The Landscape of Machine Learning for EEG Hand Motor Imagery Decoding: A Scoping Review (2020-2025) - Bitencourt, Felipe Correa; Pereira, Eduarda Tessari; Salvalaio, Claudio; Borges Junior, Voltaire Augusto; Lacerda, Marcelo Scarparo; Lima, Alexandre; Oliveira Jr, Alcyr Alves de (Anais da Escola Regional de Aprendizado de Máquina e Inteligência Artificial da Região Sul (ERAMIA-RS), 2025)
EEG-based Brain-Computer Interfaces (BCIs) show promise for motor rehabilitation, with hand motor imagery (MI) being a key paradigm. This scoping review analyzed 128 studies, mapping machine learning and deep learning architectures, training strategies, and performance metrics. Results reveal predominance of deep learning, and methodological diversity, but most studies are offline and subject-dependent, limiting reproducibility and real-time application. The review aims to highlight gaps and standardized evaluation protocols to advance practical BCIs.