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REVIEW 3 major objections 6 minor 233 references

From Adaptation to Intelligence: A Systematic Review of Data, Strategies, and Impact in Personalized VR

T0 review · 3 major / 6 minor · reviewed 2026-08-04 · deepseek-v4-flash

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Pith's one-line read Personalized virtual reality, the paper argues, is not a patchwork of domain-specific tricks but one shared five-stage closed-loop process — sense, process, decide, update, re-sense — that runs through every application area it reviewed.

desk verdict A useful and well-organized review with a credible unifying framework, but un-auditable corpus reporting and PRISMA inconsistencies need fixing before it can serve as a reliable census of the field. read the letter →

arxiv 2510.13123 v2 pith:DTBRAHHB submitted 2025-10-15 cs.HC

Tangyao Li , Yitong Zhu , Hai-Ning Liang , Yuyang Wang This is my paper · ORCID
classification cs.HC
keywords adaptivevirtualrealitypersonalizedinteractionsystematicreviewfive-stageframeworkphysiologicalsensingmachinelearningadaptationuserexperienceevaluationVRimplementationchallenges
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This systematic review of more than 130 studies claims that adaptive virtual reality systems across all application domains share a common closed-loop architecture. The authors organize this architecture into five stages — input collection, data processing, adaptive logic, system update, and feedback loop — and use it to unify findings from rehabilitation, mental health, accessibility, education, gaming, and navigation. They identify emerging trends: growing use of multimodal physiological and behavioral sensing, a shift from purely reactive to hybrid reactive-proactive adaptation, and increasing reliance on AI techniques including large language models. They also argue that current systems work well in controlled, short-term settings, but that long-term impact, scalability, evaluation comparability, and privacy remain unresolved.

What carries the argument

The central organizing object is the five-stage adaptive pipeline: input collection, data processing, adaptive logic, system update, and feedback loop. This named framework carries the argument by providing a single lens through which the review categorizes sensing modalities, adaptation mechanisms (rule-based versus machine learning), and adaptive objectives (difficulty adjustment, display adaptation, environment manipulation, feedback personalization). The framework is what lets the authors claim that results from one domain can inform another and that the field's trends are coherent rather than scattered.

What would settle it

A reader could examine the paper's own flow diagram and reference list: if the 659 screened records cannot be reconciled with the reported counts at each exclusion stage, or if a meaningful number of the 132 included studies fall outside the stated 2014–2025 window, then the corpus is not what it claims to be, and the generality of the five-stage framework would rest on an unrepresentative sample.

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Extended reading notes

Core claim

The paper's central claim is that personalization in VR is one general five-stage closed-loop process, not a collection of unrelated methods. In every reviewed system, user information — physiological, behavioral, or demographic — is captured through continuous sensing, cleaned and structured, interpreted by rule-based or machine-learned logic, used to update the virtual environment, and then re-measured so the loop can repeat. The authors argue this structure appears across rehabilitation, mental health, accessibility, education, training, gaming, and navigation, and they chart the field's trajectory: multimodal sensor fusion, a move toward hybrid reactive/proactive systems, and AI-driven a

Load-bearing premise

The load-bearing premise is that the 132 papers reviewed form a representative, correctly screened sample of adaptive-VR research from 2014 to 2025; if the screening arithmetic or date filters were applied inconsistently — the flow diagram lists only 15 records after duplicates removed while 659 records were screened, and some cited studies predate 2014 — then the five-stage framework and trend claims may describe a skewed slice of the literature rather than the field as a wh

Editorial extensions

If this is right

  • If the five-stage framework is correct, personalization techniques developed in one application domain should transfer to another that runs the same loop — for example, dynamic difficulty adjustment from games could be applied to rehabilitation exercises.
  • The identified shift toward hybrid reactive/proactive systems implies future VR systems will be expected to anticipate user state, not merely react to it, which requires more accurate user-state prediction models.
  • The growing adoption of AI, including LLM-driven NPCs and generative content, points toward scalable personalization where virtual environments and conversations adapt on the fly rather than being hand-authored.
  • Standardized evaluation protocols and benchmark datasets are prerequisites for comparing personalization strategies across studies, since the current diversity of measures and the absence of shared datasets limit comparability.
  • The challenges the review identifies — real-time processing, sensor noise, privacy, and scalability — are the concrete barriers that must be addressed before personalized VR leaves the laboratory.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • A testable extension of the review's claim is that adaptive VR systems could be built as interchangeable modules: swapping the sensing stage (say, EEG for eye tracking) while keeping the same adaptive logic should preserve system effectiveness. The paper does not test this modularity claim directly.
  • The review's observation that most systems are reactive suggests a concrete comparative study: running proactive versus reactive versions of the same adaptive task, measuring engagement, performance, and sense of control. The paper identifies the gap but does not run such comparisons.
  • If evaluation comparability is the bottleneck the authors say it is, then their analysis implies the field's next step is a domain-specific benchmark dataset for VR personalization, analogous to image-recognition benchmarks. The review calls for such datasets but does not build one.
  • A re-audit of the paper's own screening data is warranted before its trend claims are used to guide research agendas: the flow diagram reports 'records after duplicates removed (n = 15)' while 659 records were screened, and the reference list includes studies from 2012 and 2013 that fall outside the stated 2014–2025 inclusion window.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 6 minor

Summary. This systematic review examines 132+ studies on personalized/adaptive VR interaction, focusing on how user data (physiological, behavioral, contextual) is used to drive adaptation mechanisms. The authors propose a five-stage closed-loop framework (input collection, data processing, adaptation logic, system update, feedback loop) and identify trends toward multimodal sensing, hybrid reactive/proactive adaptation, and increasing use of AI, while also cataloging challenges in real-time processing, signal accuracy, and privacy. The review is organized around three research questions addressing technological implementation, UX evaluation, and implementation challenges.

Significance. If the corpus is representative and correctly screened, the review offers a useful synthesis of a fragmented literature, and the five-stage framework provides a clear organizing structure for future work. The explicit focus on combining sensing and adaptation—rather than treating them separately—addresses a genuine gap. The paper is also commendable for its broad coverage of domains (rehabilitation, mental health, accessibility, education, gaming), its detailed tables of questionnaires and ML techniques, and its balanced discussion of challenges. However, the value of the framework and the trend claims rests on the auditability of the reviewed corpus, and that auditability is currently compromised by internal inconsistencies in the PRISMA flow diagram and by included studies that violate the stated date window.

major comments (3)
  1. [§3.2.1 / Fig. 1] The PRISMA flow diagram is internally inconsistent. Records identified are 543 + 131 = 674; the diagram states 'Records after duplicates removed (n = 15)' but then 'Records screened by Abstract (n = 659)'. Since 659 = 674 − 15, the label after duplicates removed should be 659, not 15. The text also says 'over 132 studies' while the diagram reports exactly 132. These discrepancies make the screening process unverifiable and must be corrected and reconciled in a revised flow diagram.
  2. [§3.2.1 / §4.4.1 / Table 2] The inclusion criteria state that only studies published from 2014 to 2025 are eligible, yet the review includes studies outside this window. Ref. [104] (Lahiri et al., 2012) is listed in Table 2 as a study using the SUS, and Ref. [143] (Park et al., 2013) is cited in §4.4.1 as an example of gait training. No inclusion list or screening log is supplied. This inconsistency directly undermines the representativeness of the corpus on which the five-stage framework and the trend claims (multimodal sensing, hybrid reactive/proactive, AI adoption) rest. The authors must either exclude out-of-window studies or revise the stated date window, and should provide the full list of included studies with screening decisions as an appendix.
  3. [§5.1.1 / Fig. 3] The paper asserts several 'emerging trends' (e.g., increasing integration of multimodal physiological data, transition to hybrid reactive/proactive adaptation, adoption of AI) but does not present a temporal or coded quantitative analysis supporting these claims. Fig. 3 gives percentages but no per-year breakdown or coding rubric for how studies were categorized. Since the corpus is not auditable (see previous comments), these trend claims are not verifiable. The authors should either provide the underlying coded data (e.g., counts by year and category) or explicitly temper these claims to reflect qualitative observation rather than systematic trend analysis.
minor comments (6)
  1. [§1.1 / Fig. 1] The text says 'over 132 studies' in §4, while Fig. 1 reports exactly 132 included. Please make the number consistent (e.g., '132 studies').
  2. [§4.2.1] GEQ is cited as [81, 174]; the correct references for the Game Experience Questionnaire should be [81, 152] (as in Table 2).
  3. [Table 2] AttrakDiff-Short is cited as [167] in Table 2, but the text in §4.2.1 cites it as [73]. Please align these citations.
  4. [§3.2.1] The stated window 'last 10 years (from 2014 to 2025)' actually spans up to 12 years depending on the cutoff month. Please specify the exact search date range (e.g., January 2014–October 2025).
  5. [§5.1.1] Typo: 'biosignals such as EEG, GSE, EDA, and HR' should be 'GSR' instead of 'GSE'.
  6. [Throughout] Several typos and inconsistencies should be cleaned: 'scability' (§6), 'conputationally' (Table 4), 'dependecies' (Table 4), 'explic programm' (Table 4), 'embodiement' (Table 4), 'Cladue-3' (§5.1.3), 'Augest' (Refs [140,164]).

Circularity Check

0 steps flagged · score 2.0 of 10

No significant circularity; the five-stage framework is an analytic synthesis, and the PRISMA/date issues are correctness risks rather than circular steps.

full rationale

This is a qualitative systematic review, not a derivation. The central deliverable is the five-stage pipeline (input collection, data processing, adaptive logic, system update, feedback loop) used to organize the reviewed systems. That pipeline is introduced as 'typically involving' (Sec. 4.3) and then used as an analytic lens (Sec. 5.1, Fig. 5); it is an abstraction imported from the adaptive-systems literature (e.g., [9]) and applied to the corpus, not a quantity fitted to the corpus, so no prediction reduces by construction to its inputs. The trend claims (multimodal sensing, hybrid reactive/proactive, AI uptake) are empirical summaries of the included 132 papers; their reliability depends on corpus representativeness, which is a correctness/validity concern, not circularity. The flow-diagram label 'Records after duplicates removed (n = 15)' is evidently a labeling error: 543+131-15 = 659 reconciles with the screened count, and the cited 2012/2013 papers (Refs. [104], [143]) outside the stated 2014-2025 window raise screening-consistency questions; these affect the strength of the empirical claims but do not create a self-referential derivation. Several self-citations ([203], [205]-[207], [229]) occur as illustrative examples in tables and discussion; none is load-bearing for the framework or main trends. No circular step is exhibited.

Assumptions & free parameters 0 free parameters · 4 assumptions · 1 invented entities

The central synthesis rests on the completeness and faithful coding of the 132-study corpus, but the PRISMA count error and date-rule violations weaken that foundation. The review also assumes that widely different self-report and biosignal instruments can be sensibly discussed together. There are no numerical free parameters because this is a qualitative review.

assumptions (4)
  • domain assumption The published literature captured by the stated query and databases is representative of personalized VR research.
    Section 3. If the search missed adaptive VR work that does not use the 'personalized user interaction' wording, the framework and trends may be incomplete.
  • ad hoc to paper Each included study was faithfully categorized into the five pipeline stages and application domains.
    Section 5.1 and Figure 5. The coding rubric is not provided, so the categorization rests on the authors' judgment.
  • domain assumption PRISMA is the appropriate reporting standard and the reported counts are accurate.
    Section 3 and Figure 1. The flow diagram's 'n = 15' after duplicates vs 659 screened undermines this assumption.
  • domain assumption Self-reported UX instruments (SSQ, PQ, SUS, NASA-TLX, etc.) and biosignals are commensurable enough to support cross-study synthesis.
    Section 4.2. The review aggregates findings across many different instruments without a formal meta-analytic framework.
invented entities (1)
  • Five-stage pipeline (input collection, data processing, adaptive logic, system update, feedback loop)
    purpose: Unify adaptive VR mechanisms across application domains
    Introduced as the paper's central synthesis; it is a descriptive taxonomy, not an independently falsifiable entity, and it overlaps with the three-stage framework cited from [9].

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Cite this review

Pith. "Pith review of From Adaptation to Intelligence: A Systematic Review of Data, Strategies, and Impact in Personalized VR." pith.science (2026). https://pith.science/paper/DTBRAHHB

@misc{pith2026251013123,
  author       = {Pith},
  title        = {Pith review of: From Adaptation to Intelligence: A Systematic Review of Data, Strategies, and Impact in Personalized VR},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/DTBRAHHB}},
  note         = {Machine review of arXiv:2510.13123}
}
read the original abstract

As virtual reality (VR) systems advance, they are increasingly expected to adapt intelligently to individual users' states, abilities, and preferences. While prior research has examined user-state sensing and adaptive interaction design in VR, existing reviews typically address these aspects in isolation. In this paper, we examine the growing body of research on personalization in VR, with a particular focus on how user data collected during immersion is used to drive adaptive strategies that tailor the experience and enhance engagement, performance, or other specific goals. We synthesize findings from studies that employ adaptive techniques across diverse application domains and summarize a five-stage conceptual framework that unifies adaptive mechanisms across domains. Our analysis reveals emerging trends, including the integration of multimodal sensors, the transition from purely reactive to hybrid adaptation systems, and the adoption of artificial intelligence approaches. Finally, we identify key challenges related to data, modeling, and evaluation, and outline future research directions toward more effective and user-centered VR systems.

Figures

Figures reproduced from arXiv: 2510.13123 by the authors.

Figure 1
Figure 1. PRISMA flow diagram detailing the study selection process for the systematic review. [PITH_FULL_IMAGE:figures/full_fig_p006_1.png] view at source ↗
Figure 2
Figure 2. (a) The hardware setup of a multiple-sensorial media platform that provides users with vision, audio, olfaction, and haptic [PITH_FULL_IMAGE:figures/full_fig_p012_2.png] view at source ↗
Figure 3
Figure 3. (a) The percentage distribution of reviewed research papers across different domains. (b) The percentage distribution of [PITH_FULL_IMAGE:figures/full_fig_p015_3.png] view at source ↗
Figures from the paper (4 more)
Figure 4
Figure 4. Figure 4: (a) Input modalities (physiological and behavioral data) are fed into the adaptive mechanism powered by AI techniques [PITH_FULL_IMAGE:figures/full_fig_p017_4.png]
Figure 5
Figure 5. Figure 5: General pipeline for adaptive VR systems for personalized user experiences, including (1) input collection, (2) data processing, [PITH_FULL_IMAGE:figures/full_fig_p018_5.png]
Figure 6
Figure 6. Figure 6: The structure of the MultiModal InfoMax model [ [PITH_FULL_IMAGE:figures/full_fig_p020_6.png]
Figure 7
Figure 7. Figure 7: A user interface, RealityLens [202], that allows users to (a) communicate, (b) interact, and (c) avoid obstacles in the physical world in VR. This interface is customizable in terms of size and placement. virtual environments. First, it is believed that engaging more h…

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Reference graph

Works this paper leans on

233 extracted references · 3 linked inside Pith

  1. [104]

    Uttama Lahiri, Esubalew Bekele, Elizabeth Dohrmann, Zachary Warren, and Nilanjan Sarkar. 2012. Design of a virtual reality based adaptive response technology for children with autism.IEEE Transactions on Neural Systems and Rehabilitation Engineering21, 1 (2012), 55–64

    2012

  2. [143]

    Yu-Hyung Park, Chi-ho Lee, and Byoung-Hee Lee. 2013. Clinical usefulness of the virtual reality-based postural control training on the gait ability in patients with stroke.Journal of exercise rehabilitation9, 5 (2013), 489

    2013

  3. [9]

    Christopher Baker and Stephen H Fairclough. 2022. Adaptive virtual reality. InCurrent research in neuroadaptive technology. Elsevier, 159–176

    2022

  4. [1]

    César Iván Aguilar Reyes, David Wozniak, Angel Ham, and Maryam Zahabi. 2023. Design and evaluation of an adaptive virtual reality training system.Virtual Reality27, 3 (2023), 2509–2528

    2023

  5. [2]

    Nahdatul Akma Ahmad, Azaliza Zainal, Muhammad Fairuz Abd Rauf, Tengku Shahrom, Tengku Shahdan, Fadia Razali, Noor Hidayah Azmi, MH MOhd-Yussof, and Zirawani Baharum. 2020. Development of virtual reality game for the rehabilitation of upper limb control in the elderly patients Manuscript submitted to ACM Adapting to the User: A Systematic Review of Persona...

    2020

  6. [3]

    Rawan Alghofaili, Yasuhito Sawahata, Haikun Huang, Hsueh-Cheng Wang, Takaaki Shiratori, and Lap-Fai Yu. 2019. Lost in style: Gaze-driven adaptive aid for vr navigation. InProceedings of the 2019 CHI conference on human factors in computing systems. Association for Computing Machinery, New York, NY, USA, 1–12

    2019

  7. [4]

    Aliza Aliza, Irene Zaugg, Elif Celik, Wolfgang Stuerzlinger, Francisco Raul Ortega, Anil Ufuk Batmaz, and Mine Sarac. 2024. Eye-hand coordination training: A systematic comparison of 2d, vr, and ar display technologies and task instructions. In2024 IEEE Conference Virtual Reality and 3D User Interfaces (VR). IEEE, 200–210

    2024

  8. [5]

    Ferran Argelaguet. 2014. Adaptive navigation for virtual environments. In2014 IEEE symposium on 3D user interfaces (3DUI). IEEE, 123–126

    2014

Show all 233 references
  1. [6]

    Justin Asbee, Kimberly Kelly, Timothy McMahan, and Thomas D Parsons. 2023. Machine learning classification analysis for an adaptive virtual reality Stroop task.Virtual Reality27, 2 (2023), 1391–1407

    2023

  2. [7]

    Trevor Ashby, Braden K Webb, Gregory Knapp, Jackson Searle, and Nancy Fulda. 2023. Personalized quest and dialogue generation in role-playing games: A knowledge graph-and language model-based approach. InProceedings of the 2023 CHI Conference on Human Factors in Computing Syst...

    2023

  3. [8]

    Md Aashikur Rahman Azim, Zihao Su, and Seongkook Heo. 2025. Your Hands Can Tell: Detecting Redirected Hand Movements in Virtual Reality. InProceedings of the 2025 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, USA, 1–14

    2025

  4. [10]

    Esubalew Bekele, Joshua Wade, Dayi Bian, Jing Fan, Amy Swanson, Zachary Warren, and Nilanjan Sarkar. 2016. Multimodal adaptive social interaction in virtual environment (MASI-VR) for children with Autism spectrum disorders (ASD). In2016 IEEE virtual reality (VR). IEEE, 121–130

    2016

  5. [11]

    Brett Benda, Benjamin Rheault, Yanna Lin, and Eric D Ragan. 2024. Examining Effects of Technique Awareness on the Detection of Remapped Hands in Virtual Reality.IEEE Transactions on Visualization and Computer Graphics30, 5 (2024), 2651–2661

    2024

  6. [12]

    Mohamed S Benlamine, Aude Dufresne, Miriam H Beauchamp, and Claude Frasson. 2021. BARGAIN: behavioral affective rule-based games adaptation interface–towards emotionally intelligent games: application on a virtual reality environment for socio-moral development.User Modeling a...

    2021

  7. [13]

    Kamilla Bergsnev and Ana Luisa Sánchez Laws. 2022. Personalizing virtual reality for the research and treatment of fear-related disorders: A mini review.Frontiers in Virtual Reality3 (2022), 834004

    2022

  8. [14]

    Simon Besga, Nancy Rodriguez, Arnaud Sallaberry, Thomas Papastergiou, and Pascal Poncelet. 2025. Task-blind adaptive virtual reality: Is it possible to help users without knowing their assignments?Virtual Reality29, 1 (2025), 35

    2025

  9. [15]

    Dinesh Bhugra, Alex Till, and Norman Sartorius. 2013. What is mental health? 3–4 pages

    2013

  10. [16]

    Dayi Bian, Joshua Wade, Amy Swanson, Amy Weitlauf, Zachary Warren, and Nilanjan Sarkar. 2019. Design of a physiology-based adaptive virtual reality driving platform for individuals with ASD.ACM Transactions on Accessible Computing (TACCESS)12, 1 (2019), 1–24

    2019

  11. [17]

    Frank Biocca. 1997. The cyborg’s dilemma: Progressive embodiment in virtual environments.Journal of computer-mediated communication3, 2 (1997), JCMC324

    1997

  12. [18]

    Loën Boban, Lucas Strauss, Hugo Decroix, Bruno Herbelin, and Ronan Boulic. 2023. Unintentional synchronization with self-avatar for upper-and lower-body movements.Frontiers in Virtual Reality4 (2023), 1073549

    2023

  13. [19]

    Efe Bozkir, David Geisler, and Enkelejda Kasneci. 2019. Person independent, privacy preserving, and real time assessment of cognitive load using eye tracking in a virtual reality setup. In2019 IEEE conference on virtual reality and 3D user interfaces (VR). IEEE, 1834–1837

    2019

  14. [20]

    Margaret M Bradley and Peter J Lang. 1994. Measuring emotion: the self-assessment manikin and the semantic differential.Journal of behavior therapy and experimental psychiatry25, 1 (1994), 49–59

    1994

  15. [21]

    Susanna Brambilla, Giuseppe Boccignone, Alberto Nunzio Borghese, Daniele Croci, and Laura Anna Ripamonti. 2023. Tuning Stressful Experience in Virtual Reality Games. InProceedings of the 15th Biannual Conference of the Italian SIGCHI Chapter. Association for Computing Machiner...

    2023

  16. [22]

    John Brooke et al. 1996. SUS-A quick and dirty usability scale.Usability evaluation in industry189, 194 (1996), 4–7

    1996

  17. [23]

    Oscar I Caldas, Mauricio Mauledoux, Oscar F Aviles, and Carlos Rodriguez-Guerrero. 2024. Breaking presence in immersive virtual reality toward behavioral and emotional engagement.Computer Methods and Programs in Biomedicine248 (2024), 108124

    2024

  18. [24]

    James Calvert and Rhodora Abadia. 2020. Impact of immersing university and high school students in educational linear narratives using virtual reality technology.Computers & Education159 (2020), 104005

    2020

  19. [25]

    Julian Felipe Villada Castillo, Maria Fernanda Montoya Vega, John Edison Muñoz Cardona, David Lopez, Leonardo Quiñones, Oscar Alberto Henao Gallo, and Jose Fernando Lopez. 2024. Design of virtual reality exergames for upper limb stroke rehabilitation following iterative design...

    2024

  20. [26]

    Philippe Chan, Tom Van Gerven, Jean-Luc Dubois, and Kristel Bernaerts. 2023. Study of motivation and engagement for chemical laboratory safety training with VR serious game.Safety Science167 (2023), 106278

    2023

  21. [27]

    David Checa and Andres Bustillo. 2020. A review of immersive virtual reality serious games to enhance learning and training.Multimedia tools and applications79, 9 (2020), 5501–5527

    2020

  22. [28]

    Shu-Yu Chen, Yu-Kun Lai, Shihong Xia, Paul L Rosin, and Lin Gao. 2022. 3D face reconstruction and gaze tracking in the HMD for virtual interaction.IEEE Transactions on Multimedia25 (2022), 3166–3179. Manuscript submitted to ACM 28 Li et al

    2022

  23. [29]

    Yi Fei Cheng, Christoph Gebhardt, and Christian Holz. 2023. Interactionadapt: Interaction-driven workspace adaptation for situated virtual reality environments. InProceedings of the 36th Annual ACM Symposium on User Interface Software and Technology. Association for Computing ...

    2023

  24. [30]

    Vuthea Chheang, Shayla Sharmin, Rommy Márquez-Hernández, Megha Patel, Danush Rajasekaran, Gavin Caulfield, Behdokht Kiafar, Jicheng Li, Pinar Kullu, and Roghayeh Leila Barmaki. 2024. Towards anatomy education with generative AI-based virtual assistants in immersive virtual rea...

    2024

  25. [31]

    Francesco Chiossi, Changkun Ou, Carolina Gerhardt, Felix Putze, and Sven Mayer. 2025. Designing and evaluating an adaptive virtual reality system using eeg frequencies to balance internal and external attention states.International Journal of Human-Computer Studies196 (2025), 103433

    2025

  26. [32]

    Francesco Chiossi, Changkun Ou, and Sven Mayer. 2024. Optimizing visual complexity for physiologically-adaptive vr systems: Evaluating a multimodal dataset using eda, ecg and eeg features. InProceedings of the 2024 International Conference on Advanced Visual Interfaces. Associ...

    2024

  27. [33]

    Francesco Chiossi, Yagiz Turgut, Robin Welsch, and Sven Mayer. 2023. Adapting visual complexity based on electrodermal activity improves working memory performance in virtual reality.Proceedings of the ACM on Human-Computer Interaction7, MHCI (2023), 1–26

    2023

  28. [34]

    Jin Woo Choi, Haram Kwon, Jaehoon Choi, Netiwit Kaongoen, Chaeeun Hwang, Minuk Kim, Byung Hyung Kim, and Sungho Jo. 2023. Neural applications using immersive virtual reality: a review on EEG studies.IEEE Transactions on Neural Systems and Rehabilitation Engineering31 (2023), 1645–1658

    2023

  29. [35]

    Théo Combe, Jean-Rémy Chardonnet, Frédéric Merienne, and Jivka Ovtcharova. 2023. CAVE and HMD: distance perception comparative study. Virtual Reality27, 3 (2023), 2003–2013

    2023

  30. [36]

    Carolina Cruz-Neira, Daniel J Sandin, Thomas A DeFanti, Robert V Kenyon, and John C Hart. 1992. The CAVE: Audio visual experience automatic virtual environment.Commun. ACM35, 6 (1992), 64–73

    1992

  31. [37]

    Adyasha Dash and Uttama Lahiri. 2019. Design of virtual reality-enabled surface electromyogram-triggered grip exercise platform.IEEE Transactions on Neural Systems and Rehabilitation Engineering28, 2 (2019), 444–452

    2019

  32. [38]

    Jaybie A De Guzman, Kanchana Thilakarathna, and Aruna Seneviratne. 2019. Security and privacy approaches in mixed reality: A literature survey. ACM Computing Surveys (CSUR)52, 6 (2019), 1–37

    2019

  33. [39]

    Edirlei Soares de Lima, Bruno MC Silva, and Gabriel Teixeira Galam. 2022. Adaptive virtual reality horror games based on machine learning and player modeling.Entertainment Computing43 (2022), 100515

    2022

  34. [40]

    Thomas A DeFanti, Daniel Acevedo, Richard A Ainsworth, Maxine D Brown, Steven Cutchin, Gregory Dawe, Kai-Uwe Doerr, Andrew Johnson, Chris Knox, Robert Kooima, et al. 2011. The future of the CAVE.Central European Journal of Engineering1, 1 (2011), 16–37

    2011

  35. [41]

    Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei. 2009. Imagenet: A large-scale hierarchical image database. In2009 IEEE conference on computer vision and pattern recognition. Ieee, 248–255

    2009

  36. [42]

    Arindam Dey, Alex Chatburn, and Mark Billinghurst. 2019. Exploration of an EEG-based cognitively adaptive training system in virtual reality. In 2019 ieee conference on virtual reality and 3d user interfaces (vr). IEEE, 220–226

    2019

  37. [43]

    Zhi-Chao Dong, Wenming Wu, Zenghao Xu, Qi Sun, Guanjie Yuan, Ligang Liu, and Xiao-Ming Fu. 2021. Tailored reality: Perception-aware scene restructuring for adaptive vr navigation.ACM Transactions on Graphics (TOG)40, 5 (2021), 1–15

    2021

  38. [44]

    Qiuxin Du, Zhen Song, Haiyan Jiang, Xiaoying Wei, Dongdong Weng, and Mingming Fan. 2024. LightSword: A customized virtual reality exergame for long-term cognitive inhibition training in older adults. InProceedings of the 2024 CHI Conference on Human Factors in Computing System...

    2024

  39. [45]

    Ilana Dubovi. 2022. Cognitive and emotional engagement while learning with VR: The perspective of multimodal methodology.Computers & Education183 (2022), 104495

    2022

  40. [46]

    John Dudley, Lulu Yin, Vanja Garaj, and Per Ola Kristensson. 2023. Inclusive Immersion: a review of efforts to improve accessibility in virtual reality, augmented reality and the metaverse.Virtual Reality27, 4 (2023), 2989–3020

    2023

  41. [47]

    Marie Eckert, Emanuël AP Habets, and Olli S Rummukainen. 2021. Cognitive load estimation based on pupillometry in virtual reality with uncontrolled scene lighting. In2021 13th international conference on quality of multimedia experience (qomex). IEEE, 73–76

    2021

  42. [48]

    Martin Feick, Kora Persephone Regitz, Lukas Gehrke, André Zenner, Anthony Tang, Tobias Patrick Jungbluth, Maurice Rekrut, and Antonio Krüger

  43. [49]

    Carlos Flavián, Sergio Ibáñez-Sánchez, and Carlos Orús. 2021. Impacts of technological embodiment through virtual reality on potential guests’ emotions and engagement.Journal of Hospitality Marketing & Management30, 1 (2021), 1–20

    2021

  44. [50]

    Mikhail Fominykh, Ekaterina Prasolova-Førland, Tore C Stiles, Anne Berit Krogh, and Mattias Linde. 2018. Conceptual framework for therapeutic training with biofeedback in virtual reality: First evaluation of a relaxation simulator.Journal of Interactive Learning Research29, 1 ...

    2018

  45. [51]

    Rachel L Franz, Jinghan Yu, and Jacob O Wobbrock. 2023. Comparing locomotion techniques in virtual reality for people with upper-body motor impairments. InProceedings of the 25th international ACM SIGACCESS conference on computers and accessibility. 1–15

    2023

  46. [52]

    Hong Gao, Yiyang Xie, and Enkelejda Kasneci. 2025. PerVRML: ChatGPT-Driven Personalized VR Environments for Machine Learning Education. International Journal of Human–Computer Interaction0, 0 (2025), 1–15

    2025

  47. [53]

    Maria-Jose Garcia-Bonete, Maja Jensen, and Gergely Katona. 2019. A practical guide to developing virtual and augmented reality exercises for teaching structural biology.Biochemistry and Molecular Biology Education47, 1 (2019), 16–24. Manuscript submitted to ACM Adapting to the...

    2019

  48. [54]

    Gheorghita Ghinea and Oluwakemi A Ademoye. 2011. Olfaction-enhanced multimedia: perspectives and challenges.Multimedia Tools and Applications55, 3 (2011), 601–626

    2011

  49. [55]

    Alberto Giaretta. 2024. Security and privacy in virtual reality: a literature survey.Virtual Reality29, 1 (2024), 10

    2024

  50. [56]

    Irene Gironacci. 2022. XR management training simulator supported by content-based scenario recommendation. In2022 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR). IEEE, 104–108

    2022

  51. [57]

    Guilherme Gonçalves, Hugo Coelho, Pedro Monteiro, Miguel Melo, and Maximino Bessa. 2022. Systematic review of comparative studies of the impact of realism in immersive virtual experiences.Comput. Surveys55, 6 (2022), 1–36

    2022

  52. [58]

    Mar Gonzalez-Franco and Tabitha C Peck. 2018. Avatar embodiment. towards a standardized questionnaire.Frontiers in Robotics and AI5 (2018), 74

    2018

  53. [59]

    Sabine Graf, Kinshuk, and Tzu-Chien Liu. 2009. Supporting teachers in identifying students’ learning styles in learning management systems: An automatic student modelling approach.Journal of Educational Technology & Society12, 4 (2009), 3–14

    2009

  54. [60]

    1968.Diagnostic criteria for grading the severity of acute motion sickness

    Ashton Graybiel, Charles D Wood, Earl F Miller II, et al. 1968.Diagnostic criteria for grading the severity of acute motion sickness. Vol. 1030. Naval Aerospace Medical Institute, Naval Aerospace Medical Center

    1968

  55. [61]

    Jesse W Grootjen, Philipp Thalhammer, and Thomas Kosch. 2024. Your eyes on speed: Using pupil dilation to adaptively select speed-reading parameters in virtual reality.Proceedings of the ACM on Human-Computer Interaction8, MHCI (2024), 1–17

    2024

  56. [62]

    Shihui Guo, Wenyi Jiang, Xing Gao, Meili Wang, and Minghong Liao. 2018. Optimizing neural network as locomotion controller with motion data. IEEE Access6 (2018), 26949–26957

    2018

  57. [63]

    Martin Guy, Jean-Marie Normand, Camille Jeunet-Kelway, and Guillaume Moreau. 2023. The sense of embodiment in virtual reality and its assessment methods.Frontiers in Virtual Reality4 (2023), 1141683

    2023

  58. [64]

    Azadeh Hadadi, Jean-Rémy Chardonnet, Christophe Guillet, and Jivka Ovtcharova. 2024. Machine Learning Application for Real-Time Simulator. InProceedings of the 2024 9th International Conference on Machine Learning Technologies. Association for Computing Machinery, New York, NY...

    2024

  59. [65]

    Azadeh Hadadi, Christophe Guillet, Jean-Rémy Chardonnet, Mikhail Langovoy, Yuyang Wang, and Jivka Ovtcharova. 2022. Prediction of cybersickness in virtual environments using topological data analysis and machine learning.Frontiers in Virtual Reality3 (2022), 973236

    2022

  60. [66]

    Christos Hadjipanayi and Despina Michael-Grigoriou. 2022. Arousing a wide range of emotions within educational virtual reality simulation about major depressive disorder affects knowledge retention.Virtual Reality26, 1 (2022), 343–359

    2022

  61. [67]

    Andreas Halbig and Marc Erich Latoschik. 2021. A systematic review of physiological measurements, factors, methods, and applications in virtual reality.Frontiers in virtual reality2 (2021), 694567

    2021

  62. [68]

    Asim Hameed and Andrew Perkis. 2024. Authenticity and presence: Defining perceived quality in VR experiences.Frontiers in Psychology15 (2024), 1291650

    2024

  63. [69]

    Jining Han, Qiyu Zheng, and Yunan Ding. 2021. Lost in virtual reality? Cognitive load in high immersive VR environments.Journal of Advances in Information Technology12, 4 (2021), 302–310

    2021

  64. [70]

    Wei Han, Hui Chen, and Soujanya Poria. 2021. Improving Multimodal Fusion with Hierarchical Mutual Information Maximization for Multimodal Sentiment Analysis. InProceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 9180–9192

    2021

  65. [71]

    Daniel Harley, Alexander Verni, Mackenzie Willis, Ashley Ng, Lucas Bozzo, and Ali Mazalek. 2018. Sensory vr: Smelling, touching, and eating virtual reality. InProceedings of the twelfth international conference on tangible, embedded, and embodied interaction. 386–397

    2018

  66. [72]

    Sandra G Hart. 2006. NASA-task load index (NASA-TLX); 20 years later. InProceedings of the human factors and ergonomics society annual meeting, Vol. 50. Sage publications Sage CA: Los Angeles, CA, 904–908

    2006

  67. [73]

    Marc Hassenzahl, Michael Burmester, and Franz Koller. 2003. AttrakDiff: Ein Fragebogen zur Messung wahrgenommener hedonischer und pragmatischer Qualität. InMensch & computer 2003: interaktion in bewegung. Springer, 187–196

    2003

  68. [74]

    Samar Helou, Nour Khalil, Melissa Daou, and Elie El Helou. 2023. Virtual reality for healthcare: a scoping review of commercially available applications for head-mounted displays.Digital health9 (2023), 20552076231178619

    2023

  69. [75]

    Andreas Hinderks. 2017. Design and evaluation of a short version of the user experience questionnaire (UEQ-S).International Journal of Interactive Multimedia and Artificial Intelligence(2017)

    2017

  70. [76]

    Valentin Holzwarth, Johannes Schneider, Joshua Handali, Joy Gisler, Christian Hirt, Andreas Kunz, and Jan vom Brocke. 2021. Towards estimating affective states in Virtual Reality based on behavioral data.Virtual reality(2021), 1–14

    2021

  71. [77]

    Jasmin Hopf, Melina Scholl, Barbara Neuhofer, and Roman Egger. 2019. Exploring the impact of multisensory VR on travel recommendation: A presence perspective. InInformation and Communication Technologies in Tourism 2020: Proceedings of the International Conference in Surrey, U...

    2019

  72. [78]

    Matt C Howard. 2019. Virtual reality interventions for personal development: A meta-analysis of hardware and software.Human–Computer Interaction34, 3 (2019), 205–239

    2019

  73. [79]

    Sergi Bermudez i Badia, Luis Velez Quintero, Monica S Cameirao, Alice Chirico, Stefano Triberti, Pietro Cipresso, and Andrea Gaggioli. 2018. Toward emotionally adaptive virtual reality for mental health applications.IEEE journal of biomedical and health informatics23, 5 (2018)...

    2018

  74. [80]

    Manuel López Ibáñez, Maximiliano Miranda, Nahum Alvarez, and Federico Peinado. 2021. Using gestural emotions recognised through a neural network as input for an adaptive music system in virtual reality.Entertainment Computing38 (2021), 100404

    2021

  75. [81]

    2013.The game experience questionnaire

    Wijnand A IJsselsteijn, Yvonne AW De Kort, and Karolien Poels. 2013.The game experience questionnaire. Technische Universiteit Eindhoven. Manuscript submitted to ACM 30 Li et al

    2013

  76. [82]

    Remus Ilies, Megan Huth, Ann Marie Ryan, and Nikolaos Dimotakis. 2015. Explaining the links between workload, distress, and work–family conflict among school employees: Physical, cognitive, and emotional fatigue.Journal of educational psychology107, 4 (2015), 1136

    2015

  77. [83]

    Horace HS Ip, Simpson WL Wong, Dorothy FY Chan, Julia Byrne, Chen Li, Vanessa SN Yuan, Kate SY Lau, and Joe YW Wong. 2018. Enhance emotional and social adaptation skills for children with autism spectrum disorder: A virtual reality enabled approach.Computers & Education117 (20...

    2018

  78. [84]

    Karin Rizky Irminanda and Shuping Xiong. 2025. Ergonomic Risks in Immersive Virtual Reality Gaming for Entertainment: A Literature Synthesis. International Journal of Human–Computer Interaction(2025), 1–18

    2025

  79. [85]

    Rifatul Islam, Samuel Ang, and John Quarles. 2021. Cybersense: A closed-loop framework to detect cybersickness severity and adaptively apply reduction techniques. In2021 IEEE Conference on virtual reality and 3d user interfaces abstracts and workshops (VRW). IEEE, 148–155

    2021

  80. [86]

    Shan Jin, Yuyang Wang, Lik-Hang Lee, Xinyi Luo, and Pan Hui. 2023. Development of an immersive simulator for improving student chemistry learning efficiency. InProceedings of the 16th International Symposium on Visual Information Communication and Interaction. 1–8

    2023

  81. [87]

    Aaron Johnson, Ying Tang, and Christopher Franzwa. 2014. kNN-based adaptive virtual reality game system. Inproceedings of the 11th IEEE international conference on networking, sensing and control. IEEE, 457–462

    2014

  82. [88]

    Lauma Jokste and Janis Grabis. 2017. Rule based adaptation: literature review.ENVIRONMENT. TECHNOLOGIES. RESOURCES. Proceedings of the International Scientific and Practical Conference2 (2017), 42–46

    2017

  83. [89]

    Sarah Jones and Steve Dawkins. 2017. The sensorama revisited: evaluating the application of multi-sensory input on the sense of presence in 360-degree immersive film in virtual reality. InAugmented reality and virtual reality: Empowering human, place and business. Springer, 183–197

    2017

  84. [90]

    Julia M Juliano, Nicolas Schweighofer, and Sook-Lei Liew. 2022. Increased cognitive load in immersive virtual reality during visuomotor adaptation is associated with decreased long-term retention and context transfer.Journal of NeuroEngineering and Rehabilitation19, 1 (2022), 106

    2022

  85. [91]

    Han Wool Jung, Ki Won Jang, Sangkyu Nam, Mu Eob Ahn, Sang-Kyu Lee, Yeo Jin Kim, Jae-Kyoung Shin, Ju Hyun Park, and Daeyoung Roh. 2024. Personalized virtual reality exposure for panic disorder and agoraphobia: A preliminary neurophysiological study.Comprehensive Psychiatry129 (...

    2024

  86. [92]

    Dorota Kamińska, Grzegorz Zwoliński, and Anna Laska-Leśniewicz. 2022. Usability testing of virtual reality applications—the pilot study.Sensors 22, 4 (2022), 1342

    2022

  87. [93]

    S Karthick, M Dinesh, N Jayapandian, et al . 2023. Artificial Intelligence Based Enhanced Virtual Mouse Hand Gesture Tracking Using Yolo Algorithm. In2023 IEEE 2nd International Conference on Data, Decision and Systems (ICDDS). IEEE, 1–6

    2023

  88. [94]

    Robert S Kennedy, Norman E Lane, Kevin S Berbaum, and Michael G Lilienthal. 1993. Simulator sickness questionnaire: An enhanced method for quantifying simulator sickness.The international journal of aviation psychology3, 3 (1993), 203–220

    1993

  89. [95]

    Erika Kerruish. 2019. Arranging sensations: smell and taste in augmented and virtual reality.The Senses and Society14, 1 (2019), 31–45

    2019

  90. [96]

    Behrang Keshavarz and Heiko Hecht. 2011. Validating an efficient method to quantify motion sickness.Human factors53, 4 (2011), 415–426

    2011

  91. [97]

    Yong Min Kim, Ilsun Rhiu, and Myung Hwan Yun. 2020. A systematic review of a virtual reality system from the perspective of user experience. International Journal of Human–Computer Interaction36, 10 (2020), 893–910

    2020

  92. [98]

    Panagiotis Kourtesis, Simona Collina, Leonidas AA Doumas, and Sarah E MacPherson. 2019. Validation of the virtual reality neuroscience questionnaire: maximum duration of immersive virtual reality sessions without the presence of pertinent adverse symptomatology.Frontiers in hu...

    2019

  93. [99]

    Julian Kreimeier, Sebastian Hammer, Daniel Friedmann, Pascal Karg, Clemens Bühner, Lukas Bankel, and Timo Götzelmann. 2019. Evaluation of different types of haptic feedback influencing the task-based presence and performance in virtual reality. InProceedings of the 12th acm in...

    2019

  94. [100]

    Jacob Kritikos, Georgios Alevizopoulos, and Dimitris Koutsouris. 2021. Personalized virtual reality human-computer interaction for psychiatric and neurological illnesses: a dynamically adaptive virtual reality environment that changes according to real-time feedback from elect...

    2021

  95. [101]

    Logan Kugler. 2021. The state of virtual reality hardware.Commun. ACM64, 2 (2021), 15–16

    2021

  96. [102]

    Ripan Kumar Kundu, Rifatul Islam, John Quarles, and Khaza Anuarul Hoque. 2023. Litevr: Interpretable and lightweight cybersickness detection using explainable ai. In2023 IEEE Conference Virtual Reality and 3D User Interfaces (VR). IEEE, 609–619

    2023

  97. [103]

    Manuel Lagos Rodríguez, Ángel Gómez García, Javier Pereira Loureiro, and Thais Pousada García. 2022. Personalized virtual reality environments for intervention with people with disability.Electronics11, 10 (2022), 1586

    2022

  98. [105]

    Yu Lei, Yi Deng, Lin Dong, Xiaohui Li, Xiangnan Li, and Zhi Su. 2023. A novel sensor fusion approach for precise hand tracking in virtual reality-based human—Computer interaction.Biomimetics8, 3 (2023), 326

    2023

  99. [106]

    Feng Li and Jun Fei. 2019. Gesture recognition algorithm based on image information fusion in virtual reality.Personal and Ubiquitous Computing 23, 3 (2019), 487–497

    2019

  100. [107]

    Hsiao-Hui Li, Jian-Jie Lian, and Yuan-Hsun Liao. 2023. Design an adaptive virtual reality game to promote elderly health. In2023 International Conference on Computer, Information and Telecommunication Systems (CITS). IEEE, 1–7

    2023

  101. [108]

    Ruichen Li, Yuyang Wang, Handi Yin, Jean-Rémy Chardonnet, and Pan Hui. 2023. A deep cybersickness predictor through kinematic data with encoded physiological representation. In2023 IEEE International Symposium on Mixed and Augmented Reality (ISMAR). IEEE, 1132–1141. Manuscript...

    2023

  102. [109]

    Ziming Li, Pinaki Prasanna Babar, Mike Barry, and Roshan L Peiris. 2024. Exploring the use of large language model-driven chatbots in virtual reality to train autistic individuals in job communication skills. InExtended Abstracts of the CHI Conference on Human Factors in Compu...

    2024

  103. [110]

    Hailun Lian, Cheng Lu, Sunan Li, Yan Zhao, Chuangao Tang, and Yuan Zong. 2023. A survey of deep learning-based multimodal emotion recognition: Speech, text, and face.Entropy25, 10 (2023), 1440

    2023

  104. [111]

    Hui Liang, ShiQing Liu, Yi Wang, Junjun Pan, Jialin Fu, and Yingkai Yuan. 2023. Eeg-based vr scene adaptive generation system for regulating emotion. In2023 9th International Conference on Virtual Reality (ICVR). IEEE, 361–368

    2023

  105. [112]

    Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick. 2014. Microsoft coco: Common objects in context. InEuropean conference on computer vision. Springer, 740–755

    2014

  106. [113]

    Yi Lin, Shunbo Wang, and Yangfan Lan. 2022. The study of virtual reality adaptive learning method based on learning style model.Computer Applications in Engineering Education30, 2 (2022), 396–414

    2022

  107. [114]

    Marilia KS Lopes and Tiago H Falk. 2025. Generative AI for Personalized Multisensory Immersive Experiences: Challenges and Opportunities for Stress Reduction. In2025 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). IEEE, 143–146

    2025

  108. [115]

    Gadea Lucas-Pérez, José Miguel Ramírez-Sanz, Ana Serrano-Mamolar, Álvar Arnaiz-González, and Andrés Bustillo. 2024. Personalising the Training Process with Adaptive Virtual Reality: A Proposed Framework, Challenges, and Opportunities. InInternational Conference on Extended Rea...

    2024

  109. [116]

    Tiffany Luong, Yi Fei Cheng, Max Möbus, Andreas Fender, and Christian Holz. 2023. Controllers or bare hands? a controlled evaluation of input techniques on interaction performance and exertion in virtual reality.IEEE Transactions on Visualization and Computer Graphics29, 11 (2...

    2023

  110. [117]

    Sharon Macias-Velasquez, Hugo I Medellin-Castillo, and Abel Garcia-Barrientos. 2024. New-user experience evaluation in a semi-immersive and haptic-enabled virtual reality system for assembly operations.International Journal of Human-Computer Studies190 (2024), 103312

    2024

  111. [118]

    Luna Maddalon, Maria Eleonora Minissi, Thomas Parsons, Amaia Hervas, and Mariano Alcaniz. 2024. Exploring adaptive virtual reality systems used in interventions for children with autism spectrum disorder: systematic review.Journal of medical Internet research26 (2024), e57093

    2024

  112. [119]

    Athar Mahmoudi-Nejad. 2021. Automated personalized exposure therapy based on physiological measures using experience-driven procedural content generation.Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment17, 1 (2021), 232–235

    2021

  113. [120]

    Athar Mahmoudi-Nejad, Pierre Boulanger, and Matthew Guzdial. 2024. Stress Detection from Photoplethysmography in a Virtual Reality Environment.arXiv preprint arXiv:2409.17427(2024)

    2024 arXiv

  114. [121]

    Irina Makarova, Jamila Mustafina, Aleksey Boyko, Larisa Fatikhova, Gleb Parsin, Polina Buyvol, and Vladimir Shepelev. 2023. A virtual reality lab for automotive service specialists: A knowledge transfer system in the digital age.Information14, 3 (2023), 163

    2023

  115. [122]

    Henna Mäkinen, Elina Haavisto, Sara Havola, and Jaana-Maija Koivisto. 2022. User experiences of virtual reality technologies for healthcare in learning: an integrative review.Behaviour & Information Technology41, 1 (2022), 1–17

    2022

  116. [123]

    Marzena Malińska, Krystyna Zużewicz, Joanna Bugajska, and Andrzej Grabowski. 2015. Heart rate variability (HRV) during virtual reality immersion.International Journal of Occupational Safety and Ergonomics21, 1 (2015), 47–54

    2015

  117. [124]

    Javier Marín-Morales, Carmen Llinares, Jaime Guixeres, and Mariano Alcañiz. 2020. Emotion recognition in immersive virtual reality: From statistics to affective computing.Sensors20, 18 (2020), 5163

    2020

  118. [125]

    Isabela Marinho, Renatto Padilha, Gislayne Vitorino, Marcelo Batista, Yasmim Oliveira, João Vitor Almeida, Willams Costa, Cristiano Araújo, and Veronica Teichrieb. 2024. Eyes of Fear: Leveraging Emotion Recognition for Virtual Reality Experience. InProceedings of the 26th Symp...

    2024

  119. [126]

    Andreas Marougkas, Christos Troussas, Akrivi Krouska, and Cleo Sgouropoulou. 2024. How personalized and effective is immersive virtual reality in education? A systematic literature review for the last decade.Multimedia Tools and Applications83, 6 (2024), 18185–18233

    2024

  120. [127]

    Daniel Martin, Sandra Malpica, Diego Gutierrez, Belen Masia, and Ana Serrano. 2022. Multimodality in VR: A survey.ACM Computing Surveys (CSUR)54, 10s (2022), 1–36

    2022

  121. [128]

    Nuria Mateos-García, Ana-Belén Gil-González, Ana Luis-Reboredo, and Belén Pérez-Lancho. 2023. Driver stress detection from physiological signals by virtual reality simulator.Electronics12, 10 (2023), 2179

    2023

  122. [129]

    Miguel Melo, Guilherme Gonçalves, Pedro Monteiro, Hugo Coelho, José Vasconcelos-Raposo, and Maximino Bessa. 2020. Do multisensory stimuli benefit the virtual reality experience? A systematic review.IEEE transactions on visualization and computer graphics28, 2 (2020), 1428–1442

    2020

  123. [130]

    Yu Miao, Haiwei Dong, Jihad Mohamad Al Jaam, and Abdulmotaleb El Saddik. 2019. A deep learning system for recognizing facial expression in real-time.ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)15, 2 (2019), 1–20

    2019

  124. [131]

    Yewon Min and Jin-Woo Jeong. 2024. Public speaking q&a practice with llm-generated personas in virtual reality. In2024 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct). IEEE, 493–496

    2024

  125. [132]

    David Moher, Alessandro Liberati, Jennifer Tetzlaff, and Douglas G Altman. 2009. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.Bmj339 (2009)

    2009

  126. [133]

    Roberto A Montano Murillo, Elia Gatti, Miguel Oliver Segovia, Marianna Obrist, Jose P Molina Masso, and Diego Martinez Plasencia. 2017. NaviFields: Relevance fields for adaptive VR navigation. InProceedings of the 30th Annual ACM Symposium on User Interface Software and Techno...

    2017

  127. [134]

    Pedro Monteiro, Guilherme Gonçalves, Hugo Coelho, Miguel Melo, and Maximino Bessa. 2021. Hands-free interaction in immersive virtual reality: A systematic review.IEEE Transactions on Visualization and Computer Graphics27, 5 (2021), 2702–2713

    2021

  128. [135]

    Martez Mott, Edward Cutrell, Mar Gonzalez Franco, Christian Holz, Eyal Ofek, Richard Stoakley, and Meredith Ringel Morris. 2019. Accessible by design: An opportunity for virtual reality. In2019 IEEE international symposium on mixed and augmented reality adjunct (ISMAR-adjunct)...

    2019

  129. [136]

    Joschka Mütterlein. 2018. The three pillars of virtual reality? Investigating the roles of immersion, presence, and interactivity. (2018)

    2018

  130. [137]

    Adaptive Virtual Reality

    Taichi Nakagawa, Muneo Kitajima, and Katsuko T Nakahira. 2024. Model-Based Analysis of the Differences in Sensory Perception between Real and Virtual Space: Toward “Adaptive Virtual Reality”.AIVR 2024 : The First International Conference on Artificial Intelligence and Immersiv...

    2024

  131. [138]

    Eshed OhnBar, Kris Kitani, and Chieko Asakawa. 2018. Personalized dynamics models for adaptive assistive navigation systems. InConference on Robot Learning. PMLR, 16–39

    2018

  132. [139]

    Ananta Ojha, Shefalika Narain, Akshay Raj, Trapty Agrawal, Bhawna Wadhwa, and Manish Joshi. 2024. Dynamic virtual reality horror sports enhanced by artificial intelligence and player modeling.Multimedia Tools and Applications83, 32 (2024), 77415–77432

    2024

  133. [140]

    2023.Disability and Health

    World Health Organization. 2023.Disability and Health. Retrieved Augest 18, 2025 from https://www.who.int/news-room/fact-sheets/detail/ disability-and-health

    2023

  134. [141]

    Michael Otto, Eva Lampen, Philipp Agethen, Mareike Langohr, Gabriel Zachmann, and Enrico Rukzio. 2019. A virtual reality assembly assessment benchmark for measuring VR performance & limitations.Procedia CIRP81 (2019), 785–790

    2019

  135. [142]

    Susanna Pardini, Silvia Gabrielli, Marco Dianti, Caterina Novara, Gesualdo M Zucco, Ornella Mich, and Stefano Forti. 2022. The role of personalization in the user experience, preferences and engagement with virtual reality environments for relaxation.International Journal of E...

    2022

  136. [144]

    Timo Partala, Maria Jokiniemi, and Veikko Surakka. 2000. Pupillary responses to emotionally provocative stimuli. InProceedings of the 2000 symposium on Eye tracking research & applications. Association for Computing Machinery, New York, NY, USA, 123–129

    2000

  137. [145]

    Patrick David Pazour, Andreas Janecek, and Helmut Hlavacs. 2018. Virtual reality conferencing. In2018 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR). IEEE, 84–91

    2018

  138. [146]

    Tabitha C Peck and Mar Gonzalez-Franco. 2021. Avatar embodiment. a standardized questionnaire.Frontiers in Virtual Reality1 (2021), 575943

    2021

  139. [147]

    Shiva Pedram, Grace Kennedy, and Sal Sanzone. 2023. Toward the validation of VR-HMDs for medical education: a systematic literature review. Virtual Reality27, 3 (2023), 2255–2280

    2023

  140. [148]

    Alex Peer and Kevin Ponto. 2019. Mitigating incorrect perception of distance in virtual reality through personalized rendering manipulation. In 2019 IEEE conference on virtual reality and 3D user interfaces (VR). IEEE, 244–250

    2019

  141. [149]

    Siyou Pei, Alexander Chen, Chen Chen, Franklin Mingzhe Li, Megan Fozzard, Hao-Yun Chi, Nadir Weibel, Patrick Carrington, and Yang Zhang

  142. [150]

    Nikolaos Pellas, Andreas Dengel, and Athanasios Christopoulos. 2020. A scoping review of immersive virtual reality in STEM education.IEEE Transactions on Learning Technologies13, 4 (2020), 748–761

    2020

  143. [151]

    Silvia Francesca Maria Pizzoli, Ketti Mazzocco, Stefano Triberti, Dario Monzani, Mariano Luis Alcañiz Raya, and Gabriella Pravettoni. 2019. User-centered virtual reality for promoting relaxation: an innovative approach.Frontiers in psychology10 (2019), 479

    2019

  144. [152]

    Karolien Poels, Yvonne AW de Kort, and Wijnand A IJsselsteijn. 2007.D3. 3: Game Experience Questionnaire: development of a self-report measure to assess the psychological impact of digital games. Technische Universiteit Eindhoven

    2007

  145. [153]

    Thibault Porssut, Yawen Hou, Olaf Blanke, Bruno Herbelin, and Ronan Boulic. 2021. Adapting virtual embodiment through reinforcement learning. IEEE Transactions on Visualization and Computer Graphics28, 9 (2021), 3193–3205

    2021

  146. [154]

    S Purushothaman, A Himabindu, P Bhuvaneswari, P Chellammal, Satvik Vats, and P Merlin Sheela. 2025. Immersive Virtual Reality Infused Artificial Intelligence Interfaces for Hyper Personalized Digital Engagement and Enhanced User Experience. InInternational Conference on Sustai...

    2025

  147. [155]

    Zihui Qin, Yilin Cao, Jeongyeong Park, Qianru Liu, Zhuohui Xu, Nanlin Jin, and Hai-Ning Liang. 2024. Data-Driven Recommendation in Brain-Metaverse Interaction. In2024 10th International Conference on Smart Computing and Communication (ICSCC). IEEE, 343–348

    2024

  148. [156]

    Nimesha Ranasinghe, Pravar Jain, Nguyen Thi Ngoc Tram, Koon Chuan Raymond Koh, David Tolley, Shienny Karwita, Lin Lien-Ya, Yan Liangkun, Kala Shamaiah, Chow Eason Wai Tung, et al . 2018. Season traveller: Multisensory narration for enhancing the virtual reality experience. In ...

    2018

  149. [157]

    Ali Raza, Amjad Rehman, Rukhshanda Sehar, Faten S Alamri, Sarah Alotaibi, Bayan Al Ghofaily, and Tanzila Saba. 2024. Optimized virtual reality design through user immersion level detection with novel feature fusion and explainable artificial intelligence.PeerJ Computer Science...

    2024

  150. [158]

    1975.Motion sickness.Academic press

    James T Reason and Joseph John Brand. 1975.Motion sickness.Academic press

    1975

  151. [159]

    Ana Rita Rebelo, Pedro A Ferreira, and Rui Nóbrega. 2024. Adaptive Virtual Environments in Small Physical Spaces: Navigation Design for Customized User Experiences in Virtual Reality. InExtended Abstracts of the CHI Conference on Human Factors in Computing Systems. 1–7. Manusc...

    2024

  152. [160]

    Holger Regenbrecht and Thomas Schubert. 2002. Real and illusory interactions enhance presence in virtual environments.Presence: Teleoperators & Virtual Environments11, 4 (2002), 425–434

    2002

  153. [161]

    Lorcan Reidy, Dennis Chan, Charles Nduka, and Hatice Gunes. 2020. Facial electromyography-based adaptive virtual reality gaming for cognitive training. InProceedings of the 2020 International Conference on Multimodal Interaction. 174–183

    2020

  154. [162]

    Xiaojun Ren, Jiluan Fan, Ning Xu, Shaowei Wang, Changyu Dong, and Zikai Wen. 2024. DPGazeSynth: enhancing eye-tracking virtual reality privacy with differentially private data synthesis.Information Sciences675 (2024), 120720

    2024

  155. [163]

    Sathiya Kumar Renganayagalu, Steven C Mallam, and Salman Nazir. 2021. Effectiveness of VR head mounted displays in professional training: A systematic review.Technology, Knowledge and Learning(2021), 1–43

    2021

  156. [164]

    Grand View Research. [n. d.].GVR Report cover Virtual Reality In Gaming Market Size, Share & Trends Analysis Report By Component (Hardware, Software), By Connecting Device (Gaming Console, PC/Desktop, Smartphone), By User (Commercial Spaces, Individual), By Region, And Segment...

    2025

  157. [165]

    Spinassé, Gabriel Giesen Ludke, Mateus Ruy Soares Gaudio, Guilherme Iglesias Rocha Gomes, Luan Guio Cotini, Daniel da Silva Vargens, Marcelo Queiroz Schimidt, et al

    Tainã Ribeiro de Oliveira, Brenda Biancardi Rodrigues, Matheus Moura da Silva, Rafael Antonio N. Spinassé, Gabriel Giesen Ludke, Mateus Ruy Soares Gaudio, Guilherme Iglesias Rocha Gomes, Luan Guio Cotini, Daniel da Silva Vargens, Marcelo Queiroz Schimidt, et al. 2023. Virtual ...

    2023

  158. [166]

    Fabio Richlan, Moritz Weiß, Patrick Kastner, and Jeremias Braid. 2023. Virtual training, real effects: A narrative review on sports performance enhancement through interventions in virtual reality.Frontiers in Psychology14 (2023), 1240790

    2023

  159. [167]

    Monserrat Ríos-Hernández, Juan Manuel Jacinto-Villegas, Otniel Portillo-Rodríguez, and Adriana Herlinda Vilchis-González. 2021. User-centered design and evaluation of an upper limb rehabilitation system with a virtual environment.Applied Sciences11, 20 (2021), 9500

    2021

  160. [168]

    Albert ‘Skip’ Rizzo and Russell Shilling. 2017. Clinical virtual reality tools to advance the prevention, assessment, and treatment of PTSD.European journal of psychotraumatology8, sup5 (2017), 1414560

    2017

  161. [169]

    Irvin Rock and Jack Victor. 1964. Vision and touch: An experimentally created conflict between the two senses.Science143, 3606 (1964), 594–596

    1964

  162. [170]

    Daniel Roth, Jean-Luc Lugrin, Marc Erich Latoschik, and Stephan Huber. 2017. Alpha IVBO-construction of a scale to measure the illusion of virtual body ownership. InProceedings of the 2017 CHI conference extended abstracts on human factors in computing systems. Association for...

    2017

  163. [171]

    Javad Sameri, Hendrick Coenegracht, Sam Van Damme, Filip De Turck, and Maria Torres Vega. 2024. Physiology-driven cybersickness detection in virtual reality: a machine learning and explainable AI approach.Virtual Reality28, 4 (2024), 174

    2024

  164. [172]

    Thomas Schubert, Frank Friedmann, and Holger Regenbrecht. 2001. The experience of presence: Factor analytic insights.Presence: Teleoperators & Virtual Environments10, 3 (2001), 266–281

    2001

  165. [173]

    Martijn J Schuemie, Peter Van Der Straaten, Merel Krijn, and Charles APG Van Der Mast. 2001. Research on presence in virtual reality: A survey. Cyberpsychology & behavior4, 2 (2001), 183–201

    2001

  166. [174]

    Ezequiel Scott, Alvaro Soria, and Marcelo Campo. 2016. Adaptive 3D virtual learning environments—A review of the literature.IEEE Transactions on Learning technologies10, 3 (2016), 262–276

    2016

  167. [175]

    John Patrick Sexton, Anderson Augusto Simiscuka, Kevin Mcguinness, and Gabriel-Miro Muntean. 2021. Automatic CNN-based enhancement of 360°video experience with multisensorial effects.IEEE Access9 (2021), 133156–133169

    2021

  168. [176]

    Mahima Sharma, Sudhanshu Kacker, and Mohit Sharma. 2016. A brief introduction and review on galvanic skin response.Int. J. Med. Res. Prof2, 6 (2016), 13–17

    2016

  169. [177]

    MJ Singer and BG Witmer. 1996. Presence measures for virtual environments: Background & development.Draft United States Army Research Institute for the Behavioral and Social Sciences22 (1996), 675

    1996

  170. [178]

    Alexandra Sipatchin, Siegfried Wahl, and Katharina Rifai. 2021. Eye-tracking for clinical ophthalmology with virtual reality (vr): A case study of the htc vive pro eye’s usability.Healthcare9, 2 (2021), 180

    2021

  171. [179]

    Filip Škola, Dusanka Boskovic, Selma Rizvic, Dimitrios Skarlatos, and Fotis Liarokapis. 2024. Assessing user experience and cognitive workload in virtual reality digital storytelling.International Journal of Human–Computer Interaction40, 6 (2024), 1479–1486

    2024

  172. [180]

    Mel Slater. 2018. Immersion and the illusion of presence in virtual reality.British journal of psychology109, 3 (2018), 431–433

    2018

  173. [181]

    Mel Slater, Martin Usoh, and Anthony Steed. 1994. Depth of presence in virtual environments.Presence: Teleoperators & Virtual Environments3, 2 (1994), 130–144

    1994

  174. [182]

    LearningverseVR

    Yanjie Song, Kaiyi Wu, and Jiaoyang Ding. 2024. Developing an immersive game-based learning platform with generative artificial intelligence and virtual reality technologies–“LearningverseVR”.Computers & Education: X Reality4 (2024), 100069

    2024

  175. [183]

    Charles D Spielberger, Fernando Gonzalez-Reigosa, Angel Martinez-Urrutia, Luiz FS Natalicio, and Diana S Natalicio. 1971. The state-trait anxiety inventory.Revista Interamericana de Psicologia/Interamerican journal of psychology5, 3 & 4 (1971)

    1971

  176. [184]

    Qi Sun, Anjul Patney, Li-Yi Wei, Omer Shapira, Jingwan Lu, Paul Asente, Suwen Zhu, Morgan McGuire, David Luebke, and Arie Kaufman. 2018. Towards virtual reality infinite walking: dynamic saccadic redirection.ACM Transactions on Graphics (TOG)37, 4 (2018), 1–13

    2018

  177. [185]

    Ivan E Sutherland et al. 1965. The ultimate display. InProceedings of the IFIP Congress, Vol. 2. New York, 506–508

    1965

  178. [186]

    Luma Tabbaa, Ryan Searle, Saber Mirzaee Bafti, Md Moinul Hossain, Jittrapol Intarasisrisawat, Maxine Glancy, and Chee Siang Ang. 2021. Vreed: Virtual reality emotion recognition dataset using eye tracking & physiological measures.Proceedings of the ACM on interactive, mobile, ...

    2021

  179. [187]

    Kiyu Tanaka, Takuto Nakamura, Keigo Matsumoto, Hideaki Kuzuoka, and Takuji Narumi. 2025. Detection Thresholds for Replay and Real-Time Discrepancies in VR Hand Redirection.IEEE Transactions on Visualization and Computer Graphics(2025)

    2025

  180. [188]

    Da Tao, Haibo Tan, Hailiang Wang, Xu Zhang, Xingda Qu, and Tingru Zhang. 2019. A systematic review of physiological measures of mental workload.International journal of environmental research and public health16, 15 (2019), 2716

    2019

  181. [189]

    Yujie Tao, Cheng Yao Wang, Andrew D Wilson, Eyal Ofek, and Mar Gonzalez-Franco. 2023. Embodying physics-aware avatars in virtual reality. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, USA, 1–15

    2023

  182. [190]

    Jeff Tarrant, Jeremy Viczko, and Hannah Cope. 2018. Virtual reality for anxiety reduction demonstrated by quantitative EEG: a pilot study.Frontiers in psychology9 (2018), 368656

    2018

  183. [191]

    Umama Tasnim, Rifatul Islam, Kevin Desai, and John Quarles. 2024. Investigating personalization techniques for improved cybersickness prediction in virtual reality environments.IEEE Transactions on Visualization and Computer Graphics30, 5 (2024), 2368–2378

    2024

  184. [192]

    Katy Tcha-Tokey, Olivier Christmann, Emilie Loup-Escande, and Simon Richir. 2016. Proposition and validation of a questionnaire to measure the user experience in immersive virtual environments.International Journal of Virtual Reality16, 1 (2016), 33–48

    2016

  185. [193]

    Jordan Tewell and Nimesha Ranasinghe. 2024. A review of olfactory display designs for virtual reality environments.Comput. Surveys56, 11 (2024), 1–35

    2024

  186. [194]

    Jason Tham, Ann Hill Duin, Laura Gee, Nathan Ernst, Bilal Abdelqader, and Megan McGrath. 2018. Understanding virtual reality: Presence, embodiment, and professional practice.IEEE Transactions on Professional Communication61, 2 (2018), 178–195

    2018

  187. [195]

    Nana Tian, Phil Lopes, and Ronan Boulic. 2022. A review of cybersickness in head-mounted displays: raising attention to individual susceptibility. Virtual Reality26, 4 (2022), 1409–1441

    2022

  188. [196]

    Sarah Tudor, Stephanie Carey, and Rajiv Dubey. 2015. Development and evaluation of a dynamic virtual reality driving simulator. InProceedings of the 8th ACM International Conference on PErvasive Technologies Related to Assistive Environments. 1–5

    2015

  189. [197]

    Ufuk Uyan and Ufuk Celikcan. 2024. CDMS: A real-time system for EEG-guided cybersickness mitigation through adaptive adjustment of VR content factors.Displays83 (2024), 102704

    2024

  190. [198]

    Samaikya Valluripally, Aniket Gulhane, Reshmi Mitra, Khaza Anuarul Hoque, and Prasad Calyam. 2020. Attack trees for security and privacy in social virtual reality learning environments. In2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC). IEEE, 1–9

    2020

  191. [199]

    Sergio Valmorisco, Laura Raya, and Alberto Sanchez. 2024. Enabling personalized VR experiences: a framework for real-time adaptation and recommendations in VR environments.Virtual Reality28, 3 (2024), 128

    2024

  192. [200]

    Thomas Waltemate, Dominik Gall, Daniel Roth, Mario Botsch, and Marc Erich Latoschik. 2018. The impact of avatar personalization and immersion on virtual body ownership, presence, and emotional response.IEEE transactions on visualization and computer graphics24, 4 (2018), 1643–1652

    2018

  193. [201]

    Hongyu Wan, Jinda Zhang, Abdulaziz Arif Suria, Bingsheng Yao, Dakuo Wang, Yvonne Coady, and Mirjana Prpa. 2024. Building llm-based ai agents in social virtual reality. InExtended Abstracts of the CHI Conference on Human Factors in Computing Systems. 1–7

    2024

  194. [202]

    Chiu-Hsuan Wang, Bing-Yu Chen, and Liwei Chan. 2022. Realitylens: A user interface for blending customized physical world view into virtual reality. InProceedings of the 35th Annual ACM Symposium on User Interface Software and Technology. 1–11

    2022

  195. [203]

    Yuyang Wang, Jean-Rémy Chardonnet, Lik-Hang Lee, and Pan Hui. 2023. IEEE VR 2023 Workshop: Datasets for developing intelligent XR applications (DATA4XR). In2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). IEEE, 67–68

    2023

  196. [204]

    Yuyang Wang, Jean-Rémy Chardonnet, and Frédéric Merienne. 2019. VR sickness prediction for navigation in immersive virtual environments using a deep long short term memory model. In2019 IEEE conference on virtual reality and 3D user interfaces (VR). IEEE, 1874–1881

    2019

  197. [205]

    Yuyang Wang, Jean-Rémy Chardonnet, and Frédéric Merienne. 2021. Enhanced cognitive workload evaluation in 3D immersive environments with TOPSIS model.International Journal of Human-Computer Studies147 (2021), 102572

    2021

  198. [206]

    Yuyang Wang, Jean-Rémy Chardonnet, and Frédéric Merienne. 2023. Modeling online adaptive navigation in virtual environments based on PID control. InInternational Conference on Neural Information Processing. Springer, 325–346

    2023

  199. [207]

    Yuyang Wang, Jean-Rémy Chardonnet, Frédéric Merienne, and Jivka Ovtcharova. 2021. Using fuzzy logic to involve individual differences for predicting cybersickness during vr navigation. In2021 IEEE Virtual Reality and 3D User Interfaces (VR). IEEE, 373–381

    2021

  200. [208]

    Yuyang Wang, Lik-Hang Lee, Tristan Braud, and Pan Hui. 2022. Re-shaping Post-COVID-19 teaching and learning: A blueprint of virtual-physical blended classrooms in the metaverse era. In2022 IEEE 42nd international conference on distributed computing systems workshops (ICDCSW). ...

    2022

  201. [209]

    David Watson, Lee Anna Clark, and Auke Tellegen. 1988. Development and validation of brief measures of positive and negative affect: the PANAS scales.Journal of personality and social psychology54, 6 (1988), 1063

    1988

  202. [210]

    Theresa F Wechsler, Franziska Kümpers, and Andreas Mühlberger. 2019. Inferiority or even superiority of virtual reality exposure therapy in phobias?—A systematic review and quantitative meta-analysis on randomized controlled trials specifically comparing the efficacy of virtua...

    2019

  203. [211]

    Shu Wei, Desmond Bloemers, and Aitor Rovira. 2023. A preliminary study of the eye tracker in the meta quest pro. InProceedings of the 2023 ACM international conference on interactive media experiences. Association for Computing Machinery, New York, NY, USA, 216–221

    2023

  204. [212]

    Preston Tunnell Wilson, William Kalescky, Ansel MacLaughlin, and Betsy Williams. 2016. VR locomotion: walking> walking in place> arm swinging. InProceedings of the 15th ACM SIGGRAPH conference on virtual-reality continuum and its applications in industry-volume 1. 243–249

    2016

  205. [213]

    Bob G Witmer and Michael J Singer. 1998. Measuring presence in virtual environments: A presence questionnaire.Presence7, 3 (1998), 225–240. Manuscript submitted to ACM Adapting to the User: A Systematic Review of Personalized Interaction in VR 35

    1998

  206. [214]

    Kody Wood, Alvaro Joffre Uribe Quevedo, Lina Penuela, Sharman Perera, and Bill Kapralos. 2021. Virtual reality assessment and customization using physiological measures: A literature analysis. InProceedings of the 23rd Symposium on Virtual and Augmented Reality. 64–73

    2021

  207. [215]

    Jiang Wu, Xuezheng Liu, Miao Hu, Hongxu Lin, Min Chen, Yipeng Zhou, and Di Wu. 2024. GazeFed: Privacy-Aware Personalized Gaze Prediction for Virtual Reality. In2024 IEEE/ACM 32nd International Symposium on Quality of Service (IWQoS). IEEE, 1–6

    2024

  208. [216]

    Jian Wu, Ziteng Wang, Lili Wang, Yuhan Duan, and Jiaheng Li. 2024. FanPad: a fan layout touchpad keyboard for text entry in VR. In2024 IEEE Conference Virtual Reality and 3D User Interfaces (VR). IEEE, 222–232

    2024

  209. [217]

    Yi Wu, Cong Shi, Tianfang Zhang, Payton Walker, Jian Liu, Nitesh Saxena, and Yingying Chen. 2023. Privacy leakage via unrestricted motion- position sensors in the age of virtual reality: A study of snooping typed input on virtual keyboards. In2023 IEEE Symposium on Security an...

    2023

  210. [218]

    Biao Xie, Huimin Liu, Rawan Alghofaili, Yongqi Zhang, Yeling Jiang, Flavio Destri Lobo, Changyang Li, Wanwan Li, Haikun Huang, Mesut Akdere, et al. 2021. A review on virtual reality skill training applications.Frontiers in Virtual Reality2 (2021), 645153

    2021

  211. [219]

    Peixuan Xiong, Yukai Zhang, Nandi Zhang, Shihan Fu, Xin Li, Yadan Zheng, Jinni Zhou, Xiquan Hu, and Mingming Fan. 2024. To Reach the Unreachable: Exploring the Potential of VR Hand Redirection for Upper Limb Rehabilitation. InProceedings of the 2024 CHI Conference on Human Fac...

    2024

  212. [220]

    Ji Won Yoo, Dong Ryul Lee, Yon Ju Sim, Joshua H You, and Cheol J Kim. 2014. Effects of innovative virtual reality game and EMG biofeedback on neuromotor control in cerebral palsy.Bio-medical materials and engineering24, 6 (2014), 3613–3618

    2014

  213. [221]

    Zhendong Yu and Jianan Dang. 2025. The effects of the generative adversarial network and personalized virtual reality platform in improving frailty among the elderly.Scientific Reports15, 1 (2025), 8220

    2025

  214. [222]

    Maryam Zahabi and Ashiq Mohammed Abdul Razak. 2020. Adaptive virtual reality-based training: a systematic literature review and framework. Virtual Reality24, 4 (2020), 725–752

    2020

  215. [223]

    Hui Zeng and Rong Zhao. 2023. Perceptually-guided Dual-mode Virtual Reality System For Motion-adaptive Display.IEEE Transactions on Visualization and Computer Graphics29, 5 (2023), 2249–2257

    2023

  216. [224]

    André Zenner, Chiara Karr, Martin Feick, Oscar Ariza, and Antonio Krüger. 2024. Beyond the blink: Investigating combined saccadic & blink- suppressed hand redirection in virtual reality. InProceedings of the 2024 CHI Conference on Human Factors in Computing Systems. 1–14

    2024

  217. [225]

    Kevin Zhai, Azwa Dilawar, Mohammad S Yousef, Sean Holroyd, Haithem El-Hammali, and Marwa Abdelmonem. 2021. Virtual reality therapy for depression and mood in long-term care facilities.Geriatrics6, 2 (2021), 58

    2021

  218. [226]

    Song Zhao and Shiwei Cheng. 2023. Adaptive navigation assistance based on eye movement features in virtual reality.Virtual Reality & Intelligent Hardware5, 3 (2023), 232–248

    2023

  219. [227]

    Yuhang Zhao, Edward Cutrell, Christian Holz, Meredith Ringel Morris, Eyal Ofek, and Andrew D Wilson. 2019. SeeingVR: A set of tools to make virtual reality more accessible to people with low vision. InProceedings of the 2019 CHI conference on human factors in computing systems. 1–14

    2019

  220. [228]

    Jiahao Zheng, Sen Zhang, Xiaoping Wang, and Zhigang Zeng. 2022. Multimodal representations learning based on mutual information maximization and minimization and identity embedding for multimodal sentiment analysis.arXiv preprint arXiv:2201.03969(2022)

    2022 arXiv

  221. [229]

    Yitong Zhu, Tangyao Li, and Yuyang Wang. 2025. Real-time Cross-modal Cybersickness Prediction in Virtual Reality.arXiv preprint arXiv:2501.01212 (2025)

    2025 arXiv

  222. [230]

    Fatin Shamimi Mohd Zuki, Frédéric Merienne, Suziah Sulaiman, Aylen Ricca, Dayang Rohaya Awang Rambli, and Mohamad Naufal Mohamad Saad. 2022. Gamification, sensory feedback, adaptive function on virtual reality rehabilitation: a brief review. In2022 international conference on ...

    2022

  223. [231]

    Fatin Shamimi Mohd Zuki, Suziah Sulaiman, Frederic Merienne, Aylen Ricca, Christophe Guillet, and Mohamad Naufal Mohamad Saad. 2024. Assessing the impact of enriched virtual reality on motivation and engagement in stroke rehabilitation.IEEE ACCESS12 (2024), 143585–143598. Manu...

    2024

  224. [2023]

    InProceedings of the 25th International ACM SIGACCESS Conference on Computers and Accessibility

    Embodied exploration: Facilitating remote accessibility assessment for wheelchair users with virtual reality. InProceedings of the 25th International ACM SIGACCESS Conference on Computers and Accessibility. Association for Computing Machinery, New York, NY, USA, 1–17

  225. [2024]

    InProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology

    Predicting the Limits: Tailoring Unnoticeable Hand Redirection Offsets in Virtual Reality to Individuals’ Perceptual Boundaries. InProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology. Association for Computing Machinery, New York, NY, USA, 1–13

Pith tools

Reviewed August 4, 2026 · model on record in the stance chip above.