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Pain is an emotion that cannot be measured. Since people typically cannot tell how much pain someone else is in, others can use pain to their advantage. For example, some people might fake pain in order to get sympathy or another dose of prescription painkillers. In order to assess pain on a higher level, a team of researchers from the University of California San Diego and the University of Toronto developed a computer system that can separate real pain from fake pain more accurately than humans can.

"In highly social species such as humans...faces have evolved to convey rich information, including expressions of emotion and pain," said senior author Kang Lee, professor at the Dr. Eric Jackman Institute of Child Study from the University of Toronto. " And, because of the way our brains are built, people can simulate emotions they're not actually experiencing - so successfully that they fool other people. The computer is much better at spotting the subtle differences between involuntary and voluntary facial movements."

For this study, the research team was focused on creating a system that could detect fake facial expressions. People can pretend to be in pain for numerous reasons that generally benefit them in a particular situation. The researchers knew that humans are not very good at detecting fake pain. When people are trained to look out for certain cues, their accuracy is still at just 55 percent.

This computer system was built to identify these particular cues. The study found that the number one indicator of fake pain was the mouth. The researchers reported that people who are pretending to be in pain tend to open their mouths more frequently and with less variation. Based on these cues, the system can detect fake pain with 85 percent accuracy.

"The computer system managed to detect distinctive dynamic features of facial expressions that people missed," said Marian Bartlett, research professor at UC San Diego's Institute for Neural Computation and lead author of the study. "Human observers just aren't very good at telling real from faked expressions of pain."

The study, "Automatic Decoding of Deceptive Pain Expressions," was published in Current Biology.