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A 2-D Visual Model for Sasang Constitution Classification Based on a Fuzzy Neural Network

  • Zhen-Xing Zhang
  • Xue-Wei Tian
  • Joon S. Lim
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 215)

Abstract

The human constitution can be classified into four possible constitutions according to an individual’s temperament and nature: Tae-Yang (太陽), So-Yang (少陽), Tae-Eum (太陰), and So-Eum (少陰). This classification is known as the Sasang constitution. In this study, we classified the four types of Sasang constitutions by measuring twelve sets of meridian energy signals with a Ryodoraku device (良導絡). We then developed a Sasang constitution classification method based on a fuzzy neural network (FNN) and a two-dimensional (2-D) visual model. We obtained meridian energy signals from 35 subjects for the So-Yang, Tae-Eum, and So-Eum constitutions. A FNN was used to obtain defuzzification values for the 2-D visual model, which was then applied to the classification of these three Sasang constitutions. Finally, we achieved a Sasang constitution recognition rate of 89.4 %.

Keywords

Sasang constitution Tae-Yang (太陽) So-Yang (少陽) Tae-Eum (太陰) So-Eum (少陰) Ryodoraku (良導絡) Fuzzy neural network 

Notes

Acknowledgments

This research was supported by the MKE (The Ministry of Knowledge Economy), Korea, under the Convergence-ITRC (Convergence Information Technology Research Center) support program (NIPA-2012-H0401-12-1001) supervised by the NIPA (National IT Industry Promotion Agency).

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.School of Information & Electric EngineeringLudong UniversityYanTaiChina
  2. 2.IT College, Gachon UniversitySeongnamSouth Korea

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