Neural decoding of imagined speech from EEG signals using the fusion of graph signal processing and graph learning techniques

Neural decoding of imagined speech from EEG signals using the fusion of graph signal processing and graph learning techniques

Imagined Speech (IS) is the imagination of speech without using the tongue or muscles. In recent studies, IS tasks are increasingly investigated for the Brain-Computer Interface (BCI) applications. Electroencephalography (EEG) signals, which record brain activity, can be used to analyze BCI-based ta...

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Bibliographic Details
Main Authors: Aref Einizade, Mohsen Mozafari, Shayan Jalilpour, Sara Bagheri, Sepideh Hajipour Sardouie
Format: Article
Language:English
Published: Elsevier 2022-09-01
Series:Neuroscience Informatics
Subjects:
Brain-Computer Interface (BCI)
Imagined Speech (IS)
Electroencephalography (EEG)
Machine Learning (ML)
Graph Signal Processing (GSP)
Graph Learning (GL)
Online Access:http://www.sciencedirect.com/science/article/pii/S277252862200053X

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