ArticleScientific reports2026
A novel 3D region-based speller paradigm for BCI systems.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
This study proposes and evaluates a novel three-dimensional region-based (3D-RB) speller paradigm designed to enhance classification performance. EEG data were recorded from 15 participants using 32 channels. Classification accuracy was examined across both single electrodes and predefined electrode groups. Subject-dependent analyses revealed that electrodes located in the parietal and occipital regions (e.g., Pz, P7, P8, O1, O2, Oz) achieved the highest single-channel accuracies (approximately 80-85%), whereas central electrodes (e.g., Cz, C3, C4) yielded lower accuracies (around 70-73%). Electrode grouping provided a distinct advantage; for most participants, Group 4 (Parietal + Occipital) and Group 5 (Parietal + Occipital + Central) achieved the highest performance, reaching nearly 99% accuracy. Notably, despite including fewer electrodes, Group 4 performed nearly as well as Group 5, underscoring the practical benefit of optimized electrode selection. Subject-independent (LOSO) analyses showed similar trends. Among single electrodes, P7, P8, O1, and O2 achieved the highest accuracies (approximately 78-79%), while central electrodes (e.g., Cz, Cp1, Cp2, C3, C4) remained lower (70-73%). Electrode groups again outperformed single channels, with Group 4 and Group 5 reaching approximately 89-91% accuracy. The comparable performance of Group 4, despite fewer electrodes, highlights its practical advantage for real-world applications. Grand Average ERP analyses indicated that differences between target and non-target stimuli primarily emerged within early and mid-latency time windows, with these effects being more pronounced over parietal and occipital regions. Taken together, these findings demonstrate that incorporating three-dimensional visual effects within a region-based paradigm significantly enhances classification performance by leveraging parietal-occipital activity. The proposed 3D-RB paradigm therefore offers an efficient and user-friendly approach for future BCI speller designs.
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