# 2.7. Adaptive Gaming and VR Experience

Recently, integrating EEG and ECG in adaptive gaming and virtual reality (VR) experiences has also opened new doors for crafting personalized, immersive environments that react to users' physiological states in real time.

One focus in this research is building adaptive, emotion-responsive environments. For instance, Gupta et al. introduced *WizardOfVR*, a VR game that adjusts in real time to the user’s emotional state through EEG, EDA (electrodermal activity), and HRV (heart rate variability) sensors. This setup crafts an experience where users' emotional cues shape the game’s visuals and narrative, fostering deeper emotional engagement \[45][^1]. In another study, Gupta and colleagues examined the relationship between biosignals and trust, analyzing how EEG, HRV, and GSR (galvanic skin response) can measure trust levels in virtual agents, finding that EEG alpha band power could reflect trust levels under low cognitive load. This shows potential for designing interactions that adjust to user comfort and trust \[52][^2]. Schöne et al. further explored VR’s immersive potential, comparing physiological responses in virtual and real-life scenarios. They found that markers for anxiety and vigilance in EEG and HRV were nearly indistinguishable between real and VR experiences, emphasizing VR's effectiveness in mimicking real conditions \[46][^3]. Similarly, Aspiotis et al. used a VR high-altitude scenario to examine stress indicators through EEG and ECG data, confirming VR’s efficacy in simulating high-stress conditions for research and therapeutic purposes \[47][^4].

Another important theme is using EEG and ECG to enhance user-centered VR designs, especially in mental health and educational settings. Barakat et al. demonstrated this by employing EEG and HRV in a VR-based design review, allowing architecture students to navigate building designs in VR and assess their affective responses. The study concluded that EEG and HRV markers could provide insights into users’ stress and engagement levels, improving feedback in user-centered design \[48][^5]. In educational applications, Fuentes-García et al. examined differences in EEG and HRV responses between real and virtual chess games, showing that users unfamiliar with VR displayed lower focus in virtual environments. This finding suggests familiarizing users with VR for optimal performance \[49][^6].

Adaptive VR applications are also advancing in therapeutic and stress-relief domains. Jo et al. explored VR forest videos to reduce stress among university students, finding that VR significantly impacted EEG and HRV markers associated with relaxation and focus, indicating VR's potential as a tool for stress management \[50][^7]. Rahman et al. went further by developing a self-guided VR exposure therapy (VRET) system for social anxiety, integrating EEG and HRV data to detect arousal states. This system provides feedback-driven interventions in VR, allowing users to confront anxiety-inducing situations in a safe, adaptable environment—a valuable approach for overcoming social anxiety \[51][^8].

[^1]: \[45] K. Gupta, Y. Zhang, Y. S. Pai, and M. Billinghurst, "WizardOfVR: An Emotion-Adaptive Virtual Wizard Experience," in *SIGGRAPH Asia 2021 XR (SA '21 XR)*, Association for Computing Machinery, New York, NY, USA, 2021.

[^2]: \[52] K. Gupta, R. Hajika, Y. S. Pai, A. Duenser, M. Lochner, and M. Billinghurst, "In AI We Trust: Investigating the Relationship between Biosignals, Trust and Cognitive Load in VR," in S. N. Spencer, Ed., *Assoc Computing Machinery*, New York, 2019.

[^3]: \[46] B. Schöne, J. Kisker, L. Lange, T. Gruber, S. Sylvester, and R. Osinsky, "The reality of virtual reality," *Frontiers in Psychology*, vol. 14, pp. 1093014–1093014, 2023.

[^4]: \[47] V. Aspiotis et al., "Assessing Electroencephalography as a Stress Indicator: A VR High-Altitude Scenario Monitored through EEG and ECG," *Sensors (Basel, Switzerland)*, vol. 22, no. 15, p. 5792, 2022.

[^5]: \[48] A. Barakat, H. Ayad, and Z. El-Sayad, "An Integrated Approach To User-Centered Design: Mobile Brain/Heart Imaging In Virtual Reality," *WIT Transactions on The Built Environment*, vol. 210, p. 201, 2022.

[^6]: \[49] J. P. Fuentes-García, T. Pereira, M. A. Castro, A. Carvalho Santos, and S. Villafaina, "Heart and Brain Responses to Real Versus Simulated Chess Games in Trained Chess Players: A Quantitative EEG and HRV Study," *International Journal of Environmental Research and Public Health*, vol. 16, no. 24, p. 5021, 2019.

[^7]: \[50] S.-H. Jo, J.-S. Park, and P.-S. Yeon, "The Effect of Forest Video Using Virtual Reality on the Stress Reduction of University Students Focused on C University in Korea," *International Journal of Environmental Research and Public Health*, vol. 18, no. 23, p. 12805, 2021.

[^8]: \[51] M. A. Rahman, D.J. Brown, M. Mahmud et al., "Enhancing biofeedback-driven self-guided virtual reality exposure therapy through arousal detection from multimodal data using machine learning," *Brain Informatics*, vol. 10, no. 1, pp. 14–14, 2023.
