A new study led by body language expert Dr Harry Witchel, head of the department of physiology at Brighton and Sussex Medical School, suggests that computers can tell if people are interested in what is on a computer screen by reading their body language.
The study found that people’s level of interest could be judged by looking at their range of motion while using a computer, such as whether they were constantly making small, unconscious movements.
If people are immersed in what they are seeing or doing, which Dr Witchel describes as “rapt engagement”, their unconscious movements decrease.
Dr Witchel said: “Our research shows that when someone is really focused on what they are doing, they suppress their small unconscious movements. It’s the same as a child running around and watching a cartoon on TV without moving.
This finding has clear implications for the development of artificial intelligence. Future applications include creating online tutorials tailored to people’s level of interest, which could re-engage them when they show signs of boredom. It could also be used to develop companion robots that can better predict people’s mental states.
For experienced designers, such as film producers and game makers, the technology can be used to see in real time whether on-screen events are interesting or not. Viewers are subjectively asked about their likes and dislikes, a nonverbal technique that can detect feelings or mental states that people have forgotten or don’t want to mention.
“Being able to read about a person’s interest in a computer program could have real benefits for future digital learning, making it a more two-way process,” said Dr Witchel. “In the future it will help us create more empathetic companion robots, which sounds strange but may be possible in our generation.”
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In the study, 27 subjects tested a three-minute session ranging from an interesting game to boring reading about EU banking regulation, using a hand-held trackball to minimize instrument movement, such as moving a mouse. Video motion tracking was used to quantify their behavior over a three-minute period. In the two comparable reading tasks, the reading task with higher participation had significantly fewer unconscious actions, with a 42 percent reduction compared to the other task.