Cybersickness Prediction from Integrated HMD’s Sensors: A Multimodal Deep Fusion Approach using Eye-tracking and Head-tracking Data

Islam, Rifatul; Desai, Kevin; Quarles, John

doi:10.1109/ismar52148.2021.00017

Cited by 49 publications

(25 citation statements)

References 50 publications

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“…Nevertheless, beyond self-reports, there are other neuro-and bio-markers that have been used for detecting and measuring cybersickness [8]. Specifically, researchers have efficiently implemented electroencephalography [57], [58] and eye-tracking [59], [60] to detect and appraise the occurrence and intensity of cybersickness. The VR version of CSQ-VR benefits also from eye-tracking metrics.…”

Section: Comparison Of Csq-vr Ssq and Vrsqmentioning

confidence: 99%

Cybersickness in Virtual Reality Questionnaire (CSQ-VR): A Validation and Comparison against SSQ and VRSQ

et al. 2023

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Cybersickness is a drawback of virtual reality (VR), which also affects the cognitive and motor skills of users. The Simulator Sickness Questionnaire (SSQ) and its variant, the Virtual Reality Sickness Questionnaire (VRSQ), are two tools that measure cybersickness. However, both tools suffer from important limitations which raise concerns about their suitability. Two versions of the Cybersickness in VR Questionnaire (CSQ-VR), a paper-and-pencil and a 3D–VR version, were developed. The validation of the CSQ-VR and a comparison against the SSQ and the VRSQ were performed. Thirty-nine participants were exposed to three rides with linear and angular accelerations in VR. Assessments of cognitive and psychomotor skills were performed at baseline and after each ride. The validity of both versions of the CSQ-VR was confirmed. Notably, CSQ-VR demonstrated substantially better internal consistency than both SSQ and VRSQ. Additionally, CSQ-VR scores had significantly better psychometric properties in detecting a temporary decline in performance due to cybersickness. Pupil size was a significant predictor of cybersickness intensity. In conclusion, the CSQ-VR is a valid assessment of cybersickness with superior psychometric properties to SSQ and VRSQ. The CSQ-VR enables the assessment of cybersickness during VR exposure, and it benefits from examining pupil size, a biomarker of cybersickness.

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Section: Comparison Of Csq-vr Ssq and Vrsqmentioning

confidence: 99%

Cybersickness in Virtual Reality Questionnaire (CSQ-VR): A Validation and Comparison against SSQ and VRSQ

et al. 2023

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“…One of the largest limitations of this research is the use of subjective measures to track the three main constructs of interest which were cybersickness, workload, and presence. While there is not yet a wide consensus on a reliable objective measure of cybersickness, there are several recent contenders, such as using eye gaze and head movement within the HMD (Islam et al, 2021), eye gaze and game character movement (Wang et al, 2022), and VE smoothness of movement (Monteiro et al, 2021) to predict cybersickness successfully. Measures such as these, or even an additional self-report measure such as the fast motion sickness scale (FMS) (Keshavarz and Hecht, 2011) could have been useful to triangulate with SSQ.…”

Section: Limitationsmentioning

confidence: 99%

The impact of task workload on cybersickness

Sepich

Jasper

Fieffer

et al. 2022

Front. Virtual Real.

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This study explored the impact of task workload on virtual reality (VR) cybersickness. Cybersickness is a negative side effect of using VR to which many users are susceptible. Previous research on the impact on task workload on cybersickness has yielded no consistent relationships, but given that task workload requires attentional resources, it is worth further investigation of how a demand on attention might increase or decrease cybersickness. In this study, mental workload of participants (N = 151) was modified in three different task groups within the same virtual environment (VE). The Cybersickness Corn Maze VR testbed contained cybersickness-inducing stimuli and tasks with varying workload. The 0-Back group used a controller to select an object as a visual attention task. The 2-Back group performed the 2-Back memory detection task, using a controller to collect objects that matched the object presented two objects ago. The No-Task group passively moved through the environment and was not given a controller. Workload, cybersickness, dropout rate, presence, and task accuracy were compared across groups. Workload was found to be statistically significantly different in each group: highest in the 2-Back group, medium in the 0-Back group, and lowest in the No-Task group, validating the task design. Cybersickness in the 2-Back group was significantly higher than in the No-Task (140% higher) and 0-Back (54% higher) groups measured by the change in simulator sickness questionnaire (SSQ) total severity (Post SSQ - Pre SSQ). The rate of participants’ dropout due to cybersickness was significantly higher in 2-back (33%) as compared with 0-Back (10%), but 0-Back and No-Task dropout rates were not significantly different. These results indicate that 1) task workload affects cybersickness and 2) its effect could be based on a threshold of workload. Presence increased with the addition of a task but plateaued between the 0-Back and 2-Back groups, suggesting that presence can be affected by task workload but only to a certain extent. Task accuracy was shown to negatively correlate with cybersickness within the task groups. A relationship between workload and cybersickness was found and warrants further research into these concepts. This work highlights the need for task workload and attention to be studied as components of the mechanisms underlying cybersickness.

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“…A decrease in pupil size indicated higher intensity cybersickness and vice versa, a pattern that has been previously observed between pupil size and negative emotions [31]. Previously, pupil size has been included in a deep fusion model for predicting cybersickness [60]; however, its relationship, predictive ability and contribution to this model were not evaluated, preventing a conclusion of whether pupil size is a biomarker of cybersickness. This study provides evidence postulating that pupil size is indeed a biomarker of cybersickness, as well as its intensity.…”

Section: Comparison Of Csq-vr Ssq and Vrsqmentioning

confidence: 76%

“…Nevertheless, beyond self-reports, there are other neuro and biomarkers that have been used to detect and measure cybersickness [8]. Specifically, researchers have efficiently implemented electroencephalography [57,58] and eye tracking [59,60] to detect and appraise the occurrence and intensity of cybersickness. The VR version of the CSQ-VR also benefits from eye-tracking metrics.…”

Section: Comparison Of Csq-vr Ssq and Vrsqmentioning

confidence: 99%

Cybersickness in Virtual Reality Questionnaire (CSQ-VR): A Validation and Comparison against SSQ and VRSQ.

Kourtesis¹,

Linnell²,

Amir³

et al. 2023

Preprint

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Cybersickness is a drawback of virtual reality (VR), which also affects the cognitive and motor skills of the users. The Simulator Sickness Questionnaire (SSQ), and its variant, the Virtual Reality Sickness Questionnaire (VRSQ) are two tools that measure cybersickness. However, both tools suffer from important limitations, which raises concerns about their suitability. Two versions of the Cybersickness in VR Questionnaire (CSQ-VR), a paper-and-pencil and a 3D –VR version, were developed. Validation and comparison of CSQ-VR against SSQ and VRSQ were performed. Thir-ty-nine participants were exposed to 3 rides with linear and angular accelerations in VR. Assess-ments of cognitive and psychomotor skills were performed at baseline and after each ride. The va-lidity of both versions of CSQ_VR was confirmed. Notably, CSQ-VR demonstrated substantially better internal consistency than both SSQ and VRSQ. Also, CSQ-VR scores had significantly better psychometric properties in detecting a temporary decline in performance due to cybersickness. Pupil size was a significant predictor of cybersickness intensity. In conclusion, the CSQ-VR is a valid assessment of cybersickness, with superior psychometric properties to SSQ and VRSQ. The CSQ-VR enables the assessment of cybersickness during VR exposure, and it benefits from examining pupil size, a biomarker of cybersickness.

show abstract

Cybersickness Prediction from Integrated HMD’s Sensors: A Multimodal Deep Fusion Approach using Eye-tracking and Head-tracking Data

Cited by 49 publications

References 50 publications

Cybersickness in Virtual Reality Questionnaire (CSQ-VR): A Validation and Comparison against SSQ and VRSQ

Cybersickness in Virtual Reality Questionnaire (CSQ-VR): A Validation and Comparison against SSQ and VRSQ

The impact of task workload on cybersickness

Cybersickness in Virtual Reality Questionnaire (CSQ-VR): A Validation and Comparison against SSQ and VRSQ.

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