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The Association between Facial Morphology and Cold Pattern

  • Ahn, Ilkoo (Korean Medicine Data Division, Korea Institute of Oriental Medicine) ;
  • Bae, Kwang-Ho (Korean Medicine Data Division, Korea Institute of Oriental Medicine) ;
  • Jin, Hee-Jeong (Korean Medicine Data Division, Korea Institute of Oriental Medicine) ;
  • Lee, Siwoo (Korean Medicine Data Division, Korea Institute of Oriental Medicine)
  • Received : 2021.07.22
  • Accepted : 2021.10.15
  • Published : 2021.12.01

Abstract

Objectives: Facial diagnosis is an important part of clinical diagnosis in traditional East Asian Medicine. In this paper, using a fully automated facial shape analysis system, we show that facial morphological features are associated with cold pattern. Methods: The facial morphological features calculated from 68 facial landmarks included the angles, areas, and distances between the landmark points of each part of the face. Cold pattern severity was determined using a questionnaire and the cold pattern scores (CPS) were used for analysis. The association between facial features and CPS was calculated using Pearson's correlation coefficient and partial correlation coefficients. Results: The upper chin width and the lower chin width were negatively associated with CPS. The distance from the center point to the middle jaw and the distance from the center point to the lower jaw were negatively associated with CPS. The angle of the face outline near the ear and the angle of the chin line were positively associated with CPS. The area of the upper part of the face and the area of the face except the sensory organs were negatively associated with CPS. The number of facial morphological features that exhibited a statistically significant correlation with CPS was 37 (unadjusted). Conclusions: In this study of a Korean population, subjects with a high CPS had a more pointed chin, longer face, more angular jaw, higher eyes, and more upward corners of the mouth, and their facial sensory organs were relatively widespread.

Keywords

Acknowledgement

This work was supported by the "Development of Korean Medicine Original Technology for Preventive Treatment Based on Integrative Big Data" grant from the Korea Institute of Oriental Medicine (KSN2022120).

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