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

Methods and Protocols

卷:4

on behalf of the PRO GAIT Consortium¹  Luca Tonin²  Stefano Tortora²  Stefano Masiero³  Maria Rubega³  Giacomo Dazzi³  Emanuela Formaggio³  Roberto Di Marco³  Chiara Venturin³  Alessandra Del Felice³  Ilenia Bonini⁴  Humberto Antonio Cerrel Bazo⁴  Olive Lennon⁵  Rupert Ortner⁶  Ngadhnjim Sutaj⁶ 

[1] ;

[2] Department of Information Engineering, University of Padova, 35131 Padova, Italy;

[3] Department of Neurosciences, Section of Rehabilitation, University of Padova, via Belzoni, 160, 35121 Padova, Italy;

[4] Ospedale Riabilitativo di Alta Specializzazione di Motta di Livenza, 31045 Treviso, Italy;

[5] School of Public Health, Physiotherapy and Sports Science, University College Dublin, 4 Dublin, Ireland;

[6] g.tec Medical Engineering GmbH, 4521 Schiedlberg, Austria;

关键词: rehabilitation;    stroke;    aging;    EEG;    EMG;    neuromuscular plasticity;   

DOI  :  10.3390/mps4030048

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown