Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning

Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning

The aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental sta...

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Bibliographic Details
Main Authors: Jakub Browarczyk, Adam Kurowski, Bozena Kostek
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:Sensors
Subjects:
electroencephalography (EEG)
brain–computer interface (BCI)
feature extraction
automatic classification
deep learning
Online Access:https://www.mdpi.com/1424-8220/20/8/2403

Internet

https://www.mdpi.com/1424-8220/20/8/2403

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