Fall Detection

Full title: Mobile E-Health Application using Wireless Sensors.
This project involved the design and implementation of a mobile e-health application that detects falls in real time using smartphone's built-in motion sensors (accelerometer and gyroscope).
It aimed at supporting elderly individuals or patients at risk of falling.
The system is designed to run as a background service, enabling continuous monitoring even when the app is not open, without interrupting the user's normal smartphone usage.
The app provides an accessible, low-cost solution for real-time monitoring and emergency response without requiring external devices.
Utilized the smartphone's onboard accelerometer and gyroscope to continuously monitor user movement and orientation.
Implemented a fall detection algorithm that identifies sudden acceleration changes, and post-fall inactivity to differentiate real falls from normal movements.
When a fall is detected, the app immediately displays an on-screen window asking the user to confirm if they are OK. This allows false positive to be canceled by the user.
If the user does not respond within a defined timeout, the app sends an alert notification along with the user's location to a predefined list of emergency contacts.