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dc.contributorDepartment of Biomedical Engineeringen_US
dc.contributorUniversity Research Facility in Behavioral and Systems Neuroscienceen_US
dc.contributorMainland Development Officeen_US
dc.contributorDepartment of Biomedical Engineering-
dc.contributorUniversity Research Facility in Behavioral and Systems Neuroscience-
dc.contributorMainland Development Office-
dc.contributorResearch Institute for Smart Ageing-
dc.creatorGuo, Zen_US
dc.creatorZhou, Sen_US
dc.creatorJi, Ken_US
dc.creatorZhuang, Yen_US
dc.creatorSong, Jen_US
dc.creatorNam, Cen_US
dc.creatorHu, Xen_US
dc.creatorZheng, Yen_US
dc.date.accessioned2022-09-13T03:36:56Z-
dc.date.available2022-09-13T03:36:56Z-
dc.identifier.issn1741-2560en_US
dc.identifier.urihttp://hdl.handle.net/10397/95051-
dc.language.isoenen_US
dc.publisherInstitute of Physics Publishingen_US
dc.rights© 2022 The Author(s). Published by IOP Publishing Ltden_US
dc.rightsOriginal content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence (https://creativecommons.org/licenses/by/4.0/). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.en_US
dc.rightsThe following publication Guo, Z., Zhou, S., Ji, K., Zhuang, Y., Song, J., Nam, C., ... & Zheng, Y. (2022). Corticomuscular integrated representation of voluntary motor effort in robotic control for wrist-hand rehabilitation after stroke. Journal of Neural Engineering, 19(2), 026004 is available at https://doi.org/10.1088/1741-2552/ac5757.en_US
dc.subjectCorticomuscular coherenceen_US
dc.subjectHand functionsen_US
dc.subjectRobotic controlen_US
dc.subjectStroke rehabilitationen_US
dc.subjectVoluntary motor efforten_US
dc.titleCorticomuscular integrated representation of voluntary motor effort in robotic control for wrist-hand rehabilitation after strokeen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume19en_US
dc.identifier.issue2en_US
dc.identifier.doi10.1088/1741-2552/ac5757en_US
dcterms.abstractObjective. The central-to-peripheral voluntary motor effort (VME) in the affected limb is a dominant force for driving the functional neuroplasticity on motor restoration post-stroke. However, current rehabilitation robots isolated the central and peripheral involvements in the control design, resulting in limited rehabilitation effectiveness. This study was to design a corticomuscular coherence (CMC) and electromyography (EMG)-driven control to integrate the central and peripheral VMEs in neuromuscular systems in stroke survivors.en_US
dcterms.abstractApproach. The CMC-EMG-driven control was developed in a neuromuscular electrical stimulation (NMES)-robot system, i.e. CMC-EMG-driven NMES-robot system, to instruct and assist the wrist-hand extension and flexion in persons after stroke. A pilot single-group trial of 20 training sessions was conducted with the developed system to assess the feasibility for wrist-hand practice on the chronic strokes (16 subjects). The rehabilitation effectiveness was evaluated through clinical assessments, CMC, and EMG activation levels.en_US
dcterms.abstractMain results. The trigger success rate and laterality index of CMC were significantly increased in wrist-hand extension across training sessions (p < 0.05). After the training, significant improvements in the target wrist-hand joints and suppressed compensation from the proximal shoulder-elbow joints were observed through the clinical scores and EMG activation levels (p < 0.05). The central-to-peripheral VME distribution across upper extremity (UE) muscles was also significantly improved, as revealed by the CMC values (p < 0.05). Significance. Precise wrist-hand rehabilitation was achieved by the developed system, presenting suppressed cortical and muscular compensation from the contralesional hemisphere and the proximal UE, and improved distribution of the central-and-peripheral VME on UE muscles.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationJournal of neural engineering, Apr. 2022, v. 19, no. 2, 26004en_US
dcterms.isPartOfJournal of neural engineeringen_US
dcterms.issued2022-04-
dc.identifier.scopus2-s2.0-85126072286-
dc.identifier.pmid35193124-
dc.identifier.ros2021003272-
dc.identifier.eissn1741-2552en_US
dc.identifier.artn26004en_US
dc.description.validate202209 bchyen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberCDCF_2021-2022-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextthe National Natural Science Foundation of China; the Science and Technology Innovation Committee of Shenzhen, Chinaen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS68822835-
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