Scientists find way to predict cybersickness

Scientists have found a way to predict whether a person is likely to suffer from cybersickness -- a type of motion sickness caused by using virtual reality technology -- which may pave the way for preventing the condition.

Researchers at the University of Waterloo in Canada found that they could predict whether an individual will experience by how much they sway in response to a moving visual field.

They think that this knowledge will help them to develop counteractions to cybersickness.

Cybersickness involves nausea and discomfort that can last for hours after participating in virtual reality (VR) applications, which have become prevalent in gaming, skills training and clinical rehabilitation.

"Despite decreased costs and significant benefits offered by VR, a large number of users are unable to use the technology for more than a brief period because it can make them feel sick," Seamas Weech, a postdoctoral research fellow at University of Waterloo.

"Our results show that this is partly due to differences in how individuals use vision to control their balance," said Weech.

"By refining our predictive model, we will be able to rapidly assess an individual's tolerance for virtual reality and tailor their experience accordingly," he said.

Researchers collected several sensorimotor measures, such as balance control and self-motion sensitivity, from 30 healthy participants aged 18-30.

They then exposed the participants to VR with the aim of predicting the severity of motion sickness.

Using a regression model, they significantly predicted how much cybersickness participants experienced after being exposed to a zero-gravity space simulator in VR.

"Knowing who might suffer from cybersickness, and why, allows us to develop targeted interventions to help reduce, or even prevent, the onset of symptoms," said Michael Barnett-Cowan, a neuroscience professor at University of Waterloo.

"Considering this technology is in a growth phase with industries such as gaming, design, medicine and automotive starting to use it, understanding who is negatively impacted and how to help them is crucial," said Barnett-Cowan.