Development and Evaluation of Camera-based System for Analysis of Dual-task in Faller and Non-faller Older Adults: Gait combined with Prehension

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dc.contributor.advisorFrizera Neto, Anselmo
dc.contributor.refereeFerreira, André
dc.contributor.refereeRoncon, Eduardo
dc.date.accessioned2019-03-15T02:12:35Z
dc.date.available2019-03-14
dc.date.available2019-03-15T02:12:35Z
dc.identifier.urihttp://repositorio.ufes.br/handle/10/10948
dc.publisherUniversidade Federal do Espírito Santopor
dc.publisher.countryBRpor
dc.publisher.courseMestrado em Engenharia Elétricapor
dc.publisher.initialsUFESpor
dc.publisher.programPrograma de Pós-Graduação em Engenharia Elétricapor
dc.subjectDual-Task Paradigmeng
dc.subjectGaiteng
dc.subjectPrehensioneng
dc.subjectOlder Adultseng
dc.subjectFaller Older Adultseng
dc.subjectCamera-Based Systemseng
dc.subject.br-rjbnEngenharia biomédicapor
dc.subject.br-rjbnBiomecânicapor
dc.subject.br-rjbnVisão por computadorpor
dc.subject.br-rjbnIdosospor
dc.subject.br-rjbnMarcha humanapor
dc.subject.cnpqEletrônica Industrial, Sistemas e Controles Eletrônicospor
dc.subject.udc621.3
dc.titleDevelopment and Evaluation of Camera-based System for Analysis of Dual-task in Faller and Non-faller Older Adults: Gait combined with Prehensioneng
dc.typemasterThesiseng
dcterms.abstractOver the years, the population is aging rapidly and this is a global social and economic problem. As the age advances, it compromises the performance of motor abilities leading to an increased risk of falls. Recent studies suggest that there is a relationship between cognitive impairment and gait abnormalities and the gait performance has been used as predictor for cognitive decline and fall status, mainly in older adults with history of falls, also called faller older adults. The dual-task paradigm is a reference method that assess cognitive impairments, through the performance of the gait with another task simultaneously, such the combination of gait and prehension task, that is widely performed during activities of daily life. The investigation of the aging effects on gait pattern and grasp control when walking can be used as predictor to reduce the frequency of falls and to develop prevention of such falls. The biomechanics of human movement describes, analyzes and assesses human movement, including gait, posture and trunk movement and upper limb movement analysis. The advance in new technologies has facilitated the development of an objective evaluation of different movement parameters, such as accelerometers, force platforms and cameras. The Kinect sensor (Microsoft, USA) has been used for clinical motion analysis due to the low cost when compared with the expensive gold standard motion capturing systems. In addition, the Leap Motion Controller (Leap Motion, Inc., USA), also based on camera, has been used for analysis of hand movement. This work presents the development and evaluation of an accessible camera-based system using a sensor network composed by Kinect and Leap Motion Controller sensors to assess the gait and prehension parameters of fallers and non-fallers older adults under dual-task condition, gait combined with prehension. The proposed experimental protocol was divided in two conditions (walking through and dual-task) and was applied on twenty older adults (n=10). Results showed smaller step and stride lengths mean, and center of mass (CoM) velocity for fallers older adults. In addition, the both groups decreased the CoM velocity under dual-task condition, however, only faller older adults significantly decreased the step and stride lengths, with higher variability, in this condition. The faller older adults required longer movement time for perform the prehension task while walking, showing a performance more conservative. Results showed similarity with previous studies that used commercial systems, and the system developed capable to acquire the required parameters and evaluate the dual-task in the older adults. Future works involve the improvement of materials and techniques used in this work, and the analysis of more parameters.eng
dcterms.creatorAvellar, Letícia Munhoz de
dcterms.formatTexteng
dcterms.issued2019-02-18
dcterms.languageeng
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