Implementation of Artifact Removal Algorithms in Gait Signals for Diagnosis of Parkinson Disease

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dc.contributor.authorOzel, Erdogan
dc.contributor.authorTekin, Ramazan
dc.contributor.authorKaya, Yilmaz
dc.date.accessioned2024-12-24T19:30:31Z
dc.date.available2024-12-24T19:30:31Z
dc.date.issued2021
dc.departmentSiirt Üniversitesi
dc.description.abstractParkinson's disease (PD) is a neurological disease that progresses further over time. Individuals suffering from this condition have a deficiency of dopamine, a neurotransmitter found in the brain's nerve cells that is critical for coordinating body movement. In this study, a new approach is proposed for the diagnosis of PD. Common Average Reference (CAR), Median Common Average Reference (MCAR), and Weighted Common Average Reference (WCAR) methods were primarily utilized to eliminate noise from the multichannel recorded walking signals in the resulting PhysioNet dataset. Statistical features were obtained from the clean walking signals following the Local Binary Pattern (LBP) transformation application. Logistic Regression (LR), Random Forest (RF), and K-nearest neighbor (Kim) methods were utilized in the classification stage. A high success rate with a value of 92.96% was observed with Kim. It was also determined that signals on which foot and the signals obtained from which point of the sole of the foot were effective in PD diagnosis in the study. In light of the findings, it was observed that noise reduction methods increased the success rate of PD diagnosis.
dc.identifier.doi10.18280/ts.380306
dc.identifier.endpage597
dc.identifier.issn0765-0019
dc.identifier.issn1958-5608
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85112003117
dc.identifier.scopusqualityN/A
dc.identifier.startpage587
dc.identifier.urihttps://doi.org/10.18280/ts.380306
dc.identifier.urihttps://hdl.handle.net/20.500.12604/7551
dc.identifier.volume38
dc.identifier.wosWOS:000681761900006
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInt Information & Engineering Technology Assoc
dc.relation.ispartofTraitement Du Signal
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241222
dc.subjectfiltering and noise reduction
dc.subjectParkinson disease
dc.subjectfeature extraction
dc.subjectsignal processing
dc.titleImplementation of Artifact Removal Algorithms in Gait Signals for Diagnosis of Parkinson Disease
dc.typeArticle

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