Beijing Sport University Model Gains Lose Significance Under Broader Statistical Correction
Researchers at Beijing Sport University developed a motor imagery EEG decoding model and evaluated it offline on three public datasets using subject-specific and cross-subject protocols. Against the baseline with the highest mean accuracy, subject-specific gains on two datasets were 3.56 and 1.62 percentage points; another cross-subject comparison showed a 2.08-point difference. These three comparisons had statistical support after correction within their respective settings, but none remained significant under a broader correction covering 56 comparisons. The findings offer limited support for integrating local and longer-range EEG information in stages, rather than establishing benefits for online control or clinical use.
