How AI Is Learning to Measure Pain and Why It Matters
I was reading about some recent advancements in AI, and I came across an article on how researchers are trying to measure pain using artificial intelligence. It immediately caught my attention. Pain is such a personal and complicated feeling, so the idea that AI could somehow understand or quantify it sounded very interesting. That curiosity made me read a few more papers and articles on the topic. It was only a cursory read, but even then I felt the work was interesting enough to share.
Illustration by Rajashree Rajadhyax
Why Pain Measurement Matters
Pain may seem like something each of us simply feels and explains, but in healthcare it is one of the most difficult things to assess. Two people with the same issue can describe completely different levels of pain. Sometimes people under-report their discomfort because they do not want to bother anyone, and sometimes they simply cannot express it. This includes infants, patients in intensive care, people under anaesthesia, and those with dementia.
Accurate pain measurement is important because it helps doctors and caregivers make timely decisions. If pain is recognised early, it can prevent complications and reduce suffering. It is often called the fifth vital sign, but unlike temperature or blood pressure, there has never been an objective way to measure it. That is where AI research becomes interesting.
How AI Is Being Used To Measure Pain
Researchers are studying several approaches to identify signs of pain that might be too subtle for the human eye.
Facial expressions
AI models look at tiny, involuntary movements on the face. These are micro-expressions around the eyes, mouth and eyebrows that change when a person experiences discomfort. Tools like PainChek use a smartphone camera to scan these small movements and convert them into a pain score within seconds.
Movement and behaviour
Pain affects how people move. Some become restless, some guard a particular part of the body, and some make quick flinching actions. Video based AI systems analyse these patterns and notice when the behaviour suggests rising or falling pain levels.
Physiological signals
Wearables and sensors capture signals like heart rate variability, skin conductance and blood flow changes. These signals often shift when the body is under stress. Machine learning models learn which combinations match different levels of pain.
Putting all the signals together
Some of the latest AI tools combine facial analysis, movement patterns and physiological data to create a more continuous picture of a person's pain experience.
Where This Can Help
AI supported pain assessment can be very useful in situations where people cannot communicate clearly.
In dementia care, where patients may not be able to say what hurts
In neonatal care, where babies express discomfort only through behaviour
During surgery and anaesthesia, where real time signals are important
In home care, where caregivers can be alerted to changes even when they are not in the room
In all these cases, AI acts like an extra pair of attentive eyes that never get tired.
A Gentle Note
Even with all this progress, human judgement and empathy remain essential. Pain is not only physical. It is shaped by memory, fear, culture and past experience. AI can support us by detecting patterns and giving early alerts, but it cannot replace the human touch. When used thoughtfully, this technology can make care more attentive and compassionate, helping us notice what we might have missed.
Sources you can explore
I am sharing these sources in case you want to explore further. I could only do a cursory read, but you might find something worth diving into.
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