Robotic-Assisted Gait for lower-limb Rehabilitation: Evidence of Altered Neural Mechanisms in Stroke

Juan Manuel Mayor-Tores, Ben O'Callaghan, Attila Korik, Alessandra Del Felice, Damien Coyle, Sean Murphy, Olive Lennon

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Abstract

Robotic-Assisted Gait training (RAGT) offers an innovative therapeutic option for restoration of functional gait in stroke survivors, complementing existing physical rehabilitation strategies. However, there is a limited understanding of the neurophysiological response induced by this training in end-users. Neural desynchronization and Cortico-Muscular Coherence (CMC) are two biomarkers that define the level of muscle-cortex association during gait phases and can be used to estimate induced user's adaptation during RAGT. In this study, we measure Event-Related Spectral Perturbation (ERSP) and CMC from three healthy individuals and three stroke survivors during overground-gait with and without an exoskeleton. Results show that (1) the use of the exoskeleton in healthy individuals is associated with a different and more refined motor-control represented in a high θ-desynchronization, (2) altered and noisy ERSP and lower and non-focal β-CMC patterns are observed in Stroke patients when performing overground-gait both with and without the Exoskeleton, and (3) Exoskeleton use in stroke survivors is associated with a reduction in swing-time during gait-cycle, but this effect is not correlated with an increment of θ-desynchronization and/or β-CMC. ERSP and CMC demonstrated evidence of neural modulation in able-bodied users during RAGT, which could not be detected in subacute stroke survivors during RAGT. These results suggest that the gait-parameters changes observed during exoskeleton use in subacute stroke survivors are unlikely to be neurally driven.
Original languageEnglish
Number of pages10
JournalmedRxiv
Early online date3 Feb 2022
DOIs
Publication statusPublished online - 3 Feb 2022

Keywords

  • Exoskeleton
  • Robotic-Assisted Gait Training
  • desynchronization
  • ERSP
  • CMC
  • EEG
  • EMG

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