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Promoting active participation in robot-aided rehabilitation via machine learning and impedance control

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dc.contributor.authorTamantini, Christian
dc.contributor.authorLanglois, Kevin Patrice
dc.contributor.authorde Winter, Joris
dc.contributor.authorMohamadi, Parham Haji Ali
dc.contributor.authorBeckwee, David
dc.contributor.authorSwinnen, Eva
dc.contributor.authorVerstraten, Tom
dc.contributor.authorVanderborght, Bram
dc.contributor.authorZollo, Loredana
dc.contributor.imecauthorLanglois, Kevin Patrice
dc.contributor.imecauthorMohamadi, Parham Haji Ali
dc.contributor.imecauthorVanderborght, Bram
dc.contributor.orcidimecVanderborght, Bram::0000-0003-4881-9341
dc.date.accessioned2025-03-14T18:11:35Z
dc.date.available2025-03-14T18:11:35Z
dc.date.issued2025-FEB 21
dc.description.wosFundingTextThe author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported partly by the Flemish Government under the program Onderzoeksprogramma Artificiele Intelligentie (AI) Vlaanderen, partly by the strategic basic research project RevalExo (grant no. S001024N) funded by the Research Foundation - Flanders (FWO), partly by the Italian Institute for Labour Accidents (INAIL) with the SPINE 4.0 project (CUP: C85F21001020001), and partly by the Italian Ministry of Research, under the complementary actions to the NRRP "Fit4MedRob -Fit for Medical Robotics" Grant PNC0000007, (CUP: B53C22006990001). KP is supported by a personal grant from the FWO, grant number 1258523N.
dc.identifier.doi10.3389/fdgth.2025.1559796
dc.identifier.pmidMEDLINE:40060032
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/45400
dc.publisherFRONTIERS MEDIA SA
dc.source.journalFRONTIERS IN DIGITAL HEALTH
dc.source.numberofpages12
dc.source.volume7
dc.title

Promoting active participation in robot-aided rehabilitation via machine learning and impedance control

dc.typeJournal article
dspace.entity.typePublication
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