Emotion Recognition Technologies in Virtual Reality Film Experiences: A Review

Authors

  • Pengcheng Du Faculty of Creative Industries, City University Malaysia, Petaling Jaya 46100, Selangor, Malaysia Author
  • Rina Binti Abd Shukor University Selangor, Selangor, Malaysia Author
  • Zhijing Chen Creative Computing Institute, University of the Arts London, London WC1V 7EY, UK Author

DOI:

https://doi.org/10.65150/EP-jsshrs/V2E5/2026-10

Keywords:

Virtual Reality Film, Emotion Recognition, Physiological Signal Analysis, Affective Computing, Immersive Storytelling

Abstract

Virtual reality (VR) film has emerged as a representative form of immersive media, providing audiences with highly engaging and emotionally rich viewing experiences. Compared with traditional screen-based films, VR films place viewers within a three-dimensional narrative environment and offer a stronger sense of presence, embodiment, and interactivity. As emotional responses play a critical role in audience engagement, narrative comprehension, and overall user experience, emotion recognition has become an increasingly important research direction in VR film studies.

This paper reviews recent advances in emotion recognition technologies applied to virtual reality film experiences. It summarizes commonly used physiological and behavioral signals, including electroencephalography (EEG), electrodermal activity (EDA), heart rate variability (HRV), eye tracking, and facial expression analysis. In addition, representative machine learning and deep learning methods, such as support vector machines, convolutional neural networks, long short-term memory networks, and Transformer-based models, are discussed. The paper further examines key application scenarios, including audience experience evaluation, adaptive storytelling, therapeutic VR, and educational environments. However, existing studies still face challenges regarding multimodal data synchronization, individual variability, and the lack of standardized evaluation frameworks for VR film experiences.

The review indicates that multimodal physiological signal analysis provides an effective and objective approach for understanding emotional responses in immersive narrative experiences. Despite challenges related to individual differences, data synchronization, motion artifacts, and privacy concerns, continuous advances in sensor technology and artificial intelligence are expanding the potential of emotion-aware VR filmmaking. This study provides a theoretical reference for future research and practical guidance for creators seeking to develop more responsive and emotionally engaging virtual reality films.

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Published

2026-05-18

How to Cite

Du , P., Shukor , R. B. A., & Chen , Z. (2026). Emotion Recognition Technologies in Virtual Reality Film Experiences: A Review. Journal of Social Science and Human Research Studies, 2(05), 574-578. https://doi.org/10.65150/EP-jsshrs/V2E5/2026-10

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