Quasi-passive lower limbs exosuit: an in-depth assessment of fatigue, kinematic and muscular patterns while comparing assistive strategies on an expert subject's gait analysis.

Front Neurorobot

Laboratory XoLab, Department of Advanced Robotics (ADVR), Istituto Italiano di Tecnologia (IIT), Genova, Italy.

Published: May 2023

Wearable robots are becoming a valuable solution that helps injured, and elderly people regain mobility and improve clinical outcomes by speeding up the rehabilitation process. The XoSoft exosuit identified several benefits, including improvement of assistance, usability, and acceptance with a soft, modular, bio-mimetic, and quasi-passive exoskeleton. This study compares two assistive configurations: (i) a bilateral hip flexion (HA, hips-assistance) and (ii) a bilateral hip flexion combined with ankle plantarflexion (HAA, hips-ankles-assistance) with the main goal of evaluating compensatory actions and synergetic effects generated by the human- exoskeleton interaction. A complete description of this complex interaction scenario with this actuated exosuit is evaluated during a treadmill walking task, using several indices to quantify the human-robot interaction in terms of muscular activation and fatigue, metabolic expenditure, and kinematic motion patterns. Evidence shows that the HAA biomimetic controller is synergetic with the musculature and performs better concerning the other control strategy. The experimentation demonstrated a metabolic expenditure reduction of 8% of Metabolic Equivalent of Task (MET), effective assistance of the muscular activation of 12.5%, a decrease of the muscular fatigue of 0.6% of the mean frequency, and a significant reduction of the compensatory actions, as discussed in this work. Compensatory effects are present in both assistive configurations, but the HAA modality provides a 47% reduction of compensatory effects when considering muscle activation.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10213774PMC
http://dx.doi.org/10.3389/fnbot.2023.1127694DOI Listing

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