Publication:

Comparison of state-of-the-art deep learning architectures for detection of freezing of gait in Parkinson's disease

Date

2023
Journal article
https://doi.org/10.3389/fneur.2023.1306129
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dc.contributor.authorKlaver, Emilie Charlotte
dc.contributor.authorHeijink, Irene B.
dc.contributor.authorSilvestri, Gianluigi
dc.contributor.authorvan Vugt, Jeroen P. P.
dc.contributor.authorJanssen, Sabine
dc.contributor.authorNonnekes, Jorik
dc.contributor.authorvan Wezel, Richard J. A.
dc.contributor.authorTjepkema-Cloostermans, Marleen C.
dc.contributor.imecauthorSilvestri, Gianluigi
dc.contributor.orcidimecSilvestri, Gianluigi::0000-0001-5121-0161
dc.date.accessioned2024-04-04T11:30:28Z
dc.date.available2024-01-13T17:48:02Z
dc.date.available2024-04-04T11:30:28Z
dc.date.embargo2023-12-21
dc.date.issued2023
dc.description.wosFundingTextThe author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the Michael J. Fox Foundation (Legacy ID 16457), by OnePlanet research center with funding from the Province of Gelderland, and by the "Nederlandse Organisatie voor Wetenschappelijk Onderzoek-Toegepaste en Technische wetenschappen" (NWO-TTW) Crossover program under the Innovative NeuroTechnology for Society (INTENSE) project (ID 17619). The Center of Expertise for Parkinson & Movement Disorders was supported by a center of excellence grant from the Parkinson Foundation.
dc.identifier.doi10.3389/fneur.2023.1306129
dc.identifier.issn1664-2295
dc.identifier.pmidMEDLINE:38178885
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/43413
dc.publisherFRONTIERS MEDIA SA
dc.source.beginpageArt. 1306129
dc.source.endpageN/A
dc.source.issueN/A
dc.source.journalFRONTIERS IN NEUROLOGY
dc.source.numberofpages10
dc.source.volume14
dc.title

Comparison of state-of-the-art deep learning architectures for detection of freezing of gait in Parkinson's disease

dc.typeJournal article
dspace.entity.typePublication
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