This project presents a Real-Time Stress Monitoring and Analysis System using Arduino Nano and Raspberry Pi 4. A MAX30102 sensor measures the user's heart rate (HB) and SpO₂ levels, while a strain gauge sensor monitors mouse clicking pressure and usage patterns. A Pi Camera captures live video and performs facial recognition with a bounding box and expression detection such as Normal, Happy, and Sad. The Raspberry Pi analyzes physiological data, mouse behavior, and facial expressions to determine the user's stress level in real time. The stress status is displayed on an LCD and also monitored through a web interface with live video streaming. The system provides an intelligent and non-intrusive solution for stress monitoring in workplaces, healthcare, and research applications.    

The main objectives of this project are:

1. To monitor the user's stress level in real time.
2. To measure heart rate and SpO₂ using the MAX30102 sensor.
3. To detect mouse clicking force using a strain gauge sensor.
4. To capture and analyze facial expressions using a Pi Camera.
5. To perform facial recognition with bounding box and emotion detection.
6. To display stress status and physiological parameters on an LCD.
7. To provide live video streaming and stress monitoring through a web interface.
8. To store monitoring data for future analysis and reference.

      The major building blocks of this project are:  

1. Adapter power supply.
2. Raspberry pi4.
3. Arduino Nano.
4. SD card.
5. LCD display.
6. MAX30102 Sensor.
7. Strain gage sensor.
8. Pi camera.

  Software’s used:  

• Raspbian OS.
• Express SCH for Circuit design.
• Web technology.

     

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