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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.
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.
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.
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