Physiological Measures of the Mental Workload in Users of a Lower Limb Exosuit: A Comparison of Subjective and Objective Metrics

Lower-limb exosuits are particularly relevant for individuals with some degree of mobility impairment, such as post-stroke patients or older adults with reduced movement capabilities. This study aims to investigate the mental workload (MWL) assessment of XoSoft, a lower-limb soft exoskeleton, using and comparing subjective and objective physiological metrics. The NASA-TLX questionnaire, the average percentage change in pupil size (APCPS), and the Baevsky stress index (SI) are compared. The experiments were conducted on 18 healthy subjects while walking and involved mathematical tasks to create a double-task condition. The results show a complex interaction between task difficulty, exoskeleton activation, and pupillary dynamics, suggesting that the subject might reach a saturated condition under a high mental load. Besides, the data indicate that pupil diameter may be an objective mental workload indicator that correlates with subjective NASA-TLX questionnaires. The discordant indications from the stress index suggest how different metrics of the ocular and cardiac levels respond differently to various stimuli and dynamics. Research has also revealed ocular asymmetry, with the right eye more sensitive to cognitive load.

Impact of a Lower Limb Exosuit Anchor Points on Energetics and Biomechanics

Anchor point placement is a crucial yet often overlooked aspect of exosuit design since it determines how forces interact with the human body. This work analyzes the impact of different anchor point positions on gait kinematics, muscular activation and energetic consumption. A total of six experiments were conducted with 11 subjects wearing the XoSoft exosuit, which assists hip flexion in five configurations. Subjects were instrumented with an IMU-based motion tracking system, EMG sensors, and a mask to measure metabolic consumption. The results show that positioning the knee anchor point on the posterior side while keeping the hip anchor on the anterior part can reduce muscle activation in the hip flexors by up to 10.21\% and metabolic expenditure by up to 18.45\%. Even if the only assisted joint was the hip, all the configurations introduced changes also in the knee and ankle kinematics. Overall, no single configuration was optimal across all subjects, suggesting that a personalized approach is necessary to transmit the assistance forces optimally. These findings emphasize that anchor point position does indeed have a significant impact on exoskeleton effectiveness and efficiency. However, these optimal positions are subject-specific to the exosuit design, and there is a strong need for future work to tailor musculoskeletal models to individual characteristics and validate these results in clinical populations.

Robust Path Planning via Learning from Demonstrations for Robotic Catheters in Deformable Environments

Navigation through tortuous and deformable vessels using catheters with limited steering capability underscores the need for reliable path planning. State-of-the-art path planners do not fully account for the deformable nature of the environment. This work proposes a robust path planner via a learning from demonstrations method, named Curriculum Generative Adversarial Imitation Learning (C-GAIL). This path planning framework takes into account the interaction between steerable catheters and vessel walls and the deformable property of vessels. In-silico comparative experiments show that the proposed network achieves smaller targeting errors, and a higher success rate, compared to a state-of-the-art approach based on GAIL. The in-vitro validation experiments demonstrate that the path generated by the proposed C-GAIL path planner aligns better with the actual steering capability of the pneumatic artificial muscle-driven catheter utilized in this study. Therefore, the proposed approach can provide enhanced support to the user in navigating the catheter towards the target with greater precision, in contrast to the conventional centerline-following technique. The targeting and tracking errors are 1.26$\pm$0.55mm and 5.18$\pm$3.48mm, respectively. The proposed path planning framework exhibits superior performance in managing uncertainty associated with vessel deformation, thereby resulting in lower tracking errors.