###### Abstract  
Hypertension has been a crucial public health challenge among adults. This study aimed to develop a novel method for non-contact prediction of hypertension using facial characteristics such as facial features and facial color. The data of 1099 subjects (376 men and 723 women) analyzed in this study were obtained from the Korean Constitutional Multicenter Study of Korean medicine Data Center (KDC) at the Korea Institute of Oriental Medicine (KIOM). Facial images were collected and facial variables were extracted using image processing techniques. Analysis of covariance (ANCOVA) and Least Absolute Shrinkage and Selection Operator (LASSO) were performed to compare and identify the facial characteristic variables between the hypertension group and normal group. We found that the most distinct facial feature differences between hypertension patients and normal individuals were facial shape and nose shape for men in addition to eye shape and nose shape for women. In terms of facial colors, cheek color in men, as well as forehead and nose color in women, were the most distinct facial colors between the hypertension groups and normal individuals. Looking at the AUC value, the prediction power for women is better than men. In conclusion, we managed to explore and identify the facial characteristics variables related to hypertension. This study may provide new evidence in the validity of predicting hypertension using facial characteristics.  
facial characteristics; facial color; facial features; hypertension; screening 2021 12 2021 11 2021 12 2021 12 2021 12 2021 12 2021 12 2021 202  
Apart from the classic BP measurement, recent technologies have provided new potential for the evaluation of various parameters such as vital signals, speech analysis, heart rate, and step count [4]. Several studies have utilized signal-derived BP measurement such as photoplethysmogram and electrocardiogram signals as the indicators of BP [5; 6; 7]. A recent study also proposed that BP can estimate using acoustic characteristics [8]. Such novel strategies are also gradually being developed to be compatible with smartphone health applications and wearable devices.  
The face is the most observed region in a person's lifetime and perception of a person's health according to their facial appearance is a day-to-day occurrence. Numerous attempts have been made by researchers to find the association between facial appearance and health for decades [9]. Recent studies have been focusing on facial shape to investigate the elements of faces that affect the perception of health [10]. A study on craniofacial anthropometry found that the face has many manifestations associated with increased susceptibility to specific diseases and any distinct changes in face can be an indication of a health issue [11]. There are also studies that are associated with facial shape with the diagnosis of diseases where morphological characteristics in facial shape can be related to the presence of diabetes and hypertension [12; 13; 14]. Current approaches also showed that skin color and texture contribute to facial health. Moreover, many studies have been conducted to elucidate the association between skin color and hypertension [15; 16].  
In this study, we proposed that facial characteristics such as facial features or facial color can be used for hypertension screening in a non-contact, unconscious, and labor-free manner. Facial characteristics that are extracted from facial images through image processing techniques may be indicative of hypertension and have the potential to play a daily role in self-screening of hypertension. This study aimed to develop a novel method by determining the possibility of predicting hypertension using facial characteristics.