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dc.contributor.authorGracia-Ibáñez, Verónica
dc.contributor.authorVergara, Margarita
dc.contributor.authorBuffi, James H.
dc.contributor.authorMurray, Wendy M.
dc.contributor.authorSancho-Bru, Joaquin L.
dc.date.accessioned2017-02-01T08:38:47Z
dc.date.available2017-02-01T08:38:47Z
dc.date.issued2016
dc.identifier.citationGRACIA-IBÁÑEZ, Verónica, et al. Across-subject calibration of an instrumented glove to measure hand movement for clinical purposes. Computer Methods in Biomechanics and Biomedical Engineering, 2016, p. 1-11.ca_CA
dc.identifier.issn1025-5842
dc.identifier.issn1476-8259
dc.identifier.urihttp://hdl.handle.net/10234/165775
dc.description.abstractMotion capture of all degrees of freedom of the hand collected during performance of daily living activities remains challenging. Instrumented gloves are an attractive option because of their higher ease of use. However, subject-specific calibration of gloves is lengthy and has limitations for individuals with disabilities. Here, a calibration procedure is presented, consisting in the recording of just a simple hand position so as to allow capture of the kinematics of 16 hand joints during daily life activities even in case of severe injured hands. ‘across-subject gains’ were obtained by averaging the gains obtained from a detailed subject-specific calibration involving 44 registrations that was repeated three times on multiple days to 6 subjects. In additional 4 subjects, joint angles that resulted from applying the ‘across-subject calibration’ or the subject-specific calibration were compared. Global errors associated with the ‘across-subject calibration’ relative to the detailed, subject-specific protocol were small (bias: 0.49°; precision: 4.45°) and comparable to those that resulted from repeating the detailed protocol with the same subject on multiple days (0.36°; 3.50°). Furthermore, in one subject, performance of the ‘across-subject calibration’ was directly compared to another fast calibration method, expressed relative to a videogrammetric protocol as a gold-standard, yielding better results.ca_CA
dc.description.sponsorShipThis work was supported by the Ministerio de Economía y Competitividad [project number DPI2014-52095-P]; Universitat Jaume I [project number P1-1B2013-33], [project number P1-1B2014-10]; NIH [grant number NIH R01EB011615]. We thank Marta Mora, PhD, for her collaboration in coding for data glove acquisition, and the graduate student Sheyla Mestre Vicente for her collaboration in data collection. Authors thank also Union de Mutuas for their support in clinical guidanceca_CA
dc.format.extent11 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherTaylor & Francisca_CA
dc.relation.isPartOfComputer Methods in Biomechanics and Biomedical Engineering, 2016ca_CA
dc.rights© Taylor & Francis Groupca_CA
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/*
dc.subjectinstrumented gloveca_CA
dc.subjectacross-subject calibrationca_CA
dc.subjectfast calibrationca_CA
dc.subjecthand movementca_CA
dc.subjecthand disabilitiesca_CA
dc.titleAcross-subject calibration of an instrumented glove to measure hand movement for clinical purposesca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttp://dx.doi.org/10.1080/10255842.2016.1265950
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_CA
dc.relation.publisherVersionhttp://www.tandfonline.com/doi/full/10.1080/10255842.2016.1265950?scroll=top&needAccess=trueca_CA


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