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Evaluation of Golden Gait Approximation Using Smart Clothing

dc.rights.licenseCC0en_US
dc.contributor.authorSCATAGLINI, Sofia
dc.contributor.authorABRAN, Guillaume
dc.contributor.authorROOSENS, Eddy
dc.contributor.authorVAN TIGGELEN, Damien
dc.contributor.authorHAELTERMAN, Robby
dc.contributor.authorVERVULWGEN, Stijn
dc.date.accessioned2024-12-11T09:31:31Z
dc.date.available2024-12-11T09:31:31Z
dc.date.issued2020
dc.identifier.urihttps://luck.synhera.be/handle/123456789/2896
dc.identifier.doi10.1007/978-3-030-51064-0_35en_US
dc.description.abstractS. Scataglini et al., Evaluation of Golden Gait Approximation Using Smart Clothing, AHFE 2020, juin 2020en_US
dc.description.abstractenGait analysis was calculated in eighteen healthy male adults (mean age 26.33 ± 4.40 years, body mass 74.66 ± 5.62 kg) wearing a smart shirt based on body-worn accelerometer. This approximation relating the inverted pendulum model to a fractal approach of walking, where an approximation of using the golden ratio u is seen in our case nearby the golden ratio (u = 1.61). Our results demonstrated that the inverted pendulum model and walking speed are affected by anthropometric characteristics with p < 0.001. As a result, smart clothing based on body-worn accelerometer revealed to be an innovative and useful device to monitoring gait and in particular ideal gait approximation in a non-intrusive way and ecological approach in different environments.en_US
dc.language.isoENen_US
dc.publisherAHFEen_US
dc.rights.uriinconnuen_US
dc.subject.enGolden ratio ����� Walking speed ����� Spatio-temporal gait parameters ����� Gait ����� Smart clothing ����� Wearable sensorsen_US
dc.titleEvaluation of Golden Gait Approximation Using Smart Clothingen_US
dc.title.enEvaluation of Golden Gait Approximation Using Smart Clothingen_US
dc.typeActe de conférence ou de colloqueen_US
synhera.classificationIngénierie, informatique & technologieen_US
synhera.institutionHE Libre de Bruxelles Ilya Prigogineen_US
dc.description.versionOuien_US
dc.rights.holderinconnuen_US


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