Please use this identifier to cite or link to this item: http://hdl.handle.net/11434/56
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dc.contributor.authorWilliams, Gavinen
dc.contributor.authorMorris, Megen
dc.contributor.otherLai, Danielen
dc.contributor.otherSchache, Anthonyen
dc.date.accessioned2014-08-24T23:52:26Zen
dc.date.available2014-08-24T23:52:26Zen
dc.date.issued2015-03en
dc.identifier.citationThe Journal of Head Trauma Rehabilitation. Vol.30(2), Mar-Apr 2015, pp. E13-E23.en
dc.identifier.issn0885-9701en
dc.identifier.urihttp://hdl.handle.net/11434/56en
dc.description.abstractOBJECTIVE:: To determine the extent to which gait disorders associated with traumatic brain injury (TBI) are able to be classified into clinically relevant and distinct subgroups. DESIGN:: Cross-sectional cohort study comprising people with TBI receiving physiotherapy for mobility limitations. PARTICIPANTS:: One hundred two people with TBI. OUTCOME MEASURES:: The taxonomic framework for gait disorders following TBI was devised on the basis of a framework previously developed for people with cerebral palsy. Participants with TBI who were receiving therapy for mobility problems were assessed using 3-dimensional gait analysis. Pelvis and bilateral lower limb kinematic data were recorded using a VICON motion analysis system while each participant walked at a self-selected speed. Five trials of data were collected for each participant. Multiclass support vector machine models were developed to systematically and automatically ascertain the clinical classification. RESULTS:: The statistical features derived from the major joint angles from unaffected limbs contributed to the best classification accuracy of 82.35% (84 of the 102 subjects). Features from the affected limb resulted in a classification accuracy of 76.47% (78 of 102 subjects). CONCLUSIONS:: Despite considerable variability in gait disorders following TBI, we were able to generate a clinical classification system on the basis of 6 distinct subgroups of gait deviations. Statistical features related to the motion of the pelvis, hip, knee, and ankle on the less affected leg were able to accurately classify 82% of people with TBI-related gait disorders using a multiclass support vector machine framework.en
dc.subjectAssessmenten
dc.subjectGait Disordersen
dc.subjectBrain Traumaen
dc.subjectClassificationen
dc.subjectRehabilitationen
dc.subjectPhysiotherapy Department, Epworth Healthcare, Melbourne, Australia-
dc.subjectTBI-
dc.subjectTraumatic Brain Injury-
dc.subjectMobility-
dc.subject3-Dimensional Gait Analysis-
dc.subjectKinematic Data-
dc.subjectVICON motion analysis-
dc.titleClassification of gait disorders following traumatic brain injury.en
dc.typeJournal Articleen
dc.identifier.doi10.1097/HTR.0000000000000038en
dc.identifier.journaltitleJournal of Head Trauma and Rehabilitationen
dc.description.pubmedurihttp://www.ncbi.nlm.nih.gov/pubmed/24695264en
dc.type.studyortrialCross-sectional Cohort Study-
Appears in Collections:Neurosciences
Rehabilitation

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