Entropy-Based Machine Learning Model for Fast Diagnosis and Monitoring of Parkinson’s Disease

Entropy-Based Machine Learning Model for Fast Diagnosis and Monitoring of Parkinson’s Disease

This study presents the concept of a computationally efficient machine learning (ML) model for diagnosing and monitoring Parkinson’s disease (PD) using rest-state EEG signals (rs-EEG) from 20 PD subjects and 20 normal control (NC) subjects at a sampling rate of 128 Hz. Based on the comparative analy...

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Bibliographic Details
Main Authors: Maksim Belyaev, Murugappan Murugappan, Andrei Velichko, Dmitry Korzun
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Sensors
Subjects:
Parkinson’s disease
EEG
diagnosis
entropy
machine learning
monitoring
Online Access:https://www.mdpi.com/1424-8220/23/20/8609

Internet

https://www.mdpi.com/1424-8220/23/20/8609

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