Neglected physical human-robot interaction may explain variable outcomes in gait neurorehabilitation research
M.C. Plooij (Motek, Demcon Advanced Mechatronics, TU Delft - Biomechatronics & Human-Machine Control)
Salil Apte (École Polytechnique Fédérale de Lausanne, TU Delft - Biomechatronics & Human-Machine Control)
U. Keller (University Children’s Hospital Zurich, École Polytechnique Fédérale de Lausanne)
Patricia M. Baines (TU Delft - Biomechatronics & Human-Machine Control)
Bram T. Sterke (Motek, Erasmus MC)
L. Asboth (École Polytechnique Fédérale de Lausanne, University Hospital of Vaud (CHUV))
Grégoire Courtine (École Polytechnique Fédérale de Lausanne, University Hospital of Vaud (CHUV))
Joachim Von Zitzewitz (École Polytechnique Fédérale de Lausanne)
Heike Vallery (TU Delft - Biomechatronics & Human-Machine Control, Erasmus MC)
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Abstract
During gait neurorehabilitation, many factors influence the quality of gait patterns, particularly the chosen body-weight support (BWS) device. Consequently, robotic BWS devices play a key role in gait rehabilitation of people with neurological disorders. The device transparency, support force vector direction, and attachment to the harness vary widely across existing robotic BWS devices, but the influence of these factors on the production of gait remains unknown. Because this information is key to designing an optimal BWS, we systematically studied these determinants in this work. We report that with a highly transparent device and a conventional harness, healthy participants select a small backward force when asked for optimal BWS conditions. This unexpected finding challenges the view that during human-robot interactions, humans predominantly optimize energy efficiency. Instead, they might seek to increase their feeling of stability and safety. We also demonstrate that the location of the attachment points on the harness strongly affects gait patterns, yet harness attachment is hardly reported in literature. Our results establish principles for the design of BWS devices and personalization of BWS settings for gait neurorehabilitation.
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