MEG Sensor Selection for Neural Speech Decoding

MEG Sensor Selection for Neural Speech Decoding

Direct decoding of speech from the brain is a faster alternative to current electroencephalography (EEG) speller-based brain-computer interfaces (BCI) in providing communication assistance to locked-in patients. Magnetoencephalography (MEG) has recently shown great potential as a non-invasive neuroi...

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Bibliographic Details
Main Authors: Debadatta Dash, Alan Wisler, Paul Ferrari, Elizabeth Moody Davenport, Joseph Maldjian, Jun Wang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Autoencoder
brain-computer interface
forward selection algorithm
magnetoencephalography
neural speech decoding
OPM
Online Access:https://ieeexplore.ieee.org/document/9214489/

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