An exploratory study of fit assessment of the virtual reality glasses

The aim of this study is to establish an objective evaluation method for the VR glasses in the design process using fit test panels. Based on head width-length index and head height-length index in Chinese head and face 3D database, we get 9 categories using Fuzzy C-Means Clustering (FCM). Then, a fit test panels including 20 samples was established. According to the subjective evaluation of 20 subjects, the fit assessment scale of 5 regions was established. Then, the virtual fit assessment of a digital model of VR glasses padding in the design process and the traditional expert experience evaluation of its 3D printing model are carried out. The Results obtained by the objective evaluation method and the subjective evaluation were consistent. Results showed that the objective evaluation method was effective and had the characteristics of simplicity, rapidity and accuracy. It provides an effective decision tool for fitness prediction and improvement of the VR glasses padding in the design process.