Abstract
Coordinated control of the trunk and pelvis is critical for performing functional upper-body movements, particularly during standing. Deficits in trunk–pelvis coordination are common in populations with neurological or musculoskeletal impairments, contributing to poor balance and limited functional mobility. In this proof-of-concept study, we investigated training strategies in healthy participants to establish a baseline for future rehabilitation applications. Twenty-four individuals were assigned to one of three groups: (i) control, without assistance (Ctrl), (ii) robotic assistance at the trunk, specifically at the thorax (T), and (iii) robotic assistance applied concurrently at the thorax and pelvis (T-P). Training was delivered using the Robotic Upright Stand Trainer (RobUST), which provides assist-as-needed forces based on deviations from target trajectories and normative thorax–pelvis coordination patterns. Participants were trained to perform elliptical thorax movements while standing, a task with progressively increasing postural demands. Results showed that T-P assistance enabled participants to achieve larger ellipse sizes during training compared to T assistance, suggesting that pelvic support facilitated greater exploration of range of motion. Post-training, ellipse tracing accuracy improved in all groups, but only the T-P and Ctrl groups demonstrated significant gains in movement smoothness. Learning-curve analysis further revealed that while T-P participants required a longer acclimatization period, they ultimately achieved higher combined learning metrics than the T group. These findings highlight the potential of trunk–pelvis coordinated assistance to promote greater improvements in postural control than assistance limited to the trunk. The results provide a foundation for developing trunk–pelvis interventions aimed at improving postural control in clinical populations.
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Omofuma, I., Fagioli, I., & Agrawal, S. (2026). Postural Control Training With Forces Applied on the Trunk and Pelvis Using a Robotic Upright Stand Trainer (RobUST). IEEE Transactions on Neural Systems and Rehabilitation Engineering, 34, 355–365. https://doi.org/10.1109/TNSRE.2025.3647591
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