A 2-D Visual Model for Sasang Constitution Classification Based on a Fuzzy Neural Network
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 %.
KeywordsSasang constitution Tae-Yang (太陽) So-Yang (少陽) Tae-Eum (太陰) So-Eum (少陰) Ryodoraku (良導絡) Fuzzy neural network
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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