AUTHOR=Sylos-Labini Francesca , La Scaleia Valentina , d'Avella Andrea , Pisotta Iolanda , Tamburella Federica , Scivoletto Giorgio , Molinari Marco , Wang Shiqian , Wang Letian , van Asseldonk Edwin , van der Kooij Herman , Hoellinger Thomas , Cheron Guy , Thorsteinsson Freygardur , Ilzkovitz Michel , Gancet Jeremi , Hauffe Ralf , Zanov Frank , Lacquaniti Francesco , Ivanenko Yuri P. TITLE=EMG patterns during assisted walking in the exoskeleton JOURNAL=Frontiers in Human Neuroscience VOLUME=8 YEAR=2014 URL=https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2014.00423 DOI=10.3389/fnhum.2014.00423 ISSN=1662-5161 ABSTRACT=

Neuroprosthetic technology and robotic exoskeletons are being developed to facilitate stepping, reduce muscle efforts, and promote motor recovery. Nevertheless, the guidance forces of an exoskeleton may influence the sensory inputs, sensorimotor interactions and resulting muscle activity patterns during stepping. The aim of this study was to report the muscle activation patterns in a sample of intact and injured subjects while walking with a robotic exoskeleton and, in particular, to quantify the level of muscle activity during assisted gait. We recorded electromyographic (EMG) activity of different leg and arm muscles during overground walking in an exoskeleton in six healthy individuals and four spinal cord injury (SCI) participants. In SCI patients, EMG activity of the upper limb muscles was augmented while activation of leg muscles was typically small. Contrary to our expectations, however, in neurologically intact subjects, EMG activity of leg muscles was similar or even larger during exoskeleton-assisted walking compared to normal overground walking. In addition, significant variations in the EMG waveforms were found across different walking conditions. The most variable pattern was observed in the hamstring muscles. Overall, the results are consistent with a non-linear reorganization of the locomotor output when using the robotic stepping devices. The findings may contribute to our understanding of human-machine interactions and adaptation of locomotor activity patterns.