Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/32615
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dc.contributor.authorFiltjens, Benjamin-
dc.contributor.authorNieuwboer, Alice-
dc.contributor.authorD'cruz, Nicholas-
dc.contributor.authorSPILDOOREN, Joke-
dc.contributor.authorSLAETS, Leen-
dc.contributor.authorVANRUMSTE, Bart-
dc.date.accessioned2020-11-16T15:01:55Z-
dc.date.available2020-11-16T15:01:55Z-
dc.date.issued2020-
dc.date.submitted2020-09-09T13:26:13Z-
dc.identifier.citationGAIT & POSTURE, 80 , p. 130 -136-
dc.identifier.urihttp://hdl.handle.net/1942/32615-
dc.description.abstractBackground: Manual annotation of initial contact (IC) and end contact (EC) is a time consuming process. There are currently no robust techniques available to automate this process for Parkinson's disease (PD) patients with freezing of gait (FOG). Objective: To determine the validity of a data-driven approach for automated gait event detection. Methods: 15 freezers were asked to complete several straight-line and 360 degree turning trials in a 3D gait laboratory during the off-period of their medication cycle. Trials that contained a freezing episode were indicated as freezing trials (FOG) and trials without a freezing episode were termed as functional gait (FG). Furthermore, the highly varied gait data between onset and termination of a FOG episode was excluded. A Temporal Convolutional Neural network (TCN) was trained end-to-end with lower extremity kinematics. A Bland-Altman analysis was performed to evaluate the agreement between the results of the proposed model and the manual annotations. Results: For FOG-trials, F1 scores of 0.995 and 0.992 were obtained for IC and EC, respectively. For FG-trials, F1 scores of 0.997 and 0.999 were obtained for IC and EC, respectively. The Bland-Altman plots indicated excellent timing agreement, with on average 39% and 47% of the model predictions occurring within 10 ms from the manual annotations for FOG-trials and FG-trials, respectively. Significance: These results indicate that our data-driven approach for detecting gait events in PD patients with FOG is sufficiently accurate and reliable for clinical applications.-
dc.language.isoen-
dc.publisherELSEVIER IRELAND LTD-
dc.rights2020 Elsevier B.V. All rights reserved.-
dc.subject.otherGait event detection-
dc.subject.otherParkinson's disease-
dc.subject.otherFreezing of gait-
dc.subject.otherDeep learning-
dc.subject.otherCNN-
dc.subject.otherArti ficial intelligence-
dc.titleA data-driven approach for detecting gait events during turning in people with Parkinson's disease and freezing of gait-
dc.typeJournal Contribution-
dc.identifier.epage136-
dc.identifier.spage130-
dc.identifier.volume80-
local.format.pages7-
local.bibliographicCitation.jcatA1-
dc.description.notesFiltjens, B (corresponding author), Katholieke Univ Leuven, eMedia Res Lab STADIUS, Dept Elect Engn ESAT, Andreas Vesaliusstr 13, B-3000 Leuven, Belgium.-
dc.description.notesbenjamin.filtjens@kuleuven.be-
dc.description.otherFiltjens, B (corresponding author), Katholieke Univ Leuven, eMedia Res Lab STADIUS, Dept Elect Engn ESAT, Andreas Vesaliusstr 13, B-3000 Leuven, Belgium. benjamin.filtjens@kuleuven.be-
local.publisher.placeELSEVIER HOUSE, BROOKVALE PLAZA, EAST PARK SHANNON, CO, CLARE, 00000, IRELAND-
local.type.refereedRefereed-
local.type.specifiedArticle-
dc.identifier.doi10.1016/j.gaitpost.2020.05.026-
dc.identifier.pmid32504940-
dc.identifier.isiWOS:000548457100024-
dc.contributor.orcidD'Cruz, Nicholas/0000-0002-5306-5903; Filtjens,-
dc.contributor.orcidBenjamin/0000-0003-2609-6883; Vanrumste, Bart/0000-0002-9409-935X-
local.provider.typewosris-
local.uhasselt.uhpubyes-
local.description.affiliation[Filtjens, Benjamin; Vanrumste, Bart] Katholieke Univ Leuven, eMedia Res Lab STADIUS, Dept Elect Engn ESAT, Andreas Vesaliusstr 13, B-3000 Leuven, Belgium.-
local.description.affiliation[Filtjens, Benjamin; Slaets, Peter] Katholieke Univ Leuven, Intelligent Mobile Platform Res Grp, Dept Mech Engn, Andreas Vesaliusstr 13, B-3000 Leuven, Belgium.-
local.description.affiliation[Nieuwboer, Alice; D'cruz, Nicholas] Katholieke Univ Leuven, Res Grp Neurorehabil eNRGy, Dept Rehabil Sci, Tervuursevest 101, B-3001 Heverlee, Belgium.-
local.description.affiliation[Spildooren, Joke] Hasselt Univ, Rehabil Res Ctr REVAL, Dept Rehabil Sci, Agoralaan Gebouw A, B-3590 Diepenbeek, Belgium.-
item.validationecoom 2021-
item.accessRightsOpen Access-
item.fullcitationFiltjens, Benjamin; Nieuwboer, Alice; D'cruz, Nicholas; SPILDOOREN, Joke; SLAETS, Leen & VANRUMSTE, Bart (2020) A data-driven approach for detecting gait events during turning in people with Parkinson's disease and freezing of gait. In: GAIT & POSTURE, 80 , p. 130 -136.-
item.fulltextWith Fulltext-
item.contributorFiltjens, Benjamin-
item.contributorNieuwboer, Alice-
item.contributorD'cruz, Nicholas-
item.contributorSPILDOOREN, Joke-
item.contributorSLAETS, Leen-
item.contributorVANRUMSTE, Bart-
crisitem.journal.issn0966-6362-
crisitem.journal.eissn1879-2219-
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