Parkinson hastalığı sınıflandırmasına yönelik ivmeölçer tabanlı zamanlama analizi
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Date
2023
Authors
Karaçalı, Bilge
Onay, Fatih
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Open Access Color
Green Open Access
No
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Publicly Funded
No
Abstract
Parkinson's disease is a neurodegenerative disorder caused by dopamine deficiency in the basal ganglia, resulting in cognitive and motor impairments. In this study, accelerometer signals were used to estimate the delay time between the command to start pedaling and the actual movement onset in three groups: healthy individuals (n=13), Parkinson's disease patients (n=13), and patients with freezing of gait symptoms (n=13). Features were extracted from the delay time distributions for each participant and subjected to a triple classification. Linear support vector machine achieved a classification accuracy of 69.2% for all participants. Notably, the average time to start pedaling was found to be significantly different among the three groups, and accelerometer-based timing analysis could be used as a diagnostic tool to assist clinical tests.
Description
31st IEEE Conference on Signal Processing and Communications Applications (SIU) -- JUL 05-08, 2023 -- Istanbul Tech Univ, Ayazaga Campus, Istanbul, TURKEY
Keywords
Pedaling, Parkinson disease, FoG, Accelerometers, Classification, Filtering, Delay time
Fields of Science
Citation
WoS Q
N/A
Scopus Q
N/A

OpenCitations Citation Count
N/A
Source
2023 31st Signal Processing and Communications Applications Conference, Siu
Volume
Issue
Start Page
1
End Page
4
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Citations
Scopus : 2
SCOPUS™ Citations
2
checked on Apr 27, 2026
Page Views
348
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Downloads
255
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