A New Method of Diagnosing Constitutional Types Based on Vocal and Facial Features for Personalized Medicine

The aim of the present study is to develop an accurate constitution diagnostic method based solely on the individual's physical characteristics, irrespective of psychologic traits, characteristics of clinical medicine, and genetic factors. In this paper, we suggest a novel method for diagnosing constitutional types using only speech and face characteristics. Based on 514 subjects, the area under the receiver operating characteristics curve (AUC) values of classification models in age and gender groups ranged from 0.64 to 0.89. We identified significant features showing statistical differences among three constitutional types by performing statistical analysis. Also, we selected a compact and discriminative feature subset for constitution diagnosis in each age and gender group. Our method may support the direction of improved diagnosis prediction and will serve to develop a personal and automatic constitution diagnosis software for improvement of the effectiveness of prescribed medications and development of personalized medicine.

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