Los Angeles: A new software that analyses facial expressions can accurately measure pain levels in kids, a new study has found. Researchers at the University of California, San Diego School of Medicine used the software to analyse pain-related facial expressions from video taken of 50 youths, ages five to 18 years old, who had undergone laparoscopic appendectomies at Rady Children’s Hospital-San Diego. Based on the analysis, along with clinical data input by the study team, the software provided pain level scores for each participant.
“In this study, we developed and tested a new instrument, which allowed us to automatically assess pain in children in a clinical setting,” said senior author Jeannie Huang, a professor in the UC San Diego School of Medicine Department of Pediatrics and a gastroenterologist at Rady Children’s Hospital-San Diego. “We believe this technology, which enables continuous pain monitoring, can lead to better and more timely pain management,” Huang said.
Several issues, particularly age-related communication difficulties, make existing pediatric pain assessment methods problematic, said Huang. “The current gold standard for measuring pain is self reporting,” she said, noting patients are generally asked to rate their pain on a scale of zero to 10. “But in pediatrics there is a limited population of kids who can answer that question in a meaningful way,” Huang said.
Clinical pain assessments, aided by nurses or parents, are often used in lieu of patient self-report in children because of these limitations. However, several previous studies have shown nursing staff may have difficulty accurately estimating pain (often underestimating pain), particularly among pediatric patients. In the new study, researchers filmed the participants at
three different visits post-surgery.
Facial video recordings and self-reported pain ratings by the participant and pain ratings by parents and nurses were collected. The software prototype utilized data collected via prior software (Computer Expression Recognition Toolbox) by study co-author Marian Bartlett, at UC San Diego’s Institute for Neural Computation, which utilizes computer vision techniques to analyse facial expressions based on the Facial Action Coding System (FACS).
In the software prototype, the study’s authors translated the facial movement data into a pain score and then compared that with the information collected from the child’s self-reporting and the parent and nurse by proxy pain estimations. “The software demonstrated good-to-excellent accuracy in assessing pain conditions,” said Huang. “Overall, this technology performed equivalent to parents and better than nurses. It also showed strong correlations with patient self-reported pain ratings,” Huang said.