A Window Analysis for the Decoding of Premovement and Movement Intentions in Freewill EEG

Decoding movement-related intentions from electroencephalogram (EEG) is important for developing real-time brain machine interfaces (BMIs). While most studies focus on cue-based tasks in EEG-based BMIs, freewill reaching and grasping tasks allow subjects to initiate movements of their own will, making them relevant to practical EEG-based BMIs. However, the investigation of EEG window size for decoding freewill movements remains unexplored. This study systematically analyzes the effect of different window sizes on decoding EEG premovement (prior to the movement onset) and movement (after movement initiation) intentions in freewill reaching and grasping tasks. We used 49 EEG recordings from 23 subjects, and EEG windows of 0.1-1s in 0.1s increments were analyzed within the range of -3 to 3s relative to the movement onset at 0. Decoding was performed using regularized linear support vector machine (LSVM) and regularized linear discriminant analysis (RLDA), and performance was evaluated in terms of accuracy. Larger window sizes consistently outperformed smaller ones, with peak accuracy occurring between 0-1s relative to the movement onset. LSVM outperformed RLDA across all 10 window sizes, with peak accuracy ranging from 86.98% with 0.1s window to 90.94% with 1s window. Using LSVM, the earliest peak accuracy (90.03%) was achieved with a 0.7s window starting at 0.35s after the movement onset. Notably, a 0.5s window provided a peak accuracy of 89.5% which is not statistically significant compared to the 0.7s window (p = 0.05). The start point of the 0.5s window was 0.5s after the onset. With LSVM, considering the trade-off between decoding accuracy and latency, the 0.5s window offers the optimal choice for decoding movement intention in freewill EEG.Clinical relevance- Identifying the optimal window size to decode movement-related intentions in freewill EEG can help improve strategies to develop real-time BMIs for individuals with motor impairments.