## 2 Materials and Methods
### Measurements  
Our experiments used several types of variables, such as facial shape and color, voice signal, tongue color, questionnaire, and anthropometry. For facial characteristics and color measurements, the 3D face model of the participant was scanned at various viewing angles using an RGB-D camera (Intel(r) RealSenseTM Depth Module SR300) to extract the morphological profiles and colors of the face [20; 21; 22]. Each participant was requested to open his/her eyes, close his/her mouth and maintain a neutral expression in a fixed posture during the 3D scan. The 3D facial features were extracted after image preprocessing, based on the iterative closest point (ICP) algorithm [20]. From the 3D face image, many facial features were selected, such as overall face outline, eyebrow, medial/lateral canthus, pupil, nasal tip/base, and lip fissure, in front and profile view angle. The vertical and horizontal distance variables were calculated using the facial features [16; 17; 23].  
For tongue color measurement, tongue images were acquired by a computerized tongue image acquisition system (TAS-4000, Korea Institute of Oriental Medicine, Daejeon, Korea). The tongue images were divided into root, center, side, and tip areas after the color correction step was performed. Each area was divided into tongue body and coating areas by specific color value thresholding [24]. Since the center and the tip area often had a small proportion of coating area, these areas were analyzed as whole areas, not divided into the tongue body and coating area. Images of the tongue body, coating of each tongue area and teeth marks are shown in the Supplementary Materials (Figures S1 and S2). All the color features are represented by the Commission Internationale de L'eclairage (CIE) L*a*b* color space. The mean values of the three-color components were set to the values representing the characteristics of the tongue in each area. In addition to the color value, the ratio of the coated area and strength of the teeth marks [25] were also used as tongue features. Detailed explanations of facial features and tongue color showed in the Supplementary Materials (Figures S1 and S2).  
For voice measurement, voice recording was performed in a room with a noise level below 40 dB. The subjects sat comfortably and were able to maintain the speed and lip opening as they naturally speak. They were asked to pronounce five vowels (\"a\", \"e\", \"i\", \"o\", \"u\") with a certain amount of power. Then, a sentence was pronounced twice. We extracted candidate vocal features, including fundamental frequencies, MFCC (Mel-frequency cepstral coefficients), and duration time. A detailed feature list is found in [26].  
For anthropometry and questionnaires, body weight and height of subjects were measured to the nearest 0.1 kg and 0.1 cm, respectively, with very lightweight clothing and without shoes, and body mass index was calculated using weight and height. Circum-ferences of each subject's body were measured at eight positions: forehead, neck, axilla, chest, ribs, waist, pelvis, and hips. Based on these 8 circumferences, we created several variables (circumference ratios) through calculation of circumference ratios between two positions, such as waist-to-hip circumference ratio and neck-to-waist circumference ratio.  
Detailed information on this anthropometry measurement has been described in previous studies [27; 28; 29; 30; 31]. The questions of questionnaire used in this study are described in Table 2.