Predicting facial deformation during respiratory mask fitting with semi-supervised graph neural networks
Abstract
. Five-fold cross-validation confirms robust generalization with minimal overfitting and sub-2-second inference time. This study introduces a real-time personalized respiratory mask model, achieving precise prediction of facial deformation and contact pressure. The approach ensures generalization from limited labeled data, thereby improving comfort, safety, and compliance in medical and industrial applications.
Fields of Study & Subjects
Face recognition and analysis
Infection Control and Ventilation
Non-Invasive Vital Sign Monitoring
Publication details
- Journal / source
- Medical Engineering & Physics
- Volume
- 147
- Issue
- 2
- Pages
- 025014–025014
- Publication date
- 28 January 2026
- Language
- EN