Developed a core enhancement for the UniversumX/Universum repository by integrating a Wiener filter into the EEG preprocessing pipeline, enabling explicit evaluation of signal quality improvements. Leveraging Python and expertise in data preprocessing and signal processing, the work introduced utilities to compute and compare Signal-to-Noise Ratio (SNR) before and after filtering, supporting quantitative assessment of preprocessing effectiveness. The filter implementation was refactored into the main preprocessing function to improve code maintainability and clarity. This update allows users to directly measure the impact of filtering on EEG data, facilitating data quality assurance and more robust machine learning workflows within the pipeline.