDLINE | ID: mdl-28858807
On the quest to bring function of prosthetic legs closer to their biological counterparts, the intuitive interplay of their control with the user's impedance modulation is key. We present two control features to enable more physiological and more user-adaptive control of prosthetic legs: a neuromusculoskeletal impedance model ( ) including a reflexive component, and a human model reference adaptive controller ( ), which can be combined with the former. In stance-phase simulations, the allowed to control a prosthetic leg with physiological knee joint angle and moment. When perturbations were applied, the reduced the resulting root mean square error (RMSE) between simulated and physiological reference angle by 96%. In a pilot experiment with two unimpaired and one amputee subject, gait with the deviated more from a physiological reference than with a conventional visco-elastic impedance controller. Subjects, however, preferred the . When adding the to either of the two impedance controllers, the RMSE between the actual and the physiological reference angle was reduced by up to 54%. Subjects confirmed this finding and reported an easier stance-to-swing transition. Simulation and pilot experiment suggest that a reflex-based impedance controller combined with an adaptive controller may improve user-cooperative behavior of active knee exoprostheses.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Exoskeleton Device / Knee Prosthesis Type of study: Prognostic_studies Limits: Adult / Female / Humans / Male / Middle aged Language: En Journal: IEEE Trans Neural Syst Rehabil Eng Journal subject: ENGENHARIA BIOMEDICA / REABILITACAO Year: 2017 Document type: Article Country of publication: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Exoskeleton Device / Knee Prosthesis Type of study: Prognostic_studies Limits: Adult / Female / Humans / Male / Middle aged Language: En Journal: IEEE Trans Neural Syst Rehabil Eng Journal subject: ENGENHARIA BIOMEDICA / REABILITACAO Year: 2017 Document type: Article Country of publication: United States