Systematic Review of EEG-Based Imagined Speech Classification Methods
This systematic review examines EEG-based imagined speech classification, emphasizing directional words essential for development in the brain–computer interface (BCI). This study employed a structured methodology to analyze approaches using public datasets, ensuring systematic evaluation and valida...
        Saved in:
      
    
          | Main Authors: | Salwa Alzahrani, Haneen Banjar, Rsha Mirza | 
|---|---|
| Format: | Article | 
| Language: | English | 
| Published: | MDPI AG
    
        2024-12-01 | 
| Series: | Sensors | 
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/24/24/8168 | 
| Tags: | Add Tag 
      No Tags, Be the first to tag this record!
   | 
Similar Items
- 
                
                    Harnessing the Multi-Phasal Nature of Speech-EEG for Enhancing Imagined Speech Recognition        
                          
 by: Rini Sharon, et al.
 Published: (2025-01-01)
- 
                
                    Decoding Imagined Speech from EEG Data: A Hybrid Deep Learning Approach to Capturing Spatial and Temporal Features        
                          
 by: Yasser F. Alharbi, et al.
 Published: (2024-11-01)
- 
                
                    Stochasticity as a solution for overfitting—A new model and comparative study on non-invasive EEG prospects        
                          
 by: Yousef A. Radwan, et al.
 Published: (2025-01-01)
- 
                
                    Real-time classification of EEG signals using Machine Learning deployment         
                          
 by: Swati CHOWDHURI, et al.
 Published: (2024-12-01)
- 
                
                    EEG-Based Brain-Computer Interface Using Visual Flicker Imagination for Assistive Communication System        
                          
 by: Theerat Saichoo, et al.
 Published: (2024-01-01)
 
       