Enhanced Presence Evaluation in Virtual Reality Feedback System with TOPSIS Model

AbstractResearcher has been trying to optimize the method for evaluating presence in virtual reality (VR) to address variability and uncertainty in quick evaluations using questionnaires. We recommend using the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) model to calculated the iGroup Presence Questionnaire to measure users’ overall presence in VR prototyping, instead of the weighted sum approach. The effects of two presence factors (scene density and motion trajectory technology) on a self-developed VR swimming virtual system were tested using the TOPSIS model with 20 participants each 12 tasks in a user experiment. The results were compared using two different weighting methods, fuzzy hierarchical analysis and uniform weighting methods. TOPSIS had a narrower range of data within the 95% confidence interval and a significantly lower coefficient of variation (CV). This indicates enhanced precision in evaluating presence and can be used to compare different technique setting of virtual systems.Keywords: Virtual realitypresence evaluationfuzzy analytic hierarchy processhuman computer interactiontechnique order performance by similarity to ideal solution Disclosure statementWe declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service, and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled, “Enhanced Presence Evaluation in Virtual Reality Feedback System with TOPSIS Model.”Additional informationFundingThis work was supported by the National Key Research and Development Program under Grant [2022YFB3303303].Notes on contributorsShuo LiShuo Li is a PhD candidate at the School of Design, Shanghai Jiao Tong University (SJTU). She received her master’s degree in industrial design engineering from Zhejiang University (ZJU). Her research interests include human-computer interaction, VR and olfactory interface.Hongtao ZhengHongtao Zheng is a PhD candidate at the School of Design, Shanghai Jiao Tong University (SJTU). He received his master’s degree in design science from Harbin Institute of Technology (HIT). His research interests include persuasive technique and human–autonomy interaction.Ting HanTing Han received the PhD degree from the college of computer science and technology, Zhejiang University (ZJU). He is a Professor of the School of Design and also a Distinguished Professor with the Institute of Medical Robotics, Shanghai Jiao Tong University (SJTU). His research interests include human-computer interaction and healthcare.Jun HuJun Hu has a PhD degree in Interaction Design and an Engineering Doctorate degree in User-system Interaction. He is an Associate Professor in Design Research on Social Computing, and the Scientific Director for the Engineering Doctorate program in Designing Human-System Interaction at Department of Industrial Design, Eindhoven University of Technology.Chenqi ZhangChenqi Zhang is a PhD candidate at the School of Design, Shanghai Jiao Tong University (SJTU). She received her master’s degree in design from SJTU. Her research interests include human-computer interaction and health promotion.Cong YuCong Yu received her Bachelor’s degree from the School of Electronic Information and Electrical Engineering at Shanghai Jiao Tong University (SJTU). She is currently pursuing a Master’s degree from the School of Design, SJTU. Her expertise lies in Python and Unity, and she has developed a strong interest in human-computer interaction.