# VR Sickness Evaluation Method Using Recurrence Period Density Entropy
## 5 Conclusions  
In this study, a standardized method for analyzing VR sickness using the RPDE index is proposed. To validate the effectiveness of this method, comparative experiments were conducted using the most periodic and representative physiological data, namely, heart ECG data. By comparing the pre- (baseline session) and post-adaptation (evaluation session) states of VR sickness, SSQ and ECG data were collected according to the VR sickness and non-VR sickness. Subsequently, statistical analysis was conducted on the SSQ to determine whether VR sickness occurred during the two sessions. The results revealed significant differences in the nausea and oculomotor discomfort domains of the SSQ scores, confirming the significance of the differences between the VR and non-VR sickness. Because significant differences in VR sickness were observed between the two sessions in the two domains, the RPDE values were extracted to validate whether the RPDE was associated with VR sickness in each state. Correlation analysis was performed to determine whether the extracted RPDE data were directly related to VR sickness. The analysis revealed that the correlation coefficients between the two VR sickness domains and RPDE values did not reach the 95% confidence level (\(p<0.05\)), indicating that a correlation between the RPDE values and VR sickness (SSQ scores) could not be established. Therefore, considering the RPDE values themselves as indicative of individual variability in physiological data, attention was directed toward analyzing the changes in these values. To ascertain whether the changes in RPDE values were significant in the two sessions where the VR sickness was confirmed, a bootstrap analysis was conducted. The results showed a difference of 0.065 between the two groups, confirming the significance at the 95% confidence level. The results of this study are discussed based on the aforementioned experimental results. The conclusions are summarized as follows:  
First, RPDE values are considered as individual metrics of physiological indicators, and the variation in RPDE values suggests their potential function as a measure of VR sickness. Second, the RPDE values may have identified subtle differences that were not captured in the subjective survey data. Third, the RPDE values of the periodic physiological data can be used as new and common indicators to measure VR sickness. Therefore, if this method is effective for other periodic physiological datasets, it could be used as an integrated metric. If such an integrated metric is used, the proposed method is expected to contribute to the scoring and standardization of VR sickness. Furthermore, if VR sickness can be scored or standardized using a single criterion, the indicator can be used as a benchmark. The future research of this study involves integrating VR technology by utilizing the proposed method as a metric for real-time monitoring and adaptive interventions. Conceptualization, Y.S.K. ; methodology, Y.S.K. and R.L. ; software, R.L. ; validation, Y.S.K. and R.L. ; formal analysis, R.L. ; investigation, Y.S.K. and R.L. ; resources, R.L. ; data curation, R.L. ; writing--original draft preparation, R.L. ; writing--review and editing, Y.S.K. ; visualization, R.L. ; supervision, Y.S.K. ; project administration, Y.S.K. ; funding acquisition, Y.S.K. All authors have read and agreed to the published version of the manuscript. This study received no external funding. The study was conducted in accordance with the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of the Korea University of Technology and Education (approval 21052602). Informed Consent Statement: Informed consent was obtained from all participants involved in the study. The data presented in this study are available upon request from the corresponding author. The data are not publicly available because of the significant investment in time and money required for data acquisition.