This study investigated the effects of the target size and movement distance on user performance and workload in a virtual reality (VR) environment. In a repeated-measures laboratory study, 36 participants (18 male and 18 female) performed the drag-and-drop task as a standard human–computer interaction (HCI) task with different target sizes (1, 1.5, 2, 2.5, and 3 cm) and movement distances (5, 9, 13, 17, and 20 cm). Task completion time (TCT), error rate, and movement time (MT) were measured as performance indices, whereas physical load and effort were assessed as workload indices. The results demonstrated that the target size and movement distance significantly affected all performance measures and workload indices. Large target sizes produced better performance and lower workloads; however, large movement distances decreased performance and increased workload. However, sex had no significant effect on the performance or workload during the drag-and-drop tasks. The best target sizes were 2.5 and 3 cm, and the worst size was 1 cm. The best movement distances were 5 and 9 cm, and the worst distance was 20 cm. The results of this study can provide useful reference information for developing VR technology based on human factors and demonstrate that additional basic research is required to reflect the distinctive features of VR in the future.

Virtual reality (VR) users experience unwanted symptoms, such as body imbalance, nausea, dizziness, and loss of presence. This study aims to investigate the effects of posture and locomotion on postural stability, cybersickness, and presence in VR environments. Twenty participants played a VR game under different conditions depending on posture (standing and sitting) and locomotion methods (joystick and teleportation), and seven dependent variables (COM, AP displacement, ML displacement, ASL, PSQ, VRSQ, and SOP) were analyzed to observe postural stability, cybersickness, and presence. The results revealed that postural instability increased when the task was performed in the standing posture with the joystick locomotion method compared to other conditions. The AP displacement, ML displacement, and ASL were lower under teleportation conditions. The PSQ scores indicated that postural stability was better in the sitting posture than in the standing posture. The VRSQ score revealed that the sitting with teleportation condition had less cybersickness than the other conditions. The SOP score was the highest in the standing posture with the teleportation condition. This study concludes that a sitting posture with teleportation locomotion can be considered when designing games in which users actively interact with virtual movements.

With a growing interest in head-mounted display (HMD)-based virtual reality (VR) environments, there have been lots of studies enhancing user experience (UX) in the context. In particular, the study of motion sickness (MS) symptoms, which are a major barrier to providing a positive UX, is of high importance. This study investigated the effects of degree of freedom (DOF) and field of view (FOV) of HMD on MS symptoms. A user experiment was designed based on a 2 × 2 mixed design with DOF as a between-subject design variable (3-DOF and 6-DOF) and FOV as a within-subject design variable (Narrow and Wide). Participants experienced VR game content in four conditions in random order. MS symptoms were captured using heart rate variability (HRV) and virtual reality sickness questionnaire (VRSQ) at the pre- and post-task moment. The results showed that MS symptoms occurred more in the 3-DOF condition than in the 6-DOF. Further, MS symptoms in DOF conditions were adjusted depending on the FOV. In the Wide condition, we found a significant difference in MS symptoms depending on the DOF, but in the Narrow condition, no significant differences were found. Through this finding, we were able to not only show the effectiveness of HRV as MS measures but also provide meaningful design insights into HMD-based VR practices.

Industry 4.0 is potentially innovative in the workers’ role, which is becoming increasingly involved in smart activities. In this situation, it is necessary to improve highly repetitive uncomfortable working postures to reduce physical risks. This study intends to assess physical risks during VR interaction for manufacturing work. Posture-related physical risk levels were calculated using ergonomic risk assessment tools RULA, REBA, and OWAS. Three task conditions were considered for the experiment in a VR-based car-assembly environment. An analysis of variance was applied to investigate significant differences between task conditions, and it suggested that a higher risk level was obtained while working in the overhead position for RULA and REBA, whereas the squatting position obtained a higher risk level for OWAS. Sensitivity analysis identified that the upper arm and neck were responsible for the highest risk level for RULA, the upper arm, neck, and trunk for REBA, and the back posture parameter for OWAS.