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dc.contributor.authorRodrigues, Thiago Braga
dc.contributor.authorSalgado, Debora Pereira
dc.contributor.authorÓ Catháin, Ciarán
dc.contributor.authorO'Connor, Noel
dc.contributor.authorMurray, Niall
dc.date.accessioned2019-12-17T09:43:40Z
dc.date.available2019-12-17T09:43:40Z
dc.date.copyright2019
dc.date.issued2019-12-05
dc.identifier.citationRodrigues, T.B., Salgaod, D. P., Ó Catháin, C., O'Connor, Noel. (2019). Human gait assessment using a 3D marker-less multimodal motion capture system. Multimedia Tools and Applications. 5 December. doi:10.1007/s11042-019-08275-9.en_US
dc.identifier.issn1573-7721
dc.identifier.issn1380-7501
dc.identifier.otherArticles - Software Research Instituteen_US
dc.identifier.urihttp://research.thea.ie/handle/20.500.12065/2936
dc.description.abstractGait analysis is the measurement, processing and systematic interpretation of biomechanical parameters that characterize human locomotion. It supports the identification of movement limitations and development of rehabilitation procedures. Accurate Gait analysis is important in sports analysis, medical field, and rehabilitation. Although Gait analysis is performed in several laboratories in many countries, there are many issues such as: (i) the high cost of precise Motion Capture systems; (ii) the scarcity of qualified personnel to operate them; (iii) expertise required to interpret their results; (iv) space requirements to install and store these systems; as well as difficulties related to the measurement protocols of each system; (vi) limited availability (vii) and the use of markers can be a barrier for some clinical use cases (e.g. patients recovering from orthopedics surgeries). In this work, we present a low cost and more accessible system based on the integration of a Multiple Microsoft Kinect sensors and multiple Shimmer inertial sensors to capture human Gait. The novel multimodal system combines data from inertial and 3D depth cameras and outputs spatiotemporal Gait variables. A comparison of this system with the VICON system (the gold standard in Motion Capture) was performed. Our relatively low-cost marker-less multimodal motion generates a complete 360-degree skeleton view. We compare our system with the VICON via gait spatiotemporal variables: Gait cycle time, stride time, Gait length (distance between two strides), stride length, and velocity. The system was also evaluated with knee and hip joint angles measurement accuracy. The results show high correlation for spatiotemporal variables and joint angles inside the 95% bootstrap prediction when compared with VICON.en_US
dc.formatPDFen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofMultimedia Tools and Applicationsen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Ireland*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/ie/*
dc.subject3D modelen_US
dc.subjectGait analysisen_US
dc.subjectMotion captureen_US
dc.subjectMultmodal sensorsen_US
dc.titleHuman gait assessment using a 3D marker-less multimodal motion capture system.en_US
dc.typeArticleen_US
dc.description.peerreviewyesen_US
dc.identifier.doidoi:10.1007/s11042-019-08275-9.
dc.identifier.orcidhttps://orcid.org/0000-0002-2017-4492
dc.identifier.orcidhttps://orcid.org/0000-0003-1313-8044
dc.identifier.orcidhttps://orcid.org/0000-0002-8526-8924
dc.identifier.orcidhttps://orcid.org/0000-0002-5919-0596
dc.rights.accessOpen Accessen_US
dc.subject.departmentFaculty of Engineering & Informaticsen_US


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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