Brain-Computer Interaction: A Scoping Review of Current Advances, Challenges, and Future Research Directions

The term Brain-Computer Interaction (BCIx) is used to denote a paradigm that is characterized by the use of an adaptive and bidirectional communication link between the brain and computers. A literature search was performed in all major scientific databases in order to identify peer-reviewed articles on the subject. The search was successful in identifying 28 articles published until May 2026. A variety of BCIx applications have been examined, such as emotion detection, imagery, motor execution, neuro-rehabilitation, multimodal and networked BCIs, advancements in EEG decoding, methods for data augmentation, and novel hardware implementations. The studies have revealed advancements at a remarkable pace, driven by deep learning, multimodal sensing and advanced signal processing, although considerable issues remain, namely inconsistent terminology; small data sets; inter- and intra-subject variabilities, and real-world robustness issues. This review emphasizes the requirement for clearer conceptualization, standardized methodology, and interdisciplinary cooperation to address these issues.