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. 2020 Nov 4;19:81. doi: 10.1186/s12938-020-00824-w

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© The Author(s) 2020

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

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Fig. 1 — a Neurophysiological mechanisms of electrical stimulation of muscles and nerves—Illustration of the peripheral pathway generated via the efferent (motor) volley, and afferent (sensory) pathways, generated via the sensory volley during functional electrical stimulation (FES) of muscles and nerves. The antidromic activation along the motor axons and the sensory feedback traverses the spinal cord and activates the sensorimotor cortical networks to synapse with the cortical (descending) signals from the brain when a brain-computer interface (BCI) is used to trigger electrical stimulation. The figure shows electrode placement on the nerve trunk—peripheral nerve stimulation (PNS; black anode) and on the muscle belly—motor point stimulation (MPS; gray anode). b BCI activation of electrical stimulation—Illustration shows the components of the BCI system that can be used to trigger electrical stimulation of muscles and nerves via FES using non-invasive brain oscillatory recordings through electroencephalography (EEG). The main components include: (1) calibration of the state decoder (offline); and (2) control of FES system in real-time (online). During online control of FES, participants should perform functional tasks