Parkinson hastalığı sınıflandırmasına yönelik ivmeölçer tabanlı zamanlama analizi

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Date

2023

Authors

Karaçalı, Bilge
Onay, Fatih

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IEEE

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Green Open Access

No

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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

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2023 31st Signal Processing and Communications Applications Conference, Siu

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1

End Page

4
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Scopus : 2

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348

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255

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