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 statusE-pub ahead of print - 3 Feb 2022

Keywords

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

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