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

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.

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Publication Details

Journal
Ergonomics
Published
2025-02-06
DOI
https://doi.org/10.1080/00140139.2025.2458631
Citations
1
Primary Topic
Nasal Surgery and Airway Studies
Type
article
Field-Weighted Citation Impact
2.01

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article

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

Ke Zeng, Kexiang Liu, Haining Wang, Yan Yan
1 citations
Ergonomics
Nasal Surgery and Airway Studies
2.01
article

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

Ke Zeng, Kexiang Liu, Haining Wang, Yan Yan
article en
1 citations

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.

ErgonomicsVol. 69(2)
Beijing Institute of Fashion Technology (CN), Hunan University (CN)
National Key Research and Development Program of China
Openalex Percentile: Top 19%
Nasal Surgery and Airway Studies
2.01
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Statistical shape analysis of the Chinese external ear for ergonomic design of in-ear products — Ke Zeng, Kexiang Liu, et al. · Ergonomics (2025) | TGRS Research Map | TGRS