Emotion-Adaptive Virtual Image Generation System
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Solution Overview
Problem
Existing VR/AR systems struggle to tailor user experiences effectively, as they do not account for individual users' emotional states or subconscious motivations, leading to suboptimal engagement and satisfaction.
Innovation Solution
A method that uses biometric data to determine a user's emotional state and adjusts the VR/AR experience accordingly, by presenting stimuli, sensing biometric parameters, generating data, and performing actions discernible to the user to facilitate specific objectives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If VR/AR systems use generic user experiences without personalization, then device complexity is reduced, but user engagement and satisfaction deteriorate
Solution Approach 1:
The system automatically captures biometric data, determines emotional states, and adjusts virtual content without requiring manual user input or complex configuration. The system serves itself by using its own sensors and processing capabilities to personalize the experience in real-time, eliminating the need for complex setup procedures while maintaining high adaptability
Solution Approach 2:
The system continuously monitors user biometric parameters (heart rate, skin conductance, facial expressions) and uses this feedback to dynamically adjust the virtual environment. This closed-loop feedback mechanism enables automatic personalization without requiring complex pre-programming, as the system adapts based on real-time user responses
2Reliability
If VR/AR systems incorporate biometric sensing and emotional state detection, then user engagement is improved, but device complexity increases
Solution Approach 1:
The system uses a single integrated platform that performs multiple functions: capturing biometric data from various sensors, processing the data to determine emotional states, and adjusting virtual content accordingly. This multi-functional approach consolidates what would otherwise require separate complex subsystems into one unified system, improving reliability while managing complexity
Solution Approach 2:
The system introduces an intermediate layer of emotional state determination that translates raw biometric data into meaningful emotional states, which then guide content adjustment. This intermediary processing layer simplifies the overall system architecture by creating a clear separation between data collection, analysis, and application, making the system more reliable and easier to manage
3Reliability
If VR/AR systems dynamically adjust content based on emotional states, then user immersion is enhanced, but processing requirements and energy consumption increase
Solution Approach 1:
The system periodically samples biometric data and adjusts virtual content at strategically determined moments rather than continuously. This periodic approach maintains user immersion by responding to emotional state changes while significantly reducing processing requirements and energy consumption compared to continuous real-time adjustment
Solution Approach 2:
The system adjusts only the necessary aspects of the virtual environment based on detected emotional states, rather than completely reconfiguring the entire virtual world. This partial adjustment approach maintains immersion by responding to user needs while minimizing the processing power and energy required for content modification
Data Source
AI summary
A method of operating a virtual image generation system comprises allowing an end user to interact with a three-dimensional environment comprising at least one virtual object, presenting a stimulus to the end user in the context of the three-dimensional environment, sensing at least one biometric parameter of the end user in response to the presentation of the stimulus to the end user, generating biometric data for each of the sensed biometric parameter(s), determining if the end user is in at least one specific emotional state based on the biometric data for the each of the sensed biometric parameter(s), and performing an action discernible to the end user to facilitate a current objective at least partially based on if it is determined that the end user is in the specific emotional state(s).