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bioRxiv · 10.1101/2023.03.14.532662

Human-exoskeleton interaction force estimation in Indego exoskeleton

Shushtari, M.·Arami, A.
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Abstract

Accurate interaction force estimation can play an important role in optimization human-robot interaction in exoskeleton. In this work, we propose a novel approach for system identification of exoskeleton dynamics in presence of interaction forces as a whole multi-body system regardless of gait phase or any assumption on human-exoskeleton interaction. We hanged the exoskeleton through a linear spring and excited the exoskeleton joints with chirp commands while measuring the exoskeleton-environment interaction force. Several structures of neural networks have been trained to model the exoskeleton passive dynamics and estimate the interaction force. Our testing results indicated that a deep neural network with 250 neurons and 10 time delays can obtain sufficiently accurate estimation of the interaction force, resulting in 1.23 of RMSE on Z-normalized applied torques and 0.89 of adjusted R2.

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Shushtari, M., Arami, A.. 2023-03-15. Human-exoskeleton interaction force estimation in Indego exoskeleton. https://doi.org/10.1101/2023.03.14.532662

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