Abstract
Robotic gait training is a promising tool to improve walking ability after neurological disorders. Despite its benefits, its therapeutic effects might depend on the customization of the robotic training to the patient’s capabilities. In the last years, various approaches focused on the assist-as-needed (AAN) paradigm, have been proposed to improve the effectiveness of robotic rehabilitation. However, in most of these cases the amount of robotic assistance is chosen by a therapist, and therefore, subjective decisions could affect the adaptation of the therapy to the patient’s needs. This contribution presents the implementation of a novel performance-based adaptive controller, which automatically adjusts robotic assistance for diverse subtasks of gait based on the user’s performance during training. A pilot study testing this controller in one stroke survivor, shows the potential of the proposed tool to be included in future robot-based gait training protocols.
S. S. Fricke and C. Bayón—These authors contributed equally to the presented work. First author is shared between S. S. Fricke and C. Bayón.
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Acknowledgment
The work presented has been carried out with the financial support from the Ministry of Economy and Competitiveness of Spain, under contract EEBB-17-12035, and the Dutch NWO Domain Applied Engineering Sciences, project number 12850 (AWARD project).
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Fricke, S.S., Bayón, C., Rocon, E., van der Kooij, H., van Asseldonk, E.H.F. (2019). Pilot Study of a Performance-Based Adaptive Assistance Controller for Stroke Survivors. In: Masia, L., Micera, S., Akay, M., Pons, J. (eds) Converging Clinical and Engineering Research on Neurorehabilitation III. ICNR 2018. Biosystems & Biorobotics, vol 21. Springer, Cham. https://doi.org/10.1007/978-3-030-01845-0_61
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DOI: https://doi.org/10.1007/978-3-030-01845-0_61
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