A Physiological Approach to Assess Arousal in Virtual Reality and Computer-based Remote Collaboration

Bayro, Allison; Ghasemi, Yalda; Jeong, Heejin

doi:10.1177/1071181322661174

Cited by 3 publications

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“…Virtual reality (VR) has become a crucial tool in affective computing, providing human-like virtual worlds to enhance user experiences (Cambria, Das, Bandyopadhyay, & Feraco, 2017). Physiological signals like heart rate, skin conductance, and EEG are analyzed in VR to interpret users' emotional responses, enabling VR environments to adapt to the user's emotional state (Bayro, Ghasemi, & Jeong, 2022;Darzi & Novak, 2017). VR games, such as Pong, serve as controlled environments to study human emotions and behaviors, with the data used to create systems that can identify and respond to emotional cues (Ahmed, Harjunen, Jacucci, Ravaja, & Spapé, 2017).…”

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confidence: 99%

Emotion Recognition in Virtual Reality: Investigating the Effect of Gameplay Variations on Affective Responses

Bayro,

Buneo,

Jeong

2023

Proceedings of the Human Factors and Ergonomics Society Annual

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Virtual reality (VR) technology offers a unique platform for affective computing research, which aims to create intelligent systems capable of recognizing, interpreting, and responding to human emotions in immersive and interactive virtual environments. This study examined how different variations of VR games can elicit different emotional responses in players. Thirty participants played three VR Pong games, and their emotional responses were measured using the Self-Assessment Manikin and physiological measures. Results showed that different gameplay variations evoked varying emotional responses in players, and two features, average heart rate and the non-specific skin conductance responses (in peaks per min), were found to differ significantly between the games. The study suggests that VR gameplay can provide an engaging and interactive platform to study human emotions and behavior, with implications for designing and developing affective computing systems in fields such as healthcare, marketing, and humancomputer interaction.

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confidence: 99%