Development of a neural efficiency metric to assess human-exoskeleton adaptations - Mehta, Ranjana K.; Zhu, Yibo; Weston, Eric B.; Marras, William S. (Frontiers in Robotics and AI, 2025)
Passive exoskeletons have been introduced to alleviate loading on the lumbar spine while increasing the wearer’s productivity. However, few studies have examined the neurocognitive effects of short-term human-exoskeleton adaptation. The objective of the study was to develop a novel neural efficiency metric to assess short-term human exoskeleton adaptation during repetitive lifting. Twelve participants (gender-balanced) performed simulated asymmetric lifting tasks for a short duration (phase: early, middle, late) with and without a passive low back exoskeleton on two separate days. Phase, exoskeleton condition, and their interaction effects on biomechanical parameters, neural activation, and the novel neural efficiency metric were examined. Peak L5/S1 superior lateral shear forces were found to be significantly lower in the exoskeleton condition than in the control condition. However, other biomechanical and neural activation measures were comparable between conditions. The temporal change of the neural efficiency metric was found to follow the motor adaptation process. Compared to the control condition, participants exhibited lower efficiency during the exoskeleton-assisted lifting condition over time. The neural efficiency metric was capable of tracking the short-term task adaptation process during a highly ambulatory exoskeleton-assisted manual handling task. The exoskeleton-assisted task was less efficient and demanded a longer adaptation period than the control condition, which may impact exoskeleton acceptance and/or intent to use.