Measurement of Acute Pain in the Pediatric Emergency Department Through Automatic Detection of Behavioral Parameters: A Pilot Study

Abstract

Acute pain is a frequent symptom in children who access the Emergency Department (ED). Its measurement through validated tools compatible with the time of triage is essential to develop the most appropriate pain-relieving strategy. The algometric scales that can be used in children in whom self-assessment is not possible are based on the evaluation of behavioral and physiological parameters. However, the actual use of algometric scales in the ED is scarce due to environmental factors, heterogeneity of the scales and lack of training, thus making automated pain assessment desirable. In this study, we propose a camera-based system to provide an objective and contactless pain assessment in children aged less than 3 years, through the automatic detection of behavioral parameters from video recordings. To investigate the feasibility of its usage in the ED environment, we collected video recordings of healthy children aged 3–36 months admitted to the ED with acute pain as the main or accompanying symptom, while pain was measured by a healthcare professional according to the Face, Legs, Activity, Cry, and Consolability (FLACC) pain scale. For the recorded videos, we compared the scores for the items Face (F), Legs (L) and Activity (A) given by the operator with the ones given by our system, analyzing the potentiality and limitations of our approach. By showing that automatic pain assessment in young children in the ED could integrate human evaluation to make it easier and faster, without substituting it, we provide the basis for further research in this field.