Facial Expressions of Pain Among Patients in the Emergency Department

Abstract Objective: The use of facial expression tracking to measure pain in patients in an emergency clinical setting has not been used before. This study examined facial expressions via an action unit (AU)-based model to determine the pain levels of emergency department (ED) patients.Methods: Adult patients admitted to the ED due to complaints of headache, chest pain, abdominal pain, backache, or painful limbs at triage were included. Two assessments, each lasting at least 30 s, were performed for each participant. A basic description of the pain was acquired, including pain intensity, using a self-report numerical rating scale (NRS). To identify the characteristics of facial expressions of pain, 18 facial AUs were assessed. The model was developed according to analyses of the significantly correlated facial AUs. Area under the receiver operating characteristic curves (AUC) of the AU-based model for different pain severities was calculated.Results: 429 video recording sessions were enrolled for analysis. 57.7% were male and the mean age was 51.3 years. Abdominal pain (49.4%) was the most common complaint, followed by back/limb pain (12.3%). The initial and follow-up mean NRS scores were 6.4 and 3.7, respectively. Several AUs showed significant correlations with NRS scores, including AU 1 (brow raising, p=0.024), AU 4 (brow lowering, p<0.001), and AU 26 (jaw dropping, p=0.038). A model to predict pain severity that included AUs 1, 4, 5, 9, 26, and 45 was created. The AUC of the prediction model to identify severe pain and no pain from others showed a value of 0.633 and 0.645, respectively. Conclusions: Although this study identified several facial AUs correlated with patient self-report NRS pain scores, analysis of facial expressions alone failed to accurately predict pain among patients in the ED. Further studies should aim to develop a more comprehensive means of measuring pain via multiple behavioral measurements.