Karaçalı, BilgeOnay, Fatih2023-11-112023-11-112023979-8-3503-4355-72165-0608https://doi.org/10.1109/SIU59756.2023.10223916https://hdl.handle.net/11147/1396731st IEEE Conference on Signal Processing and Communications Applications (SIU) -- JUL 05-08, 2023 -- Istanbul Tech Univ, Ayazaga Campus, Istanbul, TURKEYParkinson'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.trinfo:eu-repo/semantics/openAccessPedalingParkinson diseaseFoGAccelerometersClassificationFilteringDelay timeConference Object2-s2.0-8517348718510.1109/SIU59756.2023.10223916