Smartphone Application for Mask Sizing and Projecting Quantitative Fit

Typical procedures for respirator masks sizing and protective fit test are time-consuming and user intensive, requiring taking anthropometricmeasurements of the wearer, sampling the wearers breathing zone and the use of specialized tools and equipment. The proposed softwareapp aims to quickly, accurately and automatically perform respirator mask sizing and predict protective fit using only 2D images captured onsmartphone cameras, thereby replacing the lengthy physical testing procedures and can even be performed in the field when needed. InPhase I, personalized 3D facial surfaces are generated through shape reconstruction in real-time from captured 2D images. Common facialanthropometric measurements are automatically extracted from the mesh and are then used to predict respirator mask size according toNational Institute for Occupational Safety and Health (NIOSH respirator test fit panels. Preliminary validation showed 5.1% facialanthropometric feature prediction error. Phase II will involve the development of individualized respiration models to simulate the movementof air and particulates through the mask and into the lungs in order to predict quantitative fit factor. Further validation studies will also beperformed to ensure the accuracy of the app predictions.