Learning and Identification of human upper-limb muscle synergies in daily-life tasks with autoencoders

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dc.identifier.uri http://dx.doi.org/10.15488/3679
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/3712
dc.contributor.author Hu, Tingli ger
dc.contributor.author Kühn, Johannes ger
dc.contributor.author Matouq, Jumana ger
dc.contributor.author Haddadin, Sami ger
dc.date.accessioned 2018-09-04T12:31:22Z
dc.date.available 2018-09-04T12:31:22Z
dc.date.issued 2018-05-16
dc.identifier.citation Hu, T.; Kühn, J.; Matouq, J.; Haddadin, S.: Learning and Identification of human upper-limb muscle synergies in daily-life tasks with autoencoders. OTWorld Congress 2018, 6 S. ger
dc.description.abstract As a pilot study, we present 1)a database that includes 30 daily-life table-top tasks, which were selected within the SoftPro project, and 2)a novel autoencoder-based muscle synergy identification method, whose results indicate an association between synergy space dimensionality and task complexity. ger
dc.description.sponsorship European Commission/H2020/688857 SoftPro/EU ger
dc.language.iso eng ger
dc.publisher Hannover : Institutionelles Repositorium der Leibniz Universität Hannover
dc.relation info:eu-repo/grantAgreement/European Commission/H2020/688857 SoftPro/EU ger
dc.rights Es gilt deutsches Urheberrecht. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden. ger
dc.subject upper limb muscle synergies eng
dc.subject autoencoders eng
dc.subject machine learning eng
dc.subject.ddc 620 | Ingenieurwissenschaften und Maschinenbau ger
dc.subject.ddc 610 | Medizin, Gesundheit ger
dc.title Learning and Identification of human upper-limb muscle synergies in daily-life tasks with autoencoders ger
dc.type conferenceObject ger
dc.type Text ger
dc.description.version publishedVersion ger
tib.accessRights frei zug�nglich ger


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