A state-of-the-art review of EEG-based imagined speech decoding

D Lopez-Bernal, D Balderas, P Ponce… - Frontiers in human …, 2022 - frontiersin.org
Currently, the most used method to measure brain activity under a non-invasive procedure is
the electroencephalogram (EEG). This is because of its high temporal resolution, ease of …

Neurolinguistics research advancing development of a direct-speech brain-computer interface

C Cooney, R Folli, D Coyle - IScience, 2018 - cell.com
A direct-speech brain-computer interface (DS-BCI) acquires neural signals corresponding to
imagined speech, then processes and decodes these signals to produce a linguistic output …

Neural decoding of imagined speech and visual imagery as intuitive paradigms for BCI communication

SH Lee, M Lee, SW Lee - IEEE Transactions on Neural …, 2020 - ieeexplore.ieee.org
Brain-computer interface (BCI) is oriented toward intuitive systems that users can easily
operate. Imagined speech and visual imagery are emerging paradigms that can directly …

Evaluation of hyperparameter optimization in machine and deep learning methods for decoding imagined speech EEG

C Cooney, A Korik, R Folli, D Coyle - Sensors, 2020 - mdpi.com
Classification of electroencephalography (EEG) signals corresponding to imagined speech
production is important for the development of a direct-speech brain–computer interface (DS …

Implementing a fuzzy inference system in a multi-objective EEG channel selection model for imagined speech classification

AA Torres-García, CA Reyes-García… - Expert Systems with …, 2016 - Elsevier
One of the main purposes of brain-computer interfaces (BCI) is to provide persons of an
alternative communication channel. This objective was firstly focused on handicapped …

A bimodal deep learning architecture for EEG-fNIRS decoding of overt and imagined speech

C Cooney, R Folli, D Coyle - IEEE Transactions on Biomedical …, 2021 - ieeexplore.ieee.org
Objective: Brain-computer interfaces (BCI) studies are increasingly leveraging different
attributes of multiple signal modalities simultaneously. Bimodal data acquisition protocols …

The role of artificial intelligence in decoding speech from EEG signals: a scoping review

U Shah, M Alzubaidi, F Mohsen, A Abd-Alrazaq, T Alam… - Sensors, 2022 - mdpi.com
Background: Brain traumas, mental disorders, and vocal abuse can result in permanent or
temporary speech impairment, significantly impairing one's quality of life and occasionally …

[HTML][HTML] Opportunities, pitfalls and trade-offs in designing protocols for measuring the neural correlates of speech

C Cooney, R Folli, D Coyle - Neuroscience & Biobehavioral Reviews, 2022 - Elsevier
Decoding speech and speech-related processes directly from the human brain has
intensified in studies over recent years as such a decoder has the potential to positively …

Classification of imagined spoken word-pairs using convolutional neural networks

C Cooney, A Korik, F Raffaella… - The 8th Graz BCI …, 2019 - pure.ulster.ac.uk
Imagined speech is gaining traction as a communicative paradigm for brain-computer-
interfaces (BCI), as a growing body of research indicates the potential for decoding speech …

A survey on EEG-based imagined speech classification

AA Torres-García, CA Reyes-García… - … and Classification Using …, 2022 - Elsevier
Allowing communication in those situations in which the use of the voice or other human
expressive means is not possible is one of the main objectives of two broad research areas …