Show simple item record

dc.contributor.authorUrra, Oiane
dc.contributor.authorCasals Gelpi, Alicia
dc.contributor.authorJané Campos, Raimon
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.contributor.otherInstitut de Bioenginyeria de Catalunya
dc.date.accessioned2015-06-03T11:19:32Z
dc.date.available2015-06-03T11:19:32Z
dc.date.created2014
dc.date.issued2014
dc.identifier.citationUrra, O.; Casals, A.; Jane, R. Synergy analysis as a tool to design and assess an effective stroke rehabilitation. A: IEEE Engineering in Medicine and Biology Society. "2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)". Chicago: Institute of Electrical and Electronics Engineers (IEEE), 2014, p. 3550-3553.
dc.identifier.isbn978-1-4244-7929-0/14
dc.identifier.urihttp://hdl.handle.net/2117/28165
dc.description.abstractThe poor rehabilitation success rate, including the cases of ineffective and detrimental adaptations, make stroke a leading cause of disability. Thus, it is essential to recognize the mechanisms driving healthy motor recovery to improve such rate. Stroke alters the Synergy Architecture (SA), the modular muscle control system. So SA analysis may constitute a powerful tool to design and assess rehabilitation procedures. However, current impairment scales do not consider the patient’s neuromuscular state. To gain insights into this hypothesis, we recorded multiple myoelectric signals from upper-limb muscles, in healthy subjects, while executing a set of common rehabilitation exercises. We found that SA reveals optimized motor control strategies and the positive effects of the use of visual feedback (VF) on motor control. Furthermore we demonstrate that the right and left arm’s SA share the basic structure within the same subject, so we propose using the unaffected limb’s SA as a reference motion pattern to be reached through rehabilitation.
dc.format.extent4 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica
dc.subject.lcshCerebrovascular disease -- Patients -- Rehabilitation
dc.subject.otherBars
dc.subject.otherElectromyography
dc.subject.otherMotor drives
dc.subject.otherNeuromuscular
dc.subject.otherVectors
dc.subject.otherVisualization
dc.titleSynergy analysis as a tool to design and assess an effective stroke rehabilitation
dc.typeConference lecture
dc.subject.lemacMalalties cerebrovasculars -- Pacients -- Rehabilitació
dc.contributor.groupUniversitat Politècnica de Catalunya. GRINS - Grup de Recerca en Robòtica Intel·ligent i Sistemes
dc.contributor.groupUniversitat Politècnica de Catalunya. BIOSPIN - Biomedical Signal Processing and Interpretation
dc.identifier.doi10.1109/EMBC.2014.6944389
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6944389
dc.rights.accessOpen Access
drac.iddocument15592245
dc.description.versionPostprint (author’s final draft)
upcommons.citation.authorUrra, O.; Casals, A.; Jane, R.
upcommons.citation.contributorIEEE Engineering in Medicine and Biology Society
upcommons.citation.pubplaceChicago
upcommons.citation.publishedtrue
upcommons.citation.publicationName2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
upcommons.citation.startingPage3550
upcommons.citation.endingPage3553


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder