dc.identifier.uri |
http://dx.doi.org/10.15488/3679 |
|
dc.identifier.uri |
https://www.repo.uni-hannover.de/handle/123456789/3712 |
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dc.contributor.author |
Hu, Tingli
|
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dc.contributor.author |
Kühn, Johannes
|
ger |
dc.contributor.author |
Matouq, Jumana
|
ger |
dc.contributor.author |
Haddadin, Sami
|
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dc.date.accessioned |
2018-09-04T12:31:22Z |
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dc.date.available |
2018-09-04T12:31:22Z |
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dc.date.issued |
2018-05-16 |
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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. |
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dc.description.sponsorship |
European Commission/H2020/688857 SoftPro/EU |
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dc.language.iso |
eng |
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dc.publisher |
Hannover : Institutionelles Repositorium der Leibniz Universität Hannover |
|
dc.relation |
info:eu-repo/grantAgreement/European Commission/H2020/688857 SoftPro/EU |
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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
|
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dc.subject.ddc |
610 | Medizin, Gesundheit
|
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dc.title |
Learning and Identification of human upper-limb muscle synergies in daily-life tasks with autoencoders |
eng |
dc.type |
ConferenceObject |
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dc.type |
Text |
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dcterms.extent |
6 S. |
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dc.description.version |
publishedVersion |
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tib.accessRights |
frei zug�nglich |
ger |