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

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 consumption, user comfort, and exoskeleton performance scores) and comparing it to a standard commercial exoskeleton control system (default mode). A cross-over design with randomized allocation in Thai healthy and independently walking adults ensured participants experienced both modes. All participants were assigned into two groups to receive an alternate sequence of walking with the intelligent mode or the default mode of the lower-limb exoskeleton Exo-H3 at high and normal speed. From eight participants, the intelligent mode-driven exoskeleton (adaptive exoskeleton) showed a significantly lower velocity, stride, and step lengths than the default mode-driven exoskeleton (non-adaptive exoskeleton). This setup significantly increased anterior pelvic tilt during mid-swing at normal speed (3.69 ± 1.77 degrees, p = 0.001) and high speed (2.52 ± 1.69 degrees, p = 0.004), hip flexion during stance phase with ankle dorsiflexion, and used less oxygen consumption at high speed (-2.03 ± 2.07 ml/kg/min) when compared to the default one. No significant differences of muscle activity, user comfort and exoskeleton performance scores between the two modes. Further exoskeletal modification in terms of hardware and control is still needed to improve the temporal spatial, kinematics, user comfort, and exoskeleton performance.