Experimental Protocol to Assess Neuromuscular Plasticity Induced by an Exoskeleton Training Session

Abstract

Exoskeleton gait rehabilitation is an emerging area of research, with potential applications in the elderly and in people with central nervous system lesions, e.g., stroke, traumatic brain/spinal cord injury. However, adaptability of such technologies to the user is still an unmet goal. Despite important technological advances, these robotic systems still lack the fine tuning necessary to adapt to the physiological modification of the user and are not yet capable of a proper human-machine interaction. Interfaces based on physiological signals, e.g., recorded by electroencephalography (EEG) and/or electromyography (EMG), could contribute to solving this technological challenge. This protocol aims to: (1) quantify neuro-muscular plasticity induced by a single training session with a robotic exoskeleton on post-stroke people and on a group of age and sex-matched controls; (2) test the feasibility of predicting lower limb motor trajectory from physiological signals for future use as control signal for the robot. An active exoskeleton that can be set in full mode (i.e., the robot fully replaces and drives the user motion), adaptive mode (i.e., assistance to the user can be tuned according to his/her needs), and free mode (i.e., the robot completely follows the user movements) will be used. Participants will undergo a preparation session, i.e., EMG sensors and EEG cap placement and inertial sensors attachment to measure, respectively, muscular and cortical activity, and motion. They will then be asked to walk in a 15 m corridor: (i) self-paced without the exoskeleton (pre-training session); (ii) wearing the exoskeleton and walking with the three modes of use; (iii) self-paced without the exoskeleton (post-training session). From this dataset, we will: (1) quantitatively estimate short-term neuroplasticity of brain connectivity in chronic stroke survivors after a single session of gait training; (2) compare muscle activation patterns during exoskeleton-gait between stroke survivors and age and sex-matched controls; and (3) perform a feasibility analysis on the use of physiological signals to decode gait intentions.

Design, Development, and Control for the Self-Stabilizing Bipedal Exoskeleton Prototype Co-Ex

“…Currently, the existing protocols for robot-aided walking focus on quasi-static gaits [39]. There is a protocol for dynamic walking for the fully actuated exoskeleton Atalante [11].…”

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

“…Effectiveness of robotic gait training devices to drive neuroplastic recovery of physiological gait in stroke survivors is still unclear [5], [16]. While evidence supports the use of these devices to improve gait-performance compared with treadmill or free-walking training [11], [12], the potential to evoke adaptive neuroplastic changes has rarely been addressed [51], [52]. ERSP and CMC in healthy individuals during unassisted overground walking and exoskeleton assisted walking identified a neural sync-desync pattern aligned, respectively with Heel Strike and Toe Off.…”

“…RAGT delivered during the early subacute phase after stroke [9] increases the likelihood of regaining independent walking and improves walking velocity and capacity. Exoskeleton devices further reduce the therapist’s involvement and the manual handling burden during active gait rehabilitation [10], [11], [12]. However, despite positive evidence supporting RAGT after stroke, it is not clear if RAGT devices provide a positive stimulation to promote neuroplasticity for restoration of independent and efficient walking [13], [14].…”

“…Attila Korik is at School of Computing, Engineering and Intelligent Systems at Ulster University, email: a.korik@ulster.ac.uk, Alessandra Del Felice is at University of Padova, and is responsible of Neurophysiology and Movement Rehabilitation group and email:alessandra.delfelice@unipd.it, Damien Coyle is at School of Computing, Engineering and Intelligent Systems at Ulster University, email: d.coyle@ulster.ac.uk, Sean Murphy is at Mater Misericordiae Hospital, Dublin, email: seanmurphy@mater.ie, Olive Lennon is at School of Public Health, Physiotherapy and Sports Science at University College Dublin, Belfield, Dublin, email: olive.lennon@ucd.ie and capacity. Exoskeleton devices further reduce the therapist's involvement and the manual handling burden during active gait rehabilitation [10], [11], [12]. However, despite positive evidence supporting RAGT after stroke, it is not clear if RAGT devices provide a positive stimulation to promote neuroplasticity for restoration of independent and efficient walking [13], [14].…”

Perspective Chapter: Clinical Standard of a Geriatric Patient as a Virtual Target for Correction of Pharmacotherapy of Hypertension and Stroke in the Elderly

“…Therefore, the rehabilitation of the masticatory-speech apparatus of elderly patients can indeed be improved with restorative training, but not as quickly as one would like. Practice has shown that tangible rehabilitation success comes not earlier than after 3 to 6 weeks of regular training [32][33][34][35][36].…”