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Design Customization of Respiratory Mask based on 3D Face Anthropometric Data
Chih-Hsing Chu,Szu-Hao Huang,Chih-Kai Yang,Chun-Yang Tseng 한국정밀공학회 2015 International Journal of Precision Engineering and Vol. No.
This study presents a machine learning based method for design customization of a 3D respiratory mask. A parametric model of a3D human face was constructed from an anthropometric database consisting of 495 facial models. An AdaBoost.R algorithm wasapplied to identify a set of measurable parameters most related to the facial geometry. The correlation between parameters wasestimated using principal component analysis and linear regression. With those parameter values as input, the parametric modelgenerates 3D meshes of a human face that serve as a design reference for the construction of a customized respiratory mask of agood fit. We conducted a series of experiments with 10-fold cross-validation to validate the effectiveness of the proposed method.