A New Terrain in HCI: Emotion Recognition Interface using Biometric Data for an Immersive VR Experience
This work addresses the need for personalized and immersive experiences in VR for users, though it appears incremental as it builds on existing emotion recognition and biometric technologies.
The paper tackled the problem of enhancing user immersion in virtual reality by developing an emotion recognition interface using biometric data and machine learning, achieving high accuracy and usability in experiments.
Emotion recognition technology is crucial in providing a personalized user experience. It is especially important in virtual reality(VR) to assess the user's emotions to enhance their sense of immersion. We propose an emotion recognition interface that incorporates the user's biometric data with machine learning technology for increasing user engagement in VR. Our key technologies include brainwave sensors and eye-tracking cameras embedded in a VR headset, which seamlessly acquire physiological signals, and secondly, an attractiveness recognition algorithm that uses bio-signals to predict the user's attraction on visual stimuli. We conducted experiments to test the performance of the system, and also interviewed experts and participants to acquire opinions on the system. This study demonstrated the technical feasibility of our system with high accuracy and usability. Interviewees expected that the interface will be actively used in the context of various applications. Our proposed interface could contribute to an immersive VR experience design.