Automatic Fall Detection system for patients with Parkinson's disease

This project presents an integrated sensor system designed to monitor patients suffering from Parkinson's disease and provide vital signal monitoring, as well as fall detection capabilities. The system combines Arduino-based sensor interfacing with MEMS sensors, heartbeat, and temperature sensors to ensure comprehensive patient monitoring. The core components of the system consist of MEMS sensors, which capture position data to identify symptoms of Parkinson's disease. Additionally, a heartbeat and temperature sensor is employed to continuously monitor the patient's vital signals, ensuring timely response to any alarming variations.

In the event of a fall, the MEMS sensor detects sudden changes in orientation and triggers an alert system. The Arduino microcontroller processes this information and activates a GSM module to send a text message to predefined contacts, notifying them of the fall. Simultaneously, the system employs an LCD display to present sensor readings, offering a visual representation of the patient's condition. Furthermore, an audible alert is generated through a buzzer to provide immediate on-site awareness. This integrated sensor system not only aids in identifying the symptoms of Parkinson's disease but also enhances patient safety by detecting falls and transmitting alerts promptly. It offers a versatile and reliable solution for continuous monitoring and timely intervention, ultimately improving the quality of care for Parkinson's disease patients.

Keywords: Arduino, MEMS Sensor, Heartbeat Sensor, Temperature Sensor, LCD.