The Webcam Pulse Reader is a stand-alone Python-based application that utilizes the power of machine learning, computer vision, and signal processing techniques to detect the pulse rate of an individual through a webcam. By employing the Fast Fourier Transform (FFT) approach, the application can analyze subtle color changes in the individual's face, which correspond to changes in blood flow caused by the heartbeat.

• Real-time pulse rate detection: The application continuously analyzes the video stream from the webcam and accurately calculates the pulse rate in real time.
• Webcam integration: The application seamlessly captures video frames from the webcam, eliminating the need for additional hardware.
• Fast Fourier Transform (FFT): By utilizing FFT, the application transforms the color intensity variations in facial regions into the frequency domain, allowing for precise pulse rate estimation.
• Machine Learning: The application employs machine learning algorithms to enhance the accuracy of pulse rate detection by adapting to different skin tones, lighting conditions, and camera qualities.
• Graphical User Interface (GUI): The application provides an intuitive GUI to display the live video stream, pulse rate readings, and additional visualizations.

• Python: The core programming language used to develop the application.
• OpenCV: A popular computer vision library that provides functions for capturing video frames from the webcam and performing image processing tasks.
• OpenMDAO: An open-source framework for multidisciplinary analysis and optimization, which can be utilized to optimize and fine-tune the pulse rate detection algorithms.
• Machine Learning Libraries: Various machine learning libraries such as scikit-learn, TensorFlow, or PyTorch can be integrated to enhance the application's performance.
• NumPy: A fundamental package for scientific computing in Python, extensively used for mathematical operations and array manipulation.
• Matplotlib: A plotting library that enables the creation of visualizations to display the pulse rate readings and other relevant data.

1. Clone the repository:

   git clone https://github.com/sourrinn/webcam-pulse-reader.git

2. Run the application:

• Run the stand-alone application "get_pulse.exe".

1. Launch the application using the provided installation instructions.
2. Ensure that your webcam is connected and properly configured.
3. Position yourself in front of the webcam and ensure that your face is well-illuminated and visible to the camera.
4. The application will start detecting and analyzing your pulse rate in real-time.
5. The GUI will display the live video stream, pulse rate readings, and any additional visualizations or data as configured.

Contributions to the Webcam Pulse Reader are welcome! If you have suggestions for new features, improvements, or bug fixes, please open an issue or submit a pull request. For major changes, please discuss the proposed changes with the repository owners first.

Apache 2.0

The Webcam Pulse Reader application builds upon various open-source projects, research papers, and libraries. We acknowledge their contributions and appreciate the collective efforts of the developer community in advancing this field.

If you use this application in your research or projects, please consider citing this repository.

For any questions, suggestions, or collaborations, please feel free to contact the repository owner(s) or open an issue in the GitHub repository. We value and appreciate your feedback!