Publication:
Shoulder glenohumeral elevation estimation based on upper arm orientation

dc.contributor.authorHamdan, Sara
dc.contributor.authorÖztop, Erhan
dc.contributor.authorFurukawa, J.-I.
dc.contributor.authorMorimoto, J.
dc.contributor.authorUğurlu, Regaip Barkan
dc.contributor.departmentComputer Science
dc.contributor.departmentMechanical Engineering
dc.contributor.ozuauthorÖZTOP, Erhan
dc.contributor.ozuauthorUĞURLU, Regaip Barkan
dc.contributor.ozugradstudentHamdan, Sara
dc.date.accessioned2019-03-04T14:23:46Z
dc.date.available2019-03-04T14:23:46Z
dc.date.issued2018-10-26
dc.description.abstractIn this paper, the shoulder glenohumeral displacement during the movement of the upper arm is studied. Four modeling approaches were examined and compared to estimate the humeral head elevation (vertical displacement) and translation (horizontal displacement). A biomechanics-inspired method was used firstly to model the glenohumeral displacement in which a least squares method was implemented for parameter identification. Then, three Gaussian process regression models were used in which the following variable sets were employed: i) shoulder adduction/abduction angle, ii) combination of shoulder adduction/abduction and flexion/extension angles, iii) overall upper arm orientation in the form of quaternions. In order to test the respective performances of these four models, we collected motion capture data and compared the models' representative capabilities. As a result, Gaussian process regression that considered the overall upper arm orientation outperformed the other modeling approaches; however, it should be noted that the other methods also provided accuracy levels that may be sufficient depending on task requirements.en_US
dc.description.sponsorshipNew Energy and Industrial Technology Development Organization ; Japan Society for the Promotion of Science ; Cabinet Office, Government of Japan ; Council for Science, Technology and Innovation ; TÜBİTAK ; Japan Agency for Medical Research and Development.
dc.identifier.doi10.1109/EMBC.2018.8512564en_US
dc.identifier.endpage1484en_US
dc.identifier.isbn978-153863646-6
dc.identifier.issn1557-170Xen_US
dc.identifier.scopus2-s2.0-85056629908
dc.identifier.startpage1481en_US
dc.identifier.urihttp://hdl.handle.net/10679/6183
dc.identifier.urihttps://doi.org/10.1109/EMBC.2018.8512564
dc.identifier.volume2018en_US
dc.identifier.wos000596231901234
dc.language.isoengen_US
dc.publicationstatusPublisheden_US
dc.publisherIEEEen_US
dc.relationinfo:eu-repo/grantAgreement/TUBITAK/1001 - Araştırma/116C014
dc.relation.ispartof2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
dc.relation.publicationcategoryInternational
dc.rightsrestrictedAccess
dc.subject.keywordsBiological system modelingen_US
dc.subject.keywordsPredictive modelsen_US
dc.subject.keywordsShoulderen_US
dc.subject.keywordsGround penetrating radaren_US
dc.subject.keywordsBiomechanicsen_US
dc.subject.keywordsMeasurement uncertaintyen_US
dc.subject.keywordsQ measurementen_US
dc.titleShoulder glenohumeral elevation estimation based on upper arm orientationen_US
dc.typeconferenceObjecten_US
dspace.entity.typePublication
relation.isOrgUnitOfPublication85662e71-2a61-492a-b407-df4d38ab90d7
relation.isOrgUnitOfPublicationdaa77406-1417-4308-b110-2625bf3b3dd7
relation.isOrgUnitOfPublication.latestForDiscovery85662e71-2a61-492a-b407-df4d38ab90d7

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