New Approach to Objective Pain Assessments
MIE Professor and Interim Chair Yingzi Lin’s research on pain assessment and management practices appeared in the September 2024 issue of Nature. She is studying a “Continuous Objective Multimodal Pain Assessment Sensing System” to advance the field of pain management research and patient safety, which could also reduce opioid dependency.
The U.S. Department of Health and Human Services identified pain management as one of the five key strategies to address the opioid crisis, which is a national emergency. Doctors rely primarily on a patient’s subjective assessment of pain using visual scales to rate pain intensity from 0 to 10.
Lin and her team explored objective pain assessment and management practices, gathering valuable data through research projects sponsored by the National Science Foundation that were conducted at her lab and in a clinical setting. Lin hopes to develop an automated AI system for use at the patient’s bedside. The system, which will provide scientific data to complement a patient’s subjective rating, will enable doctors to make more effective treatment decisions, avoid overprescribing pain pills that can lead to addiction, and help patients who are in severe pain.
Lin says this problem impacts everyone in some way, and she is committed to improving the quality of human lives.
This article originally appeared on Northeastern Global News. It was published by Cynthia McCormick Hibbert. Main photo: Yingzi Lin, professor of mechanical and industrial engineering, attaches sensors to measure physiological responses to pain prompts. Photo by Ruby Wallau/Northeastern University
Can you measure pain objectively, based on science? Northeastern researcher uses AI to develop ‘pain-o-meter’
When Northeastern professor Yingzi Lin visited her father after his hip replacement, doctors asked him to measure his level of pain on the standard score of zero to 10.
He couldn’t do it, says Lin, who accompanied her father to his appointments.
Maybe it was his cultural background from being raised in China or the fact he had lived with chronic pain for a long time. But the number system didn’t work for her father, nor did it work for Lin when she was delivering her first child at Brigham and Women’s Hospital in Boston.
Professor Yingzi Lin is using AI and machine learning to objectively rate pain. “Pain touches everybody’s life.” Photo by Matthew Modoono/Northeastern University
“I had an induced delivery but when the nurse would come to check on me, I would always tell them, ‘I’m OK,’” Lin says, even when her pain was nearly off the charts.
“I hated to give very high numbers and say, ‘I’m a nine or a 10’ because I was worried that I might get some unnecessary treatment from the doctors.”
Lin, who is a professor of mechanical and industrial engineering, says the experiences gave her the idea to use her engineering skills to pin down the subjective experience of pain.
“How can you measure it objectively?” she says.
A bucket of ice water
For her research, Lin uses pin pricks, applied, steady pressure and a test that calls for participants to dunk their hand in a bucket of ice cold water that is maintained at around 32 degrees Fahrenheit.
“They are free to stop any time, as needed,” says Lin, who was the first test subject.
While running the tests, she uses sensors placed on participants’ heads and chests to collect a bundle of physiological responses, including, heart rate, respiration, muscle movement, galvanic skin response and brain wave signals.
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Photos by Matthew Modoono/Northeastern University
Facial expressions also factor in, as do eye movements and dilation, says Lin, whose research was recently featured in a Nature article about how a “pain-o-meter” could improve treatment.
The responses are fed into machine learning algorithms to find patterns and relationships that will be a sure-fire indicator of pain levels.
Read Full Story at Northeastern Global News