A Review On Ergonomics Evaluations Of Virtual Reality Part 2
Sep 04, 2023
3.3.2. Cognitive ergonomics
Cognitive ergonomics research for virtual reality software is focused on two aspects: task performance and cognitive load.
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3.3.2.1. Task performance. Virtual reality environments can have an impact on users' task performance. Rizzuto et al. [73] evaluated the performance of the pointing task in real and virtual environments and found that the target error in the virtual condition was significantly larger than that in the real condition. To compare walking in virtual reality and the real world, various aspects were studied, including types of systems such as video displays and helmet displays, 3D spatial recognition, speed recognition, and environments such as space stations or buildings. Several scholars [74, 75] have compared navigation tasks in HMD and desktop environments, including the number of captures, distance traveled, and average speed. The experiments showed that, in general, people were more satisfied and intuitive with HMD, but performed better on the desktop environment for most tasks.
Task performance is closely related to access to information in the virtual environment. Lee et al. [76] investigated the influence of text information on the cognitive processing of visual information in HMD by obtaining user evaluations from three dimensions: contrast sensitivity, sentence length, and text size. They proposed that in a virtual reality environment, a text size of 96 pixels or more, a background contrast sensitivity of 75% to 50%, and an effective sentence length ratio of 33.3% to 50% were used to ensure the readability of text information. Lambooij et al. [77] also conducted a user study to determine the visual discomfort associated with 3D stereoscopic displays compared to 2D displays and suggested that participants with a moderate binocular condition experienced more visual discomfort and showed decreased performance in reading tasks. By studying the effects of color mode (dark or light mode), peripheral illumination, and virtual illumination on reading text, Erickson et al. [78] found that using light mode under bright virtual illumination facilitates the legibility of text to the user, but switching to dark mode was beneficial when lowering the virtual illumination. They believed that this was partially due to a color bleeding effect that occurs when a light-colored letter is presented on a dark background, where the light from the letter partially illuminates neighboring background pixels and results in a letter that appears slightly larger [79].
3.3.2.2. Cognitive load. A particular challenge of virtual reality is the potential overload of visual input, which creates an unnecessary cognitive load [80]. Rhiu et al. [81] verified that users felt a higher workload when using the HMD while walking and driving. In particular, the scores of mental demand and frustration were significantly different between the two systems, as users felt dizzy or mentally stressed when participating in the experiment. Chang et al. [82] designed a driving system with embedded Stroop tasks. Stroop task was used to assess cognitive processing and selective attention abilities, which asked an individual to distinguish whether a certain word’s meaning and visual color match [82]. They found that the average response time when users answered Stroop trials in the FSD (flat-screen displays) condition was shorter than that in the HMD condition. This indicated that HMDs might have caught more of the users' attention for virtual driving, which led to their delayed responses to the Stroop trials. In terms of gender differences, they found that men outperformed women in virtual driving, especially at longer driving distances. They speculated that the reason for this may be that females have a higher cognitive load in virtual driving. Female users had a significantly lower average minimum oxygen saturation and a greater decrease in oxygen saturation during the use of the system. The virtual driving system generated more mental work for women, which resulted in greater oxygen consumption [82].
4. Summary of the evaluation methods for the above ergonomic issues
Facing the ergonomic evaluation of virtual reality, there are different evaluation indexes and methods for different problems, which are summarized in Table 1.
5. Conclusion
In this paper, we summarized the ergonomics research of virtual reality and introduced subjective and objective evaluation methods for related issues. Based on the above review, we consider that there are three trends in future research:
(1) First and foremost, we should enhance the development of VR hardware.
From the various human-caused problems listed in the text, it can be found that problems concerning VR hardware are serious problems that limit the development of the virtual reality industry and affect the user experience, and emphasis should be placed on enhancing the development technology of the virtual reality headset hardware system. Methods such as reducing latency and flicker and increasing display resolution can effectively reduce VR-related diseases.
(2) We should refine design guidelines for VR software content.
Virtual reality-related illnesses often prevent users from experiencing virtual reality-designed content for long periods. In terms of improving user experience from VR software, we believe that VR content developers should consider not only the design of the content but also whether the user will feel any discomfort due to unsuitable VR content, such as the speed of scene switching and the dynamic effect of the interface. In the future, we can refine the design guidelines of VR software content through in-depth research.
(3) We should establish the design model based on human factors and a comprehensive evaluation system for head-up displays.
By clarifying the mapping relationship between the design parameters of product modeling characteristics and human factors evaluation indicators, we can provide a theoretical basis and data support for the improved design of products. In the future, we can consider customizing HMD according to personal conditions such as head circumference to reduce the current local pressure and light leakage caused by improper size. Combining subjective evaluation by experts and statistical analysis of data, a comprehensive evaluation index system for human factors of the headset is gradually constructed to form a complete set of subjective and objective evaluation methods.
Ethical approval
Not applicable.
Informed consent
Not applicable.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Acknowledgments
The authors thank the editors and the reviewers for their helpful suggestions on earlier versions of this manuscript.
Funding
This study was partly supported by the National Natural Science Foundation of China (No. 51905175), the second Batch of 2020 MOE of PRC Industry-University Collaborative Education Program (Program No. 202101042012, Kingfar-CES “Human Factors and Ergonomics” Program), Shanghai Pujiang Talent Program (No. 2019PJC021), the Shanghai Soft Science Key Project (No. 21692196800) and the Smart Travel Art Design Innovation Laboratory (No.20212679).
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