Statistical shape analysis of the Chinese external ear for ergonomic design of in-ear products.

Abstract

3D scanning capture complex ear morphology, but most research focuses on dimensions defined by product design or ergonomic guidelines, often missing crucial 3D details, especially those of ear canal for in-ear product design. This study conducted a statistical shape analysis on the 3D geometry of the cavum concha and the external auditory meatus (EAM) using 1195 scans of Chinese ears. A surface registration method was adopted to standardise and align ear models for shape analysis. Principal component analysis (PCA) generated statistical models of ear shapes, with the most significant variation reflecting the overall width of the cavum concha, explaining 29.63% of the variation. The k-means++ algorithm was employed to classify ear shapes using the first 15 principal component scores, identifying four shape categorisations. Significant variations and shape modes of ear shape were identified, and the derived statistical shape models provide essential 3D references for the ergonomic design of ear-related products.