A study presented at ANESTHESIOLOGY 2023, the annual meeting of the American Society of Anesthesiologists, showcased a promising development in pain management: an automated pain recognition system designed to detect pain in surgical patients.
This innovation, developed by Timothy Heintz and his team from the University of California San Diego, employs cutting-edge deep learning (DL) models to interpret pain through facial expressions.
The study involved 77 patients, whose facial expressions were captured using a three-camera array during various stages of their surgical procedures. These facial images were then analyzed using computer vision-based deep learning models.
To assess pain, two scales were employed: the self-reported visual analog scale (VAS) and the observer-measured Critical Care Pain Observation Tool (CPOT) scale. The facial images were divided into training, validation, and testing sets for the DL models.
With an extensive dataset of 143,293 images from 115 pain episodes and 159 non-pain episodes across 69 patients, the DL models were finely tuned to recognize pain indicators.
The models achieved an impressive accuracy of 88% for the CPOT scale and 66% for the VAS. Notably, the models identified key facial areas – the brows, nose, and upper lip – as critical indicators of pain.
This AI-powered pain detection system represents a significant leap in patient care, offering real-time, objective pain assessment.
Unlike traditional methods that rely on subjective patient input or clinical observation, this automated system provides a consistent and unbiased way to gauge pain levels.
This can be particularly beneficial in cases where patients are unable to communicate their pain effectively, such as during or after surgery, or in intensive care settings.
The researchers believe that their proof-of-concept AI model could revolutionize pain management, enhancing patient comfort and potentially improving surgical outcomes.
As AI and machine learning continue to advance, their application in healthcare promises to bring about more precise and personalized treatment approaches, improving patient experiences and clinical effectiveness.
If you care about pain management, please read studies about Scientists find a new drug for chronic nerve pain and findings of Scientists find a new, less-invasive way to tackle knee pain.
For more information about pain, please see recent studies about why people with red hair respond differently to pain than others, and results showing this drug may relieve painful ‘long covid’ symptoms.
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