Fall Detection

The project aims to detect when an elder falls based on biomedical signal data collected from wearable sensors.

• Researched signal processing and machine learning algorithms for fall detection
• Visualized, pre-processed and annotated the signal data to create a labelled dataset ready for analysis
• Implemented data science pipeline to extract time-domain & frequency-domain features, train machine learning models, and evaluate the models’ performance with Python and Scikit-learn