Scientists are working with AI to measure chronic pain
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Scientists are working on a way to use AI to create quantitative measurements for chronic pain.
Why it matters: Chronic pain is an epidemic in the U.S., but doctors can't measure discomfort as they can other vital signs. Building methods that can objectively measure pain can help ensure that the millions in need of palliative care aren't left to suffer.
What's happening: Late last month, scientists from IBM and Boston Scientific presented new research outlining a framework that uses machine learning and activity monitoring devices to capture and analyze biometric data that can correspond to the perception of pain.
- The researchers are using biomarkers collected in clinical studies involving patients undergoing spinal cord stimulation, including information on movement collected from smartwatches, sleep data, heart rate levels and even voice recordings.
- AI is being employed to sift through the results in the hopes of identifying patterns that might enable doctors to "read" a patient's pain levels through that more granular data.
What they're saying: "We want to use all the tools of predictive analytics and get to the point where we can predict where people's pain is going to be in the future, with enough time to give doctors the chance to intervene," says Jeff Rogers, senior manager for digital health at IBM Research.
Background: According to one estimate, more than 100 million Americans struggle with chronic pain, at an annual cost of as much as $635 billion in painkillers and lost productivity.
- Yet doctors' methods for pain measurement remain rudimentary, like asking patients to report their pain on a scale of 1 to 10, or even just pointing to cartoon faces with different emotions.
What's next: Rogers hopes the research can lead to medical devices that could predict chronic pain signals ahead of suffering and adjust their response accordingly.
