Predicting Cybersickness

Design Interactive will be unveiling a predictive algorithm for cybersickness at this year’s Interservice/Industry, Training, Simulation and Education Conference (I/ITSEC). This individualized, predictive algorithm was developed from thousands of hours of physiological data captured during consumption of virtual content. The resultant predictive cybersickness index, or PCSI, can be used to evaluate virtual content for its potential to induce cybersickness and monitor a user’s progression toward sickness that may result in significant after effects.

The proliferation of low cost head mounted displays has resulted in significant investment into the investigation of their use for military and industrial training. The challenge however is that the expert virtual content developers are not experts in cybersickness. These talented individuals are reliant upon guidance from the hardware manufacturers which can be sparse at best or implementation of a subjective questionnaire. There is a lack of understanding of best practices and any best practices found are not necessarily grounded in a full understanding of what causes cybersickness physiologically.

The PCSI was developed by capturing physiological data during virtual content consumption within a leading virtual head mounted display. Cardiovascular, gastrointestinal, and electrodermal activity were collected via external, non-invasive sensors. DI’s internal testing has shown the PCSI to be 90% accurate in predicting both subjective and objective cybersickness, including the relatively long term detrimental effects such as headache, eye strain, nausea and alterations to balance.

How can I apply the PCSI?

Evaluate and compare virtual content.Training content can be evaluated in real time and comparisons can be made between content following consumption. Iterations in the content can be compared on a physiological basis, not just a subjective basis during development.

Evaluate dynamic virtual training systems.Training content may be coupled with dynamic, moving simulators. Motion sickness is similar in symptom presentation to cybersickness. PCSI can effectively evaluate the experience when virtual content is coupled with dynamic movement.

Establish break schedules.Cybersickness may not be completely avoidable. Some people will be more susceptible than others. PCSI can help predict onset at an individual level and help establish personalized break schedules for training simulations or consumption of content.

Identify individual resistance to onset.People are all different when it comes to susceptibility to cybersickness. Some will be more resilient than others. If a vocation dictates extensive exposure to virtual simulation (e.g. flight simulation qualification for pilots), then identifying those most resilient may be important.

Identify those quickest to recover.Cybersickness causes aftereffects that manifest in potential balance, coordination, and visual issues among others. It may not be safe for an individual to perform even basic daily activities immediately or hours following significant exposure, including driving a vehicle. PCSI can not only identify those most resistant to onset, but also those most resilient and quickest to recover.

What are the next steps in development?

Currently the PCSI is reliant upon physiological sensing in real time. The next evolution in development is to achieve the same level of prediction accuracy by utilizing measures that can come directly from the IMU in HMDs such as postural sway, head tracking, and eye-tracking in available systems.

How can I learn more and adopt the PCSI?

DI is unveiling PCSI at I/ITSEC 2016 in Booth 1721. You can contact DI now for more information and set up a meeting prior to or at the show to discuss how you can purchase DI’s services or license the algorithm. DI offers research and development services and can train your personnel on the use of the PCSI.

For more information contact:

Dr. Brent Winslow
Chief Scientist