Automatic Versus Manual Tuning of Robot-Assisted Gait Training

C. Bayón; S. S. Fricke; H. van der Kooij; E.H.F. van Asseldonk

doi:10.1007/978-3-030-70316-5_2

Automatic Versus Manual Tuning of Robot-Assisted Gait Training

C. Bayón^*, S. S. Fricke, H. van der Kooij, E.H.F. van Asseldonk

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic › peer-review

1 Citation (Scopus)

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Abstract

Robot-assisted gait training (RAGT) is a promising rehabilitation technique that is increasingly used in the clinic to improve walking ability after a neurological disorder. The effectiveness of RAGT might depend on the customization of the robotic therapy, which in most of the cases is done either manually by the clinical practitioner (MT) or by adaptive controllers developed to automatically adjust the assistance (AT). In this contribution we present a comparison of automatic versus manual tuning of RAGT, where we assessed the differences in the adjustment of the therapy for ten participants with neurological disorders (six stroke, four spinal cord injury). The AT approach reached stable assistance levels quicker than the MT approach. Moreover, the AT ensured a good performance for all subtasks of walking with lower assistance levels than the MT. Future clinical trials need to be performed to show whether these apparent advantages result in better clinical outcomes.

Original language	English
Title of host publication	Converging clinical and engineering research on neurorehabilitation IV
Subtitle of host publication	Proceedings of the 5th International Conference on Neurorehabilitation (ICNR2020), October 13-16, 2020
Editors	Diego Torricelli, Metin Akay, Jose L. Pons
Place of Publication	Cham
Publisher	Springer
Pages	9-14
Number of pages	6
ISBN (Electronic)	978-3-030-70316-5
ISBN (Print)	978-3-030-70315-8
DOIs	https://doi.org/10.1007/978-3-030-70316-5_2
Publication status	Published - 2022

Publication series

Name	Biosystems and Biorobotics
Volume	28
ISSN (Print)	2195-3562
ISSN (Electronic)	2195-3570

Keywords

2022 OA procedure

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/978-3-030-70316-5_2

Bayón2022_Chapter_AutomaticVersusManualTuningOfRFinal published version, 214 KBLicence: Taverne

Cite this

Bayón, C., Fricke, S. S., van der Kooij, H., & van Asseldonk, E. H. F. (2022). Automatic Versus Manual Tuning of Robot-Assisted Gait Training. In D. Torricelli, M. Akay, & J. L. Pons (Eds.), Converging clinical and engineering research on neurorehabilitation IV: Proceedings of the 5th International Conference on Neurorehabilitation (ICNR2020), October 13-16, 2020 (pp. 9-14). (Biosystems and Biorobotics; Vol. 28). Springer. https://doi.org/10.1007/978-3-030-70316-5_2

Bayón, C. ; Fricke, S. S. ; van der Kooij, H. et al. / Automatic Versus Manual Tuning of Robot-Assisted Gait Training. Converging clinical and engineering research on neurorehabilitation IV: Proceedings of the 5th International Conference on Neurorehabilitation (ICNR2020), October 13-16, 2020. editor / Diego Torricelli ; Metin Akay ; Jose L. Pons. Cham : Springer, 2022. pp. 9-14 (Biosystems and Biorobotics).

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title = "Automatic Versus Manual Tuning of Robot-Assisted Gait Training",

abstract = "Robot-assisted gait training (RAGT) is a promising rehabilitation technique that is increasingly used in the clinic to improve walking ability after a neurological disorder. The effectiveness of RAGT might depend on the customization of the robotic therapy, which in most of the cases is done either manually by the clinical practitioner (MT) or by adaptive controllers developed to automatically adjust the assistance (AT). In this contribution we present a comparison of automatic versus manual tuning of RAGT, where we assessed the differences in the adjustment of the therapy for ten participants with neurological disorders (six stroke, four spinal cord injury). The AT approach reached stable assistance levels quicker than the MT approach. Moreover, the AT ensured a good performance for all subtasks of walking with lower assistance levels than the MT. Future clinical trials need to be performed to show whether these apparent advantages result in better clinical outcomes.",

keywords = "2022 OA procedure",

author = "C. Bay{\'o}n and Fricke, {S. S.} and {van der Kooij}, H. and {van Asseldonk}, E.H.F.",

note = "Funding Information: Fig. 2 Assistances (bars) and errors (circles) for all subtasks with respect to the reference pattern in the more impaired leg for one STR and one SCI subjects, in MTconst and ATconst Acknowledgements This work was supported by the Dutch NWO Domain Applied and Engineering Sciences, project number 12850 (AWARD project). Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.",

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doi = "10.1007/978-3-030-70316-5_2",

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Bayón, C, Fricke, SS, van der Kooij, H & van Asseldonk, EHF 2022, Automatic Versus Manual Tuning of Robot-Assisted Gait Training. in D Torricelli, M Akay & JL Pons (eds), Converging clinical and engineering research on neurorehabilitation IV: Proceedings of the 5th International Conference on Neurorehabilitation (ICNR2020), October 13-16, 2020. Biosystems and Biorobotics, vol. 28, Springer, Cham, pp. 9-14. https://doi.org/10.1007/978-3-030-70316-5_2

Automatic Versus Manual Tuning of Robot-Assisted Gait Training. / Bayón, C.; Fricke, S. S.; van der Kooij, H. et al.
Converging clinical and engineering research on neurorehabilitation IV: Proceedings of the 5th International Conference on Neurorehabilitation (ICNR2020), October 13-16, 2020. ed. / Diego Torricelli; Metin Akay; Jose L. Pons. Cham: Springer, 2022. p. 9-14 (Biosystems and Biorobotics; Vol. 28).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic › peer-review

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N1 - Funding Information: Fig. 2 Assistances (bars) and errors (circles) for all subtasks with respect to the reference pattern in the more impaired leg for one STR and one SCI subjects, in MTconst and ATconst Acknowledgements This work was supported by the Dutch NWO Domain Applied and Engineering Sciences, project number 12850 (AWARD project). Publisher Copyright: © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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N2 - Robot-assisted gait training (RAGT) is a promising rehabilitation technique that is increasingly used in the clinic to improve walking ability after a neurological disorder. The effectiveness of RAGT might depend on the customization of the robotic therapy, which in most of the cases is done either manually by the clinical practitioner (MT) or by adaptive controllers developed to automatically adjust the assistance (AT). In this contribution we present a comparison of automatic versus manual tuning of RAGT, where we assessed the differences in the adjustment of the therapy for ten participants with neurological disorders (six stroke, four spinal cord injury). The AT approach reached stable assistance levels quicker than the MT approach. Moreover, the AT ensured a good performance for all subtasks of walking with lower assistance levels than the MT. Future clinical trials need to be performed to show whether these apparent advantages result in better clinical outcomes.

AB - Robot-assisted gait training (RAGT) is a promising rehabilitation technique that is increasingly used in the clinic to improve walking ability after a neurological disorder. The effectiveness of RAGT might depend on the customization of the robotic therapy, which in most of the cases is done either manually by the clinical practitioner (MT) or by adaptive controllers developed to automatically adjust the assistance (AT). In this contribution we present a comparison of automatic versus manual tuning of RAGT, where we assessed the differences in the adjustment of the therapy for ten participants with neurological disorders (six stroke, four spinal cord injury). The AT approach reached stable assistance levels quicker than the MT approach. Moreover, the AT ensured a good performance for all subtasks of walking with lower assistance levels than the MT. Future clinical trials need to be performed to show whether these apparent advantages result in better clinical outcomes.

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Bayón C, Fricke SS, van der Kooij H , van Asseldonk EHF. Automatic Versus Manual Tuning of Robot-Assisted Gait Training. In Torricelli D, Akay M, Pons JL, editors, Converging clinical and engineering research on neurorehabilitation IV: Proceedings of the 5th International Conference on Neurorehabilitation (ICNR2020), October 13-16, 2020. Cham: Springer. 2022. p. 9-14. (Biosystems and Biorobotics). Epub 2021 Oct 2. doi: 10.1007/978-3-030-70316-5_2

Automatic Versus Manual Tuning of Robot-Assisted Gait Training

Abstract

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Keywords

UN SDGs

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