Software reads kids’ expression to measure pain levels

Software reads kids’ expression to measure pain levels
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Highlights

Assessing the exact pain levels of child patients could now be a lot easier with researchers having found a new method to better measure their pain levels by using a novel facial pattern recognition software. \"The current methods by which we analyse pain in kids are suboptimal,\" said senior author Jeannie Huang, professor at University of California, San Diego School of Medicine in the US.

New York: Assessing the exact pain levels of child patients could now be a lot easier with researchers having found a new method to better measure their pain levels by using a novel facial pattern recognition software. "The current methods by which we analyse pain in kids are suboptimal," said senior author Jeannie Huang, professor at University of California, San Diego School of Medicine in the US.


"In this study, we developed and tested a new instrument, which allowed us to automatically assess pain in children in a clinical setting. We believe this technology, which enables continuous pain monitoring, can lead to better and more timely pain management," Huang said.


Huang said controlling pain is important, not only for the child's comfort, but also for recovery. However, several issues, particularly age-related communication difficulties, make existing paediatric pain assessment methods problematic. Clinical pain assessments, aided by nurses or parents, are often used in lieu of patient self-report in children because of these limitations.

The researchers used the software to analyze pain-related facial expressions from videos taken of 50 youths, aged 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. "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 added. The study was published in the journal Paediatrics.

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