Comprehensive multi-metric analysis of user experience and performance in adaptive and non-adaptive lower-limb exoskeletons.

ABSTRACT: Among control methods for robotic exoskeletons, biologically inspired control based on central pattern generators (CPGs) offer a promising approach to generate natural and robust walking patterns. Compared to other approaches, like model-based and machine learning-based control, the biologically inspired control provides robustness to perturbations, requires less computational power, and does not need system models or large learning datasets. While it has shown effectiveness, a comprehensive evaluation of its user experience is lacking. Thus, this study addressed this gap by investigating the performance of a state-of-the-art adaptive CPG-based exoskeleton control system (intelligent mode) under a multi-metric analysis (involving three-dimensional gait analysis, muscle activity, oxygen con

SUBMITTER: Supapitanon K 

PROVIDER: S-EPMC11717227 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature