README

This project presents a computer vision-based method for the screening of Parkinson’s disease. We specifically focus on detecting bradykinesia, a core motor symptom, by analyzing finger tapping performance. Using simultaneous bilateral finger tapping, we extract motion features from video recordings and assess the presence of motor slowing patterns associated with Parkinson’s disease. The provided Jupyter Notebook includes the full pipeline: video processing, feature extraction, and classification. This work aims to support early and accessible screening of Parkinson's disease through non-invasive, vision-based assessment techniques.