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Systematic Review of EEG-Based Imagined Speech Classification Methods.

Salwa Alzahrani¹, Haneen Banjar¹, Rsha Mirza¹

¹Department of Computer Science, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia.

Sensors (Basel, Switzerland)

|January 8, 2025

Summary

This review explores electroencephalography (EEG) for brain-computer interfaces (BCIs) to classify imagined speech, especially directional words. Progress is noted, but challenges in generalizability and accuracy persist for practical communication tools.

Keywords:

BCI EEG brain–computer interfaces electroencephalogram imagined speech inner speech

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Area of Science:

Neuroscience
Biomedical Engineering
Computer Science

Background:

Brain-computer interfaces (BCIs) are crucial for assistive communication.
Electroencephalography (EEG) offers a non-invasive method for BCI development.
Imagined speech classification is a key area for BCI advancement.

Conclusions:

Despite progress, classifying directional words in imagined speech remains challenging.
Generalizability and scalability are key hurdles for subject-independent BCIs.
Future research should focus on advanced signal processing, neural networks, and adaptive BCI systems for practical communication.