Shoulder glenohumeral elevation estimation based on upper arm orientation
dc.contributor.author | Hamdan, Sara | |
dc.contributor.author | Öztop, Erhan | |
dc.contributor.author | Furukawa, J.-I. | |
dc.contributor.author | Morimoto, J. | |
dc.contributor.author | Uğurlu, Regaip Barkan | |
dc.date.accessioned | 2019-03-04T14:23:46Z | |
dc.date.available | 2019-03-04T14:23:46Z | |
dc.date.issued | 2018-10-26 | |
dc.identifier.isbn | 978-153863646-6 | |
dc.identifier.issn | 1557-170X | en_US |
dc.identifier.uri | http://hdl.handle.net/10679/6183 | |
dc.identifier.uri | https://ieeexplore.ieee.org/document/8512564 | |
dc.description.abstract | In 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.sponsorship | New 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.language.iso | eng | en_US |
dc.publisher | IEEE | en_US |
dc.relation | info:turkey/grantAgreement/TUBITAK/116C014 | |
dc.relation.ispartof | 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) | |
dc.rights | restrictedAccess | |
dc.title | Shoulder glenohumeral elevation estimation based on upper arm orientation | en_US |
dc.type | Conference paper | en_US |
dc.publicationstatus | Published | en_US |
dc.contributor.department | Özyeğin University | |
dc.contributor.authorID | (ORCID 0000-0002-3051-6038 & YÖK ID 45227) Öztop, Erhan | |
dc.contributor.authorID | (ORCID 0000-0002-9124-7441 & YÖK ID 241209) Uğurlu, Barkan | |
dc.contributor.ozuauthor | Öztop, Erhan | |
dc.contributor.ozuauthor | Uğurlu, Regaip Barkan | |
dc.identifier.volume | 2018 | en_US |
dc.identifier.startpage | 1481 | en_US |
dc.identifier.endpage | 1484 | en_US |
dc.identifier.wos | WOS:000596231901234 | |
dc.identifier.doi | https://doi.org/10.1109/EMBC.2018.8512564 | en_US |
dc.subject.keywords | Biological system modeling | en_US |
dc.subject.keywords | Predictive models | en_US |
dc.subject.keywords | Shoulder | en_US |
dc.subject.keywords | Ground penetrating radar | en_US |
dc.subject.keywords | Biomechanics | en_US |
dc.subject.keywords | Measurement uncertainty | en_US |
dc.subject.keywords | Q measurement | en_US |
dc.identifier.scopus | SCOPUS:2-s2.0-85056629908 | |
dc.contributor.ozugradstudent | Hamdan, Sara | |
dc.relation.publicationcategory | Conference Paper - International - Institutional Academic Staff and Graduate Student |
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