Assessment and Benchmarking of XoNLI: a Natural Language Processing Interface for Industrial Exoskeletons

Industrial exoskeletons are a potential solution for reducing work-related musculoskeletal disorders during carrying or lifting tasks. Having sensors, electrical/pneumatic actuators, and control systems, active exoskeletons present a more versatile control system because it is possible to select different assistive strategies based on the performed task. From this perspective, human-machine interaction is required to safely open basic exoskeleton domains to the user and provide an adaptable setup system. This article presents the assessment and benchmarking of the novel XoLab Natural Language Interface, a voice user interface for interaction and configuration of industrial active exoskeletons. The evaluation of the novel interface was performed by 17 participants who completed the setup and operational activities while wearing the XoTrunk exoskeleton. The benchmark consisted of a comparison of the presented device with previous adaptable interfaces for the exoskeleton: the user command interface and the monitor system interface. The results showed that although the novel interface demonstrated a considerable lag in the time response, it was more attractive, stimulating and novel than the standard one. However, the standard interface obtained favourable results over the user command interface and the voice interface perspicuity and efficiency.