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. 2017 Oct 12;14:104. doi: 10.1186/s12984-017-0312-4

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© The Author(s). 2017

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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Fig. 3 — a Block diagram of the FES-based Feedback Error Learning (FEL) controller. b Artificial Neural Network used as feedforward loop. $Ø_{r,} {\dot{Ø}}_{r}, {\ddot{Ø}}_{r}$ represent the desired angular position, velocity and acceleration respectively; Ø _h is the measured position of the human arm; e(n) is the error position; μ _ff, μ _fb are the control signal generated for the feedback and feedforward controllers respectively; μ _t is the total assistance; μ _ts is the assistance at the output of the saturator; e _u is the difference between μ _ts and μ _t