Real-Time Wellness Monitoring Using Computer Vision
Developed an AI-powered system that analyzes facial expressions to detect stress levels in real time, enhancing employee wellness monitoring.
The Challenge
Traditional stress assessments require physical consultations or subjective self-reporting, limiting accessibility and real-time intervention. There was a need for a non-invasive, scalable solution that could assess stress levels instantly, especially for mental wellness apps and remote healthcare tools.
The Solution
iCubes built an AI-based facial gesture recognition system that detects stress levels by analyzing micro-expressions in real time. Using a mobile camera, the system captures and interprets facial features to determine a person’s stress index (e.g., Low, Moderate, High).
The solution uses CNN-based deep learning models trained on emotion datasets, integrated with OpenCV and TensorFlow for real-time facial landmark detection and expression mapping.
- AI/ML ModelsConvolutional Neural Networks (CNN)
- LibrariesTensorFlow, OpenCV
- HardwareStandard Mobile Camera
- PlatformMobile App Integration (iOS/Android compatible)
Non-invasive Stress
Detection in under 5 seconds
Mobile-Friendly
works via standard front-facing
90% Accuracy
Trained Emotional Datasets
No Wearables Needed
frictionless experience for users
Have a project in mind or questions about our services? We’re here to help you turn ideas into impactful digital solutions tailored to your business needs.
Call Us
+44 (0)7586697547
Email Id
sales@i-cubes.net