A Deep Learning Model for Correlation Analysis between Electroencephalography Signal and Speech Stimuli

A Deep Learning Model for Correlation Analysis between Electroencephalography Signal and Speech Stimuli

In recent years, the use of electroencephalography (EEG) has grown as a tool for diagnostic and brain function monitoring, being a simple and non-invasive method compared with other procedures like histological sampling. Typically, in order to extract functional brain responses from EEG signals, pro...

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Bibliographic Details
Main Authors: Michele Alessandrini, Laura Falaschetti, Giorgio Biagetti, Paolo Crippa, Simona Luzzi, Claudio Turchetti
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Sensors
Subjects:
canonical correlation analysis (CCA)
deep correlation analysis (DCCA)
deep learning
electroencephalography (EEG)
multilayer perceptron (MLP)
speech–EEG analysis
Online Access:https://www.mdpi.com/1424-8220/23/19/8039

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https://www.mdpi.com/1424-8220/23/19/8039

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