London: Computers are able to read a person’s body language to tell whether they are bored or interested in what they see on the screen, according to a new study that could lead to empathetic robots and reactive online learning programmes.
The research shows that by measuring a person’s movements as they use a computer, it is possible to judge their level of interest by monitoring whether they display tiny movements that people usually constantly exhibit, known as non-instrumental movements.
If someone is absorbed in what they are watching or doing — what Dr Harry Witchel, from the Brighton and Sussex Medical School in UK calls ‘rapt engagement’ — there is a decrease in these involuntary movements. “Our study showed that when someone is really highly engaged in what they’re doing, they suppress these tiny involuntary movements,” Witchel said.
“It’s the same as when a small child, who is normally constantly on the go, stares gaping at cartoons on the television without moving a muscle,” he said. The discovery could have a significant impact on the development of artificial intelligence, researchers said.
Future applications could include the creation of online tutoring programmes that adapt to a person's level of interest, in order to re-engage them if they are showing signs of boredom, they said. It could even help in the development of companion robots, which would be better able to estimate a person’s state of mind.
Also, for experience designers like movie directors or game makers, this technology could provide complementary moment-by-moment reading of whether the events on the screen are interesting.
While viewers can be asked subjectively what they liked or disliked, a nonverbal technology would be able to detect emotions or mental states that people either forget or prefer not to mention.
“Being able to ‘read’ a person’s interest in a computer programme could bring real benefits to future digital learning, making it a much more two-way process. In the study, 27 participants faced a range of three-minute stimuli on a computer, from fascinating games to tedious readings, while using a handheld trackball to minimise instrumental movements, such as moving the mouse.
Their movements were quantified over the three minutes using video motion tracking. In two comparable reading tasks, the more engaging reading resulted in a significant reduction (42 per cent) of non-instrumental movement.
