Predicting cybersickness using individual and task characteristics

Jasper, Angelica; Sepich, Nathan C.; Gilbert, Stephen B.; Kelly, Jonathan W.; Dorneich, Michael C.

doi:10.1016/j.chb.2023.107800

Cited by 16 publications

(13 citation statements)

References 59 publications

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“…Further we decided to exclude patients with pre-existing severe motion sickness (based on self-report). Due to results of previous studies showing that a motion sickness history in real life is an important predictor for the experience of cyber sickness (38,39), selfreported motion sickness is a common exclusion criterion in VR studies (40).…”

Section: Participants and Recruitmentmentioning

confidence: 99%

Acceptability, feasibility, and user satisfaction of a virtual reality relaxation intervention in a psychiatric outpatient setting during the COVID-19 pandemic

Humbert,

Kohls,

Baldofski

et al. 2023

Front. Psychiatry

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BackgroundThe COVID-19 pandemic was particularly difficult for individuals with mental disorders. Due to governmental restrictions, face-to-face offers for psychiatric outpatients like therapies, psychoeducational groups or relaxation courses were limited. Virtual reality (VR) might be a new possibility to support these patients by providing them with a home-based relaxation tool.ObjectiveThe aim of this study was to evaluate the acceptability, feasibility, and user satisfaction of a supportive therapy-accompanying, relaxation VR intervention in psychiatric outpatients during the COVID-19 pandemic in Germany.MethodsThe four-weeks VR intervention consisted of regular watching of relaxing videos in the participants’ home environment. Sociodemographics, feasibility (frequency of use, user-friendliness), satisfaction (Client Satisfaction Questionnaire-8), depressive symptoms (Patient Health Questionnaire-9), quality of life (abbreviated World Health Organization Quality of Life assessment), and credibility and expectancy (Credibility Expectancy Questionnaire-8) were measured in an intention-to-treat (ITT) analysis and a per-protocol (PP) analysis of completers.ResultsIn total, N = 40 patients participated in the study. Most of the participants in the ITT analysis (n = 30, 75.0%) used the VR device three or 4 weeks. A majority of the N = 29 completers (PP: n = 18, 62.1%) used it all 4 weeks. Most participants used the device two or more times a week (ITT: n = 30, 83.3%; PP: n = 26, 89.7%) and described the user-friendliness as rather or very easy (ITT: n = 33, 91.7%; PP: n = 26, 89.7%). User satisfaction was high (ITT: 19.42, SD = 4.08; PP: M = 20.00, SD = 4.19) and did not correlate with participants’ sex or age (all p < 0.05). Depressive symptoms and psychological quality of life improved significantly from pre-to post-intervention (ITT and PP, all p < 0.05). Higher pre-intervention credibility significantly correlated with a better outcome of satisfaction (ITT and PP), depressive symptoms, physical, psychological, and social quality of life (PP; all p < 0.05).ConclusionA supportive therapy-accompanying VR relaxation intervention is feasible and acceptable in a psychiatric outpatient setting. Due to the high satisfaction and user-friendliness, VR can be an easy to implement relaxation tool to support psychiatric outpatients.Clinical trial registrationhttps://clinicaltrials.gov/, DRKS00027911.

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Section: Participants and Recruitmentmentioning

confidence: 99%

Acceptability, feasibility, and user satisfaction of a virtual reality relaxation intervention in a psychiatric outpatient setting during the COVID-19 pandemic

Humbert,

Kohls,

Baldofski

et al. 2023

Front. Psychiatry

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Section: A Prediction Of Cybersicknessmentioning

confidence: 99%

“…An alternative approach is to look at participant and task characteristics as cues to predicting susceptibility to cybersickness [12], [27]. Jasper et al [12] explored participant demographics, the task to be completed, the virtual environment design and the VR hardware used as the four main factors contributing to the likelihood of cybersickness. Based on a user study (n=150), they constructed hierarchical multiple regression models to examine individual characteristics, such as motion sickness history, previous VR use, gender, age and personality, and task characteristics, particularly workload.…”

Section: A Prediction Of Cybersicknessmentioning

confidence: 99%

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Exploring Cybersickness Experiences via a Markov Chain Model

Smith

2024

IEEE Access

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Users of virtual reality (VR) technology, especially head-mounted displays (HMDs), often experience cybersickness, similar to motion sickness, with feelings of nausea, dizziness and sweatiness. Cybersickness typically increases with duration of wearing a HMD and is commonly evaluated in user studies with physiological measures, in-situ verbal reports and post session questionnaires. However, in addition to being time-consuming, user studies only provide insight into the specific configuration of the VR experience under study and can be limited to participant numbers, duration of VR exposure and the impact of cybersickness on VR experience dropout and completion rates. This paper presents a formal approach to modelling cybersickness. A Markov chain is used to define a general cybersickness model where probabilities represent changes in a user's state of cybersickness. The Markov chain can be populated with historical user study data and interrogated to gain further awareness of the VR experience under evaluation. The approach is exemplified with a custom Markov chain model generated from a public VR experience dataset. The resulting model is shown to be representative of the ground truth user experience from the source material. Examples are presented to demonstrate how the model can be explored to gain insight for (i) scaled up parameters, such as exposure duration and participant numbers, and (ii) acceptance thresholds for minimum/maximum cybersickness. Limitations on the generation of the model and its utility across different user populations and environment types are considered and discussed in the context of future work. INDEX TERMS Virtual reality, cybersickness, head-mounted display, Markov chain, prediction I. INTRODUCTION

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“…In another study, nevertheless, the athletes did not verbally report discomfort and did not have to stop testing; it was assumed that the actual cybersickness occurred only to a minor extent under VR conditions through an HMD display and marginally affected the athletes in their response tasks [27]. The sensation of cybersickness can hinder the effectiveness of training and the overall experience for every person who uses an HMD [30], including karate athletes. Striking the right balance between virtual and physical training is another challenge that karate practitioners and coaches need to navigate.…”

mentioning

confidence: 99%

The Use of Immersive Technologies in Karate Training: A Scoping Review

Lygouras,

Tsinakos

2024

MTI

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This study investigates the integration of immersive technologies, primarily virtual reality (VR), in the domain of karate training and practice. The scoping review adheres to PRISMA guidelines and encompasses an extensive search across IEEE Xplore, Web of Science, and Scopus databases, yielding a total of 165 articles, from which 7 were ultimately included based on strict inclusion and exclusion criteria. The selected studies consistently highlight the dominance of VR technology in karate practice and teaching, with VR often facilitated by head-mounted displays (HMDs). The main purpose of VR is to create life-like training environments, evaluate performance, and enhance skill development. Immersive technologies, particularly VR, offer accurate motion capture and recording capabilities that deliver detailed feedback on technique, reaction time, and decision-making. This precision empowers athletes and coaches to identify areas for improvement and make data-driven training adjustments. Despite the promise of immersive technologies, established frameworks or guidelines are absent for their effective application in karate training. As a result, this suggests a need for best practices and guidelines to ensure optimal integration.

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Predicting cybersickness using individual and task characteristics

Cited by 16 publications

References 59 publications

Acceptability, feasibility, and user satisfaction of a virtual reality relaxation intervention in a psychiatric outpatient setting during the COVID-19 pandemic

Acceptability, feasibility, and user satisfaction of a virtual reality relaxation intervention in a psychiatric outpatient setting during the COVID-19 pandemic

Exploring Cybersickness Experiences via a Markov Chain Model

The Use of Immersive Technologies in Karate Training: A Scoping Review

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