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dc.contributor.authorRodrigues, Thiago Braga
dc.contributor.authorÓ'Catháin, Ciarán
dc.contributor.authorO'Connor, Noel E.
dc.contributor.authorMurray, Niall
dc.date.accessioned2020-03-30T15:26:42Z
dc.date.available2020-03-30T15:26:42Z
dc.date.copyright2019
dc.date.issued2020-03-23
dc.identifier.citationRodrigues, T.B., Ó'Catháin, C., O'Connor, N.E., Murray, N. (2020). A quality of experience assessment of haptic and augmented reality feedback modalities in a gait analysis system. PLOS One. 15(3):e0230570. doi: 10.1371/journal.pone.0230570. eCollection 2020.en_US
dc.identifier.issn1932-6203
dc.identifier.urihttp://research.thea.ie/handle/20.500.12065/3067
dc.description.abstractGait analysis is a technique that is used to understand movement patterns and, in some cases, to inform the development of rehabilitation protocols. Traditional rehabilitation approaches have relied on expert guided feedback in clinical settings. Such efforts require the presence of an expert to inform the re-training (to evaluate any improvement) and the patient to travel to the clinic. Nowadays, potential opportunities exist to employ the use of digitized "feedback" modalities to help a user to "understand" improved gait technique. This is important as clear and concise feedback can enhance the quality of rehabilitation and recovery. A critical requirement emerges to consider the quality of feedback from the user perspective i.e. how they process, understand and react to the feedback. In this context, this paper reports the results of a Quality of Experience (QoE) evaluation of two feedback modalities: Augmented Reality (AR) and Haptic, employed as part of an overall gait analysis system. The aim of the feedback is to reduce varus/valgus misalignments, which can cause serious orthopedics problems. The QoE analysis considers objective (improvement in knee alignment) and subjective (questionnaire responses) user metrics in 26 participants, as part of a within subject design. Participants answered 12 questions on QoE aspects such as utility, usability, interaction and immersion of the feedback modalities via post-test reporting. In addition, objective metrics of participant performance (angles and alignment) were also considered as indicators of the utility of each feedback modality. The findings show statistically significant higher QoE ratings for AR feedback. Also, the number of knee misalignments was reduced after users experienced AR feedback (35% improvement with AR feedback relative to baseline when compared to haptic). Gender analysis showed significant differences in performance for number of misalignments and time to correct valgus misalignment (for males when they experienced AR feedback). The female group self-reported higher utility and QoE ratings for AR when compared to male group.en_US
dc.formatPDFen_US
dc.language.isoenen_US
dc.publisherPublic Library of Scienceen_US
dc.relation.ispartofPLOS Oneen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Ireland*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/ie/*
dc.subjectGait analysisen_US
dc.subjectFeedback modalitiesen_US
dc.subjectQoE - Quality of experienceen_US
dc.titleA quality of experience assessment of haptic and augmented reality feedback modalities in a gait analysis system.en_US
dc.typeArticleen_US
dc.description.peerreviewyesen_US
dc.identifier.doiFunding: The work presented in this paper has been supported by the Irish Research Council under grant GOIPG/2017/803 awarded to T.B.R. This publication has also been supported by the Science Foundation Ireland (SFI) under grant number SFI/12/RC/2289_P2 awarded to N.OC. and grant number SFI/13/RC/2106 awarded to N.M
dc.identifier.orcidhttps://orcid.org/0000-0002-2017-4492
dc.identifier.orcidhttps://orcid.org/0000-0002-2017-4492
dc.identifier.orcidhttps://orcid.org/0000-0002-8526-8924
dc.identifier.orcidhttps://orcid.org/0000-0002-5919-0596
dc.identifier.orcidhttps://orcid.org/0000-0002-5919-0596
dc.identifier.orcidhttps://orcid.org/0000-0002-5919-0596
dc.rights.accessOpen Accessen_US
dc.subject.departmentFaculty of Engineering and Informatics AITen_US
cr.identifier.grantFunding: The work presented in this paper has been supported by the Irish Research Council under grant GOIPG/2017/803 awarded to T.B.R. This publication has also been supported by the Science Foundation Ireland (SFI) under grant number SFI/12/RC/2289_P2 awarded to N.OC. and grant number SFI/13/RC/2106 awarded to N.M


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Attribution-NonCommercial-NoDerivs 3.0 Ireland
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Ireland