A Brief Review of EEG-Based Brain-Computer Interfaces Using Endogenous Paradigms for Innovative Device Applications

Electroencephalography (EEG) is a cornerstone technology in biomedical and computer sciences, extensively utilized for monitoring and analyzing brain activity. Brain signals are fundamental to understanding neurological abilities, disabilities, and cognitive processes, making their analysis critical for predicting and interpreting human behavior. Advancements in EEG technology have revolutionized the ability to decode brain waves, driving the rapid development of brain-computer interfaces (BCIs). These non-invasive systems facilitate direct interaction between humans and external devices by interpreting brain activity. Modern neurotechnology has expanded BCI applications far beyond traditional medical and clinical settings, influencing areas such as rehabilitation, education, and gaming. This systematic review examines EEG-based BCIs utilizing the motor imagery (MI) paradigm. A thorough literature search across multiple databases identified relevant publications from 2010 onward using terms like "BCI," "motor imagery," and "EEG." Out of 223 studies, 92 unique papers remained after removing duplicates. Following title and abstract screening, 96 studies focusing on BCI development were selected, excluding those limited to theoretical discussions of EEG.