Rodyti trumpą aprašą

dc.contributor.authorLukšys, Donatas
dc.contributor.authorKizlaitienė, Rasa
dc.contributor.authorKaubrys, Gintaras Ferdinandas
dc.contributor.authorPakulaitė-Kazlienė, Gytė
dc.contributor.authorJatužis, Dalius
dc.contributor.authorKaladytė-Lokominienė, Rūta
dc.contributor.authorVilimienė, Ramunė
dc.contributor.authorGriškevičius, Julius
dc.date.accessioned2023-09-18T16:47:53Z
dc.date.available2023-09-18T16:47:53Z
dc.date.issued2016
dc.identifier.other(BIS)VGT02-000033401
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/116951
dc.description.abstractHuman gait is cyclic process, which is affected by various neurological disorders like Parkinson’s disease (PD) or multiple sclerosis (MS). Instrumented gait analy sis facilitate monitoring and diagnosing motor deficiencies; it ma y serve as a tool for clinicians evaluating the patients. This study aims at finding biomechanical parameters that allow separat ing pathological gaits via application of inertial sensors to capture the gait. The experiment involved 33 subjects divid ed in three groups PD, MS and healthy controls (CO). The analys is showed the statistically significant difference bet ween stride time of the right leg in MS and CO groups, left str ide time between PD and CO, stance time difference between P D and CO group, right and left leg. Hip flexion and exten sions amplitudes difference was between CO and PD group, left hip flexion and extension.eng
dc.formatPDF
dc.format.extentp. 1-4
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyConference Proceedings Citation Index - Science (Web of Science)
dc.relation.isreferencedbyIEEE Xplore
dc.source.urihttp://ieeexplore.ieee.org/document/7821814/
dc.subjectIK04 - Skaitmeninės signalų apdorojimo technologijos / Digital signal processing technologies
dc.titleNeurological diseases differentiation analysis using inertial measurement units
dc.typeStraipsnis konferencijos darbų leidinyje Web of Science DB / Paper in conference publication in Web of Science DB
dcterms.accessRightsOrganized by: Vilnius Gediminas Technical University, Riga Technical University, IEEE Latvia Section
dcterms.references10
dc.type.pubtypeP1a - Straipsnis konferencijos darbų leidinyje Web of Science DB / Article in conference proceedings Web of Science DB
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.institutionVšĮ Vilniaus universiteto ligoninės Santariškių klinikos
dc.contributor.facultyMechanikos fakultetas / Faculty of Mechanics
dc.subject.researchfieldT 009 - Mechanikos inžinerija / Mechanical enginering
dc.subject.ltspecializationsL105 - Sveikatos technologijos ir biotechnologijos / Health technologies and biotechnologies
dc.subject.enIMU
dc.subject.enGait analysis
dc.subject.enLower limb
dc.subject.enPathological gait
dcterms.sourcetitleAIEEE’2016 : 2016 IEEE 4th workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE) : proceedings of the 4th IEEE workshop, November 10–12, 2016 Vilnius, Lithuania / Edited by: Dalius Navakauskas, Andrejs Romanovs, Darius Plonis
dc.publisher.nameIEEE
dc.publisher.cityWashington
dc.identifier.doi000393578900014
dc.identifier.doi10.1109/AIEEE.2016.7821814
dc.identifier.elaba20055077


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Rodyti trumpą aprašą