SENSI EEG PREPROC — Bad-Channel Detection Module Version v1.0.0 — Initial Public Release This is the first public release of the Bad-Channel Detection Module. This version corresponds to the codebase described in the accompanying preprint: Amilcar J. Malave and Blair Kaneshiro (2026). EEG Bad-Channel Detection Using Multi-Feature Thresholding and Co-Occurrence of High-Amplitude Transients. bioRxiv. https://doi.org/10.64898/2026.02.04.703874 Dataset: Amilcar J. Malave and Blair Kaneshiro (2025). Example EEG data for the SENSI EEG PREPROC Bad-Channel Detection Module [Data set]. Stanford Digital Repository. https://doi.org/10.25740/dg856vy8753 Included in this Release markSusChs.m (main user entry point) Multi-feature suspiciousness scoring: Neighbor dissimilarity Amplitude screening Variance-based measures High-amplitude transient clustering via Jaccard-like similarity Interactive review interface (reviewBadChsUI) Example workflow (example.m) User Manual (PDF) Intended Usage This Module is designed as a quality-control step prior to ICA and downstream EEG analyses. It emphasizes interpretability and human-in-the-loop validation rather than fully automated rejection. MATLAB Requirements MATLAB R2024b (tested) Statistics and Machine Learning Toolbox Notes This release represents the first stable public version of the Module. Future releases may refine clustering behavior, visualization outputs, and parameter defaults. This version should be cited when referencing the v1.0.0 implementation.