Development of a Parametric Model of Adult Human Ear Geometry

Abstract

Quantitative knowledge regarding the size and shape of the human ear is valuable for the design of hearing protection and audio devices. Prior studies have used primarily landmark-to-landmark measurements rather than a three-dimensional analysis. To address the need for a parametric, high-resolution, three-dimensional model of adult ear geometry, a retrospective analysis of computed tomography (CT) scans from a patient database was conducted. The geometry of the pinna, canal, and adjacent scalp was extracted in skull-based coordinates for 331 ears from 224 men and women ages 18 to 81 years. A template polygonal mesh with 60040 vertices was fit to the geometry with a median distance error across ears of 0.03 mm and a median 99.9th percentile distance error of 0.44 mm. Principal component analysis demonstrated a large amount of variance not previously quantified in the position and orientation of the ears with respect to the skull. A regression analysis confirmed previous findings of sex differences in the increase of ear size with increasing age and also demonstrated an effect of body mass index on ear position and orientation that has not been previously described. A boundary method in principal component space was used to generate a set of ears suitable for designing devices for which the ear position on the head is important. Boundary ears were also generated in pinna-centered coordinates for applicability to in-ear device design, demonstrating the flexibility of the dataset and analysis methodology. To our knowledge, this study developed the largest and highest-resolution database of human ear geometry, the first to be measured in head-centered coordinates, and the first to include the geometry of the canal to the ear drum. Future work is needed to extend the applicability to populations not well represented in the current database.