Our project focuses on improving healthcare and safety for individuals—especially those with Parkinson’s disease—by detecting and predicting fall risks. Using datasets with gyroscope sensor values, our model analyzes gait patterns to determine when a person is at high risk of falling. While we currently rely on pre-recorded sensor data, the real-world implementation will use live data from wearable sensors for continuous monitoring and early fall detection.
Built With
- angular.js
- colab
- css3
- html5
- javascript
- node.js
- tailwind
Log in or sign up for Devpost to join the conversation.