About Oxzi
Project Overview
Oxzi is an innovative AI-powered application designed to measure and evaluate key health metrics such as blood oxygen saturation (SpO2), heart rate, and stress levels through non-contact facial analysis. Developed by a team of students from Prince Royal's College, this project aims to revolutionize health monitoring, especially in emergency situations and remote areas.
Key Features
Utilizes facial analysis to measure health metrics without physical contact, reducing infection risks.
Provides instant health data through advanced image processing and AI algorithms.
Designed for ease of use, making it accessible for both medical professionals and the general public.
Ideal for quick health assessments in emergency situations or remote areas with limited medical resources.
Technology
Oxzi leverages cutting-edge technologies including:
- Photoplethysmography (PPG) for analyzing light reflection changes on the skin
- Fourier Analysis for separating pulse signals from noise
- Convolutional Neural Networks (CNN) for enhancing accuracy and reducing data errors
- Time Series Analysis for examining pulse rate changes over time
- Linear Regression for evaluating relationships between measured signals and standard values
Project Impact
Oxzi has the potential to significantly impact healthcare by:
- Providing quick and accurate health assessments in emergency situations
- Reducing the risk of infection transmission in medical settings
- Enabling remote health monitoring in areas with limited medical resources
- Promoting preventive healthcare through easy-to-use technology
Future Development
The Oxzi team is committed to continuous improvement and expansion of the project, including:
- Enhancing AI models for even greater accuracy
- Expanding the range of health metrics that can be measured
- Integrating with IoT devices for comprehensive health monitoring
- Collaborating with healthcare providers for real-world implementation and validation