Analysis of Gait Dynamics of ALS Disease and Classification of Artificial Neural Networks

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dc.authorid0000-0003-1860-7049
dc.authorid0000-0002-4657-6617
dc.authorid0000-0003-3486-2197
dc.authorid0000-0001-8894-5794
dc.authorscopusid17433273300
dc.authorscopusid35617283100
dc.authorscopusid57201280225
dc.authorscopusid16229256000
dc.authorwosidDemir, Hasan/ABA-3698-2020
dc.authorwosidAkan, Aydin/P-3068-2019
dc.authorwosidAKGÜN, ÖMER/AAC-8894-2019
dc.authorwosidAKINCI, Tahir Cetin/AAB-3397-2021
dc.contributor.authorAkgün, Ömer
dc.contributor.authorAkan, Aydın
dc.contributor.authorDemir, Hasan
dc.contributor.authorAkıncı, Tahir Çetin
dc.date.accessioned2022-05-11T14:17:40Z
dc.date.available2022-05-11T14:17:40Z
dc.date.issued2018
dc.departmentFakülteler, Çorlu Mühendislik Fakültesi, Elektronik ve Haberleşme Mühendisliği Bölümü
dc.description.abstractIn this study, a gait device was used for gathering data.A group comprising control group and ALS patients was requested to walk using this device.Gait signals of the control group individuals and ALS patients taken from their left feet were recorded by means of the sensors sensitive to the force which was placed to the device. Spectral and statistical analyses of these signals were made.The results obtained from these analyses were used for making classification with Artificial Neural Network.In consequence of the classification, the individuals with ALS disease were diagnosed accurately with an average rate of 82 %.In the study, the signals taken from left foot of 14 normal individuals and 13 ALS patients were analyzed.
dc.identifier.doi10.17559/TV-20160914144554
dc.identifier.endpage187
dc.identifier.issn1330-3651
dc.identifier.issn1848-6339
dc.identifier.scopus2-s2.0-85047823645
dc.identifier.scopusqualityQ3
dc.identifier.startpage183
dc.identifier.urihttps://doi.org/10.17559/TV-20160914144554
dc.identifier.urihttps://hdl.handle.net/20.500.11776/6435
dc.identifier.volume25
dc.identifier.wosWOS:000433290300026
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorDemir, Hasan
dc.language.isoen
dc.publisherUniv Osijek, Tech Fac
dc.relation.ispartofTehnicki Vjesnik-Technical Gazette
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectALS Disease
dc.subjectArtificial Neural Nets
dc.subjectGait Dynamics Analysis
dc.subjectPiezo Electric Sensors
dc.subjectSound and Vibration
dc.subjectAmyotrophic-Lateral-Sclerosis
dc.subjectPerspective
dc.titleAnalysis of Gait Dynamics of ALS Disease and Classification of Artificial Neural Networks
dc.typeArticle

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