Evaluation of Machine Learning Algorithms for Classification of EEG Signals

Evaluation of Machine Learning Algorithms for Classification of EEG Signals

In brain–computer interfaces (BCIs), it is crucial to process brain signals to improve the accuracy of the classification of motor movements. Machine learning (ML) algorithms such as artificial neural networks (ANNs), linear discriminant analysis (LDA), decision tree (D.T.), K-nearest neighbor (KNN)...

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Bibliographic Details
Main Authors: Francisco Javier Ramírez-Arias, Enrique Efren García-Guerrero, Esteban Tlelo-Cuautle, Juan Miguel Colores-Vargas, Eloisa García-Canseco, Oscar Roberto López-Bonilla, Gilberto Manuel Galindo-Aldana, Everardo Inzunza-González
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Technologies
Subjects:
EEG
BCI
feature extraction
artificial intelligence
machine learning
deep learning
Online Access:https://www.mdpi.com/2227-7080/10/4/79

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https://www.mdpi.com/2227-7080/10/4/79

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