Adapting a Virtual Reality Experience for a User Based on a Mood Improvement Score

Smart overview of the Invention

The patent application discusses a virtual reality (VR) system designed to enhance a user's mood through adaptive experiences. The system utilizes a database of digital assets, each with an associated mood improvement score. These scores predict the potential mood enhancement effects for users with similar profiles. By leveraging user profile data and these scores, the system can tailor VR experiences to individual users, aiming to improve their mood effectively.

Technical Background

Traditional media systems, such as movies or video games, offer static or interactive content but lack personalization for mood improvement. The challenge lies in predicting how specific content affects an individual's mood. This innovation addresses this by creating a dynamic VR experience that adapts based on user feedback and biometric data, providing a more personalized approach to mood enhancement.

System Components

The VR system comprises several key components: a media server, media processing devices, and client devices. The media server delivers content and processes user data to tailor experiences. Media processing devices, like VR headsets, present the immersive content and capture user inputs and biometric data. Client devices allow users to manage profiles and provide feedback through surveys, enhancing the system's ability to adapt experiences.

Customization Process

Digital assets are selected for inclusion in VR experiences based on their scores and user preferences. The system can incorporate user-specified assets or apply random selection criteria to diversify experiences. User responses are collected via surveys or biometric measurements before and after the VR session to assess mood changes, enabling the system to update asset scores and refine future experiences.

Adaptive Learning

The system continuously learns from user interactions by updating asset scores and potentially reclassifying users into different cohorts based on updated profile data. This adaptive learning process ensures that the VR experiences remain effective in improving mood by closely aligning with individual user needs and preferences.