Can Momentum-Based Control Predict Human Balance Recovery Strategies?

C. Bayon, A.R. Emmens, M. Afschrift, T. Van Wouwe, A.Q.L. Keemink, H. Van Der Kooij, E.H.F. Van Asseldonk

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

© 2001-2011 IEEE.Human-like balance controllers are desired for wearable exoskeletons in order to enhance human-robot interaction. Momentum-based controllers (MBC) have been successfully applied in bipeds, however, it is unknown to what degree they are able to mimic human balance responses. In this paper, we investigated the ability of an MBC to generate human-like balance recovery strategies during stance, and compared the results to those obtained with a linear full-state feedback (FSF) law. We used experimental data consisting of balance recovery responses of nine healthy subjects to anteroposterior platform translations of three different amplitudes. The MBC was not able to mimic the combination of trunk, thigh and shank angle trajectories that humans generated to recover from a perturbation. Compared to the FSF, the MBC was better at tracking thigh angles and worse at tracking trunk angles, whereas both controllers performed similarly in tracking shank angles. Although the MBC predicted stable balance responses, the human-likeness of the simulated responses generally decreased with an increased perturbation magnitude. Specifically, the shifts from ankle to hip strategy generated by the MBC were not similar to the ones observed in the human data. Although the MBC was not superior to the FSF in predicting human-like balance, we consider the MBC to be more suitable for implementation in exoskeletons, because of its ability to handle constraints (e.g. ankle torque limits). Additionally, more research into the control of angular momentum and the implementation of constraints could eventually result in the generation of more human-like balance recovery strategies by the MBC.
Original languageEnglish
Article number9127521
Pages (from-to)2015-2024
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume28
Issue number9
DOIs
Publication statusPublished - 1 Sept 2020
Externally publishedYes

Funding

Manuscript received January 29, 2020; revised April 29, 2020 and June 8, 2020; accepted June 24, 2020. Date of publication June 29, 2020; date of current version September 7, 2020. This work was supported in part by the Dutch Research Council (NWO) through the research program Wearable Robotics under Project P16-05, in part by the EU Research Program FP7-ICT-2013-10 through the SYMBITRON project under Contract 611626, and in part by COST (European Cooperation in Science and Technology) Action CA16116. (C. Bayón and A. R. Emmens are co-first authors.) (Corresponding author: C. Bayón.) C. Bayón, A. R. Emmens, A. Q. L. Keemink, and E. H. F. van Asseldonk are with the Department of Biomechanical Engineering, University of Twente, 7500 AE Enschede, The Netherlands (e-mail: c.bayoncalderon@utwente.nl).

FundersFunder number
Dutch Research Council
EU Research Program FP7-ICT-2013-10611626
European Cooperation in Science and TechnologyCA16116
Nederlandse Organisatie voor Wetenschappelijk OnderzoekP16-05

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