A Comparative Study of Machine Learning and Deep Learning Models for Automatic Parkinson’s Disease Detection from Electroencephalogram Signals

A Comparative Study of Machine Learning and Deep Learning Models for Automatic Parkinson’s Disease Detection from Electroencephalogram Signals

<b>Background:</b> Parkinson’s disease (PD) is one of the most prevalent, widespread, and intricate neurodegenerative disorders. According to the experts, at least 1% of people over the age of 60 are affected worldwide. In the present time, the early detection of PD remains difficult due...

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Bibliographic Details
Main Authors: Sankhadip Bera, Zong Woo Geem, Young-Im Cho, Pawan Kumar Singh
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Diagnostics
Subjects:
Parkinson’s disease detection
electroencephalogram signals
power spectral density
UC San Diego Resting State EEG dataset
IOWA dataset
support vector machine
Online Access:https://www.mdpi.com/2075-4418/15/6/773
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