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IMU Sensors Based Parkinson's Detection Model
Advanced machine learning model analyzing 400,000+ smartwatch IMU sensor records to detect Parkinson's disease with ensemble classification achieving +8% accuracy boost.
Project Demo Video
The Problem
Early detection of Parkinson's disease requires expensive clinical tests and specialist consultations.
How it Works
Leverage smartwatch IMU sensors with heavy feature engineering and ensemble ML models (Logistic Regression, Random Forest, XGBoost) for non-invasive early detection.
Future Improvements
- Optimize performance for real-time processing.
- Add support for multi-user collaboration.
- Integrate cloud storage for data persistence.
Tech Stack
Pythonscikit-learnXGBoostPandasNumPyGPU Computing
Links
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