Virtual Reality Interaction Analysis System
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Solution Overview
Problem
Current solutions for analyzing user interactions in virtual reality environments are inadequate, as they rely on pre-defined libraries of expected interactions, failing to accurately capture natural and unconscious user gestures, which can interfere with application functionality.
Innovation Solution
A system that collects and analyzes user interactions within a virtual reality environment, including gestures, spatial contexts, and application contexts, to determine relationships between user inputs and application responses, providing insights through a report that facilitates improved user experience and application responsiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If pre-defined libraries of expected interactions are used, then analysis structure is simplified, but measurement precision of actual user behavior deteriorates
Solution Approach 1:
Instead of mapping user actions to pre-defined expected interactions, the system inverts the approach by collecting all user interactions and automatically discovering patterns and relationships without predefined constraints, allowing unexpected and natural gestures to be identified and analyzed.
Solution Approach 2:
The system enables self-service by allowing the interaction library to be automatically built and refined from actual user behavior data without requiring manual curation of expected interactions. The system serves itself by continuously learning from user actions and updating its understanding of valid interactions.
2Ease of manufacture
If pre-defined interaction libraries are used, then implementation is easier, but adaptability to natural user gestures deteriorates
Solution Approach 1:
The interaction library transitions from a static, pre-defined structure to a dynamic system that continuously evolves based on actual user behavior. The system adapts its understanding of valid interactions in real-time, allowing it to accommodate natural and unexpected gestures while maintaining ease of implementation through automated learning processes.
Solution Approach 2:
The system changes the parameters of interaction recognition from fixed, pre-defined categories to flexible, data-driven patterns. By adjusting recognition parameters based on actual user behavior statistics, the system maintains implementation simplicity while significantly improving adaptability to diverse and natural user gestures.
3Loss of information
If detailed tracking of all user interactions is implemented, then user behavior understanding is improved, but data processing complexity increases
Solution Approach 1:
The system extracts only the essential and meaningful relationships from the comprehensive interaction data, separating signal from noise. By focusing on identifying significant patterns and correlations rather than processing all raw interaction data equally, the system reduces processing complexity while maintaining rich behavioral understanding.
Solution Approach 2:
The system implements partial action by selectively analyzing and processing only those interaction patterns that provide meaningful insights, rather than uniformly processing all possible interaction data. This approach captures sufficient behavioral information while avoiding the excessive complexity of comprehensive data processing.
Data Source
AI summary
The disclosure describes systems and methods of analyzing interactions with a user interface for an application, where the user interface is implemented at least partly within a virtual reality environment. Certain embodiments provide for receiving interactions that include gestures, spatial contexts, and applications contexts, and receiving results from the application, such as application behavior or error conditions. The user interface interactions and the application results are analyzed. Events, metrics, and relationships are determined based on the analysis. In some cases, additional data (such as historical interactions and results, system environment data, or system configuration data) are received and analyzed, and the determined relationships are further based on the additional data.