Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/13967
Title: Parkinson hastalığı sınıflandırmasına yönelik ivmeölçer tabanlı zamanlama analizi
Other Titles: Accelerometer-based timing analysis for Parkinson's disease classification
Authors: Onay, Fatih
Karaçalı, Bilge
Keywords: Pedaling
Parkinson disease
FoG
Accelerometers
Classification
Filtering
Delay time
Issue Date: 2023
Publisher: IEEE
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
URI: https://doi.org/10.1109/SIU59756.2023.10223916
https://hdl.handle.net/11147/13967
ISBN: 979-8-3503-4355-7
ISSN: 2165-0608
Appears in Collections:Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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