Survey of Machine Learning Techniques in the Analysis of EEG Signals for Parkinson’s Disease: A Systematic Review

An article by Ana M. Maitín López and Álvaro J. García Tejedor, members of the CEIEC research team, and Juan Pablo Romero Muñoz, lecturer at the UFV and member of the Brain Injury Unit of the Beata María Ana Hospital, has recently been published in the journal Applied Sciences.

In this article, we review those studies that consider ML techniques to study the EEG of patients with PD from a computational science point of view. Methods: The review process was carried out following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, which are used to provide quality standards for the objective evaluation of various studies, resulting in 59 articles.

All publications prior to February (59 publications) 2022 were included and their main characteristics and results were assessed and documented across three key points associated with the development of ML techniques: dataset quality, dataset preprocessing and model evaluation.

The publication can be found at the following link.

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