Understand and mitigate the impact of simulator sickness on VR users.
Given that up to 1 in 3 people [1, 2] experience some type of motion sickness, it’s highly likely that either you or someone you know has felt a bit queasy after using a virtual reality (VR) simulator for the first time. And this includes your users.
Although simulator sickness (SS) can occur with any variety of VR experiences, moving experiences such as high-speed rollercoasters and driving simulators tend to be particularly susceptible to this phenomenon, especially in the absence of haptic feedback. Your eyes receive input that you are moving, but the rest of your body cannot feel that motion. This dissonance leads your body to the same physiological response as if you were poisoned, commonly referred to as the Sensory Conflict Theory.
Unfortunately, determining ahead of time which individuals are most likely to experience SS is still a subject of research and is therefore not easy to predict. However, for those researching solutions to improve their users’ experience (UX) and feel more comfortable in VR, knowing how to measure the signs is a good first step to refining recommendations for your various user groups.
VR immersion and its effect on the body is still a relatively new area of research, especially since low-cost VR solutions have only been around for a few years as of the time of this article. As a result, much of this information is either considered taboo to talk about in industry or confined solely to dense academic literature.
The goal of this article is to help summarize my learnings from academic literature reviews and my industry UX research experience alike.
If you would like to a more general overview of design considerations to avoid simulator sickness, that is the subject of a future article. This post is focused on recognizing the symptoms in your users and systematically correcting for it from a usability testing perspective. Be sure to give me a follow if you want to see more content like this!
Before we dive into this topic, I want to clarify key terms and answer common questions related to the topic of simulator sickness.
Motion sickness (MS) and simulator sickness (SS), although caused by different phenomena, present with near-identical symptoms, meaning they can be measured using the same tools and that research in one area can be used to inform the other. These symptoms generally include (to varying degrees):
For example, something like vomiting is more common in motion sickness (such as the classic movie trope of someone hurling on a cruise ship) whereas there’s only a 0.1% incidence of vomiting with simulator sickness. That is to say, while symptoms do overlap, they are not seen with the same frequency or severity across all applications.
Other terms often used for simulator sickness is “cyber sickness” or “visually induced motion sickness (VIMS)”. In this article I will only be using the term “simulator sickness (SS)” as it is specific to simulators rather than digital devices more broadly. However, all of these terms generally refer to the same phenomenon in this context.
It’s one thing to notice these signs of SS in your users, but another to quantify its impact.
Is everyone experiencing this? To what degree are we seeing symptoms? How do these symptoms impact simulator use? What about its effects on users after they finish their session? Does this experience deter them from returning? How do we know a particular intervention is working?
These are the sort of questions we want to find answers to.
And in order to find these answers we’re looking for, we need to collect some data to analyze.
For those just starting out in this arena, acquiring subjective data will be a helpful first step. After all, it requires no fancy sensors to get started, so it’s fairly accessible to everyone. However, it can be a bit trickier to get right in terms of asking the right questions so that subjects can provide useful answers.
That’s where standardized questionnaires can help.
The famous Simulator Sickness Questionnaire (SSQ) by Kennedy et. al (1993) — a questionnaire designed to evaluate different symptoms of simulator sickness and calculate a weighted score — is still considered the standard measure for simulator sickness. It builds off of (or rather, edited and refined) another paper from 1965 on a motion sickness questionnaire (MSQ) to adapt it to simulator-specific applications.
Although there have been attempts in recent years to further refine the SSQ for modern devices, it still remains the current standard.
For more information on how to use the SSQ in practice, I will soon be publishing a follow-up article with a comprehensive Google Form Template and data analysis tutorial! Be sure to follow for updates on when that is posted!
In addition to the SSQ, you may also want to conduct less structured ethnographic observations of your study participants as they complete their tasks. Recording sessions with a video camera will help you point out any visual behavioral clues of someone starting to experience signs of simulator sickness such as skin flushing, gulping, sweating, removing layers of clothing, or complaining that it “feels hot in here”.
While these may or may not be specific metrics needed for your study, observing users over time could help you refine your methodology if you uncover any particular behavioral patterns unique to your experience.
After all, not all VR experiences are created equal.
While biometric measures are objective and quantifiable, you do need to ensure that the equipment you’re using has the appropriate precision for your measurements to be valid and they may also require calibration to retain accuracy. Additionally, depending on what type of sensors you ultimately choose for your study, there may be extra regulations on how you handle the data collected (more on that later).
Based on the equipment you have access to and the goals of your study, you may choose to take discrete before and after measurements of these metrics or measure continuously during the full duration of the experiment to detect inflection points. There are plenty of options for your research budget!
One measure of simulator sickness is body temperature. Subjects experiencing SS often complain of feeling hot or will ask if they can pause to remove a jacket. One would think this means their body temperature is increasing, but it’s actually the opposite. The body thinks it’s getting hot from the sensory mismatch (i.e., perceiving a fever that isn’t there), and therefore, decreases the body temperature to compensate.
To measure this decrease in body temperature over time you can utilize sensors such as thermistors or even thermal cameras (if you want to localize the heat changes to specific areas of the body).
Normal skin surface temperature ranges from 90–95°F (32–35°C) but may be vary in different body regions or with individual syndromes like Raynaud’s disease, so it’s recommended to choose sensor placement that minimizes deviation across your study sample. Please note that skin surface temperature is different than core body temperature (and is, therefore, less invasive to measure, as well).
Another measure to look out for is skin conductance, measured with a galvanic skin response or electrodermal sensor, is a measure of how much someone is sweating. This is closely related to the body temperature metric as it is a direct physiological response that allows the body to cool down.
Typically this is measured on the forehead for VR applications, where symptoms often occur first and most noticeably. Sensors may come stock with fingertip attachments, so modifications or alternative forehead straps may be needed.
Heart Rate and HRV
Another potential sign of simulator sickness is a spike in heart rate andor a decrease in heart rate variability (HRV).
Heart rate has been shown to increase during nausea associated with motion sickness. Similarly, mild simulator sickness has also been shown to alter heart rate variability, lower heart rate variability has been shown in some subjects in VR applications.
If you have access to a climate-controlled room, it’s important to keep subjects at a comfortable room temperature and humidity in order to mitigate any effects due to climate. This can interfere with sensor results in many ways — such as causing subjects to shiver in the cold or sweat in the heat — as well as potentially exacerbating any SS symptoms.
Additionally, be sure to keep in mind if sensors have to “warm up” (literally or figuratively) prior to measurement to achieve a stable result. For this you may want to attach sensors while taking demographic information to achieve a baseline prior to experimentation. These are factors you should test before scheduling official subjects for your sample.
One often forgotten (but critical) component of managing simulator sickness in users is actually a social one.
Through a select number of customer visits, we found that users who discussed simulator sickness with a colleague about to embark on a VR training session were significantly more likely to report simulator sickness symptoms, suggesting a potential psychosomatic effect.
This is where “training the trainer” becomes critical in enterprise applications. When trainers are properly educated on the risks associated with simulator sickness, they can prevent social escalation of these issues by carefully crafting how they speak about these issues with trainees. This also applies to you as UX researcher working with test subjects, as well.
Additionally, if your participants do experience motion sickness during your trial, it is imperative that you do your best to give them breaks and help them feel comfortable as they recover.
There are many tricks for this, but you can start by waiting to take demographic information until after the experiment so they can sit down and recover while answering those questions. It can also be helpful to provide water to keep them hydrated and hard candies to suck on, which has been shown to help dissipate symptoms in some subjects.
You may also consider scheduling participants directly after lunch or immediately in the morning after breakfast, so they’re not participating while hungry. In this way, offering cafeteria tickets as an alternative form of compensation could also directly benefit your experiment.
As you might imagine, when you start to delve into the realm of biometric measurements and physiology, you run the risk of your study coming into contact with personal health data or being considered a clinical study, even if you are not providing medical intervention. Therefore, before conducting a study of this nature, it is imperative that you understand the risks and regulations associated with your specific study design.
If you’re in academia, you most likely have access to an IRB board that can help you determine what training you may need to work with human subjects, especially if the extent of your measurements might be considered a clinical-adjacent study. This type of training often includes topics such as conducting human subjects research in an ethical manner as well as avoiding bias and conflicts of interest.
If you’re in industry, guidelines are not always as straightforward. Be sure to contact a lawyer, whether it’s a corporate lawyer working with your employer or your own attorney for freelance work. There may be specific compliance guidelines you need to follow and those guidelines may differ depending on how your subjects are sourced (e.g., internal employees vs. outside users).
Specific recommendations are not included here because they may vary by jurisdiction, so it us up to you to do your due diligence and verify what is applicable to you. This is simply a reminder to do so!