Abstract
A detailed data of shape of auricular concha is currently not available. Therefore, this study constructed a framework to statistically analyze the shape of the auricular concha based on a database of 3D scanned images. The 3D models of the auricular concha from 308 study participants are converted into compatible NURBS surfaces generated through 795 data points to perform a requisite statistical analysis. Subsequently, the shape of the auricular concha of the participants is grouped into 29 clusters with a modified hierarchical clustering algorithm. Finally, a wear trial and simulation test are carried out to validate the wear comfort of a designed OTC hearing aids based on the average shape of each cluster. The experimental results show that the average shape obtained as per the cluster is capable of representing the common geometric properties of their corresponding members, and could thus be used as a reference in designing mass-customized OTC hearing aid. The method in this study is superior to conventional methods that rely on sparse results for shape analysis because it takes into account the intricate geometric shape of the auricular concha. The quantitative description of conchal morphometry will be beneficial for plastic surgeons, and for the ergonomic design of ear-related products.
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