SUMMARY AI summary by gpt-5-mini
This repository implements an AI/computer-vision pipeline to analyze movement patterns associated with Parkinson’s Disease using hand and body landmarks. It was developed as a university group project for research, demonstration, and testing by students, researchers, and developers working on healthcare-related AI. Key features: - Hand landmark detection and pose estimation (MediaPipe) - Coordinate extraction, motion tracking and signal/feature generation - Movement-pattern analysis and machine‑learning evaluation (confusion matrix, precision‑recall) - Real‑time visualization and Jupyter notebooks for experiments Tech stack: Python, OpenCV, MediaPipe, YOLOv5, ML libraries. Workflow: video input → detection → landmark extraction → feature processing → ML analysis → visualization. Notes: contributions include documentation, feature-extraction design, testing; planned improvements include larger datasets, deep models, and a user interface.
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Owner
BSc (Hons) Artificial Intelligence Student | Machine Learning & Computer Vision Enthusiast | Python | AI Projects | Open to Opportunities
Dates
| Created on GitHub | 2026-05-12 |
| Last push | 2026-05-12 |
| First seen here | 2026-05-12 |
| Last fetched | 2026-05-13 16:10 |
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