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Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-19668
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dc.contributor.authorJust, Fabian-
dc.contributor.authorÖzen, Özhan-
dc.contributor.authorTortora, Stefano-
dc.contributor.authorKlamroth-Marganska, Verena-
dc.contributor.authorRiener, Robert-
dc.contributor.authorRauter, Georg-
dc.date.accessioned2020-03-05T15:07:01Z-
dc.date.available2020-03-05T15:07:01Z-
dc.date.issued2020-
dc.identifier.issn1743-0003de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/19668-
dc.description.abstractBackground Arm weight compensation with rehabilitation robots for stroke patients has been successfully used to increase the active range of motion and reduce the effects of pathological muscle synergies. However, the differences in structure, performance, and control algorithms among the existing robotic platforms make it hard to effectively assess and compare human arm weight relief. In this paper, we introduce criteria for ideal arm weight compensation, and furthermore, we propose and analyze three distinct arm weight compensation methods (Average, Full, Equilibrium) in the arm rehabilitation exoskeleton ’ARMin’. The effect of the best performing method was validated in chronic stroke subjects to increase the active range of motion in three dimensional space. Methods All three methods are based on arm models that are generalizable for use in different robotic devices and allow individualized adaptation to the subject by model parameters. The first method Average uses anthropometric tables to determine subject-specific parameters. The parameters for the second method Full are estimated based on force sensor data in predefined resting poses. The third method Equilibrium estimates parameters by optimizing an equilibrium of force/torque equations in a predefined resting pose. The parameters for all three methods were first determined and optimized for temporal and spatial estimation sensitivity. Then, the three methods were compared in a randomized single-center study with respect to the remaining electromyography (EMG) activity of 31 healthy participants who performed five arm poses covering the full range of motion with the exoskeleton robot. The best method was chosen for feasibility tests with three stroke patients. In detail, the influence of arm weight compensation on the three dimensional workspace was assessed by measuring of the horizontal workspace at three different height levels in stroke patients. Results All three arm weight compensation methods reduced the mean EMG activity of healthy subjects to at least 49% compared with the no compensation reference. The Equilibrium method outperformed the Average and the Full methods with a highly significant reduction in mean EMG activity by 19% and 28% respectively. However, upon direct comparison, each method has its own individual advantages such as in set-up time, cost, or required technology. The horizontal workspace assessment in poststroke patients with the Equilibrium method revealed potential workspace size-dependence of arm height, while weight compensation helped maximize the workspace as much as possible. Conclusion Different arm weight compensation methods were developed according to initially defined criteria. The methods were then analyzed with respect to their sensitivity and required technology. In general, weight compensation performance improved with the level of technology, but increased cost and calibration efforts. This study reports a systematic way to analyze the efficacy of different weight compensation methods using EMG. Additionally, the feasibility of the best method, Equilibrium, was shown by testing with three stroke patients. In this test, a height dependence of the workspace size also seemed to be present, which further highlights the importance of patient-specific weight compensation, particularly for training at different arm heights.de_CH
dc.language.isoende_CH
dc.publisherBioMed Centralde_CH
dc.relation.ispartofJournal of NeuroEngineering and Rehabilitationde_CH
dc.rightshttp://creativecommons.org/licenses/by/4.0/de_CH
dc.subjectArm Weight Compensationde_CH
dc.subjectEMGde_CH
dc.subjectRehabilitation Roboticsde_CH
dc.subjectStrokede_CH
dc.subjectWorkspace Assessmentde_CH
dc.subject.ddc615.8515: Ergotherapiede_CH
dc.subject.ddc616.8: Neurologie und Krankheiten des Nervensystemsde_CH
dc.titleHuman arm weight compensation in rehabilitation robotics : efficacy of three distinct methodsde_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementGesundheitde_CH
zhaw.organisationalunitInstitut für Ergotherapie (IER)de_CH
dc.identifier.doi10.1186/s12984-020-0644-3de_CH
dc.identifier.doi10.21256/zhaw-19668-
dc.identifier.pmid32024528de_CH
zhaw.funding.euNode_CH
zhaw.issue1de_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.start13de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume17de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.webfeedErgoTransde_CH
zhaw.author.additionalNode_CH
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Just, F., Özen, Ö., Tortora, S., Klamroth-Marganska, V., Riener, R., & Rauter, G. (2020). Human arm weight compensation in rehabilitation robotics : efficacy of three distinct methods. Journal of NeuroEngineering and Rehabilitation, 17(1), 13. https://doi.org/10.1186/s12984-020-0644-3
Just, F. et al. (2020) ‘Human arm weight compensation in rehabilitation robotics : efficacy of three distinct methods’, Journal of NeuroEngineering and Rehabilitation, 17(1), p. 13. Available at: https://doi.org/10.1186/s12984-020-0644-3.
F. Just, Ö. Özen, S. Tortora, V. Klamroth-Marganska, R. Riener, and G. Rauter, “Human arm weight compensation in rehabilitation robotics : efficacy of three distinct methods,” Journal of NeuroEngineering and Rehabilitation, vol. 17, no. 1, p. 13, 2020, doi: 10.1186/s12984-020-0644-3.
JUST, Fabian, Özhan ÖZEN, Stefano TORTORA, Verena KLAMROTH-MARGANSKA, Robert RIENER und Georg RAUTER, 2020. Human arm weight compensation in rehabilitation robotics : efficacy of three distinct methods. Journal of NeuroEngineering and Rehabilitation. 2020. Bd. 17, Nr. 1, S. 13. DOI 10.1186/s12984-020-0644-3
Just, Fabian, Özhan Özen, Stefano Tortora, Verena Klamroth-Marganska, Robert Riener, and Georg Rauter. 2020. “Human Arm Weight Compensation in Rehabilitation Robotics : Efficacy of Three Distinct Methods.” Journal of NeuroEngineering and Rehabilitation 17 (1): 13. https://doi.org/10.1186/s12984-020-0644-3.
Just, Fabian, et al. “Human Arm Weight Compensation in Rehabilitation Robotics : Efficacy of Three Distinct Methods.” Journal of NeuroEngineering and Rehabilitation, vol. 17, no. 1, 2020, p. 13, https://doi.org/10.1186/s12984-020-0644-3.


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