Date: November 2023.
Source: Proceedings of Korean Institute of Information Technology (KIIT) Autumn Conference, Pages 563-566.
Abstract: The ergonomic insights into human dimensions are pivotal in the development of user-friendly wearable devices. In this study, we apply the Self-Organizing Map (SOM) clustering technique to 3D ear scan data of Korean individuals. We statistically compare and validate the features of the average ear specifications and models extracted from these clusters. Through this, we aim to understand the specific characteristics of Korean ear morphologies, providing insights for ear data analysis and suggesting directions for wearable product design.

Article: Analysis and Data Clustering of 3D Ear Morphology for the Development of Customized Wearable Products
Analysis and Data Clustering of 3D Ear Morphology for the Development of Customized Wearable Products.
Authors: Jo-el Shin, Seok-beom Jang, Jeong-ho Kim, Dong-min Kim, Ye-jeong Kim, Won-seop Lee. Handong Global University.

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