VR User Behavior Data Visualization and Analysis System
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for analyzing user behavior in Virtual Reality (VR) and Augmented Reality (AR) environments are inefficient, relying on manual observation and video recordings, which are time-consuming and do not effectively process the complex data from new VR/AR hardware and behavior inputs, lacking visualization of new forms of behavior data and metrics specific to VR/AR setups.
Innovation Solution
A system and method for collecting, processing, and visualizing user behavior data in VR/AR environments, filtering data based on physical characteristics, emotional states, and VR/AR hardware specifics, using a software plugin to capture targeted Behavior Data Segments and generate metrics, allowing for efficient objective evaluation and comparison of user experiences across different users and hardware setups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual observation and video recordings are used to analyze user behavior, then no specialized processing is needed, but the analysis is time-consuming and inefficient
Solution Approach 1:
The patent replaces manual observation (mechanical human analysis) with an automated software system that collects, processes, and visualizes VR/AR behavior data. The system substitutes human analysts with computational algorithms that automatically generate behavior metrics and visualizations, dramatically improving analysis efficiency while managing system complexity through automated workflows.
Solution Approach 2:
The system enables self-service analysis by automatically collecting raw behavior data from VR/AR sessions, processing it through predefined algorithms, and generating visualizations without requiring manual intervention. The automated pipeline serves itself by transforming raw data into actionable insights without human effort, resolving the contradiction between efficiency and complexity.
2Loss of information
If comprehensive user behavior data is collected, then analysis completeness improves, but data processing complexity increases
Solution Approach 1:
The patent segments comprehensive behavior data into distinct categories (physical movements, interactions, emotional states, physiological data) and processes each segment with specialized algorithms. This segmentation allows the system to maintain complete data collection while managing processing complexity through modular, category-specific analysis pipelines rather than attempting to process all data uniformly.
Solution Approach 2:
The system transforms raw behavior data into standardized parameters and metrics (e.g., converting movement trajectories into velocity vectors, transforming interaction sequences into event types). By changing the parameter representation of raw data, the system maintains information completeness while simplifying subsequent processing and analysis operations.
3Measurement precision
If detailed behavior metrics are generated, then evaluation precision improves, but computational requirements increase
Solution Approach 1:
The patent implements partial action by generating detailed behavior metrics selectively based on analysis needs rather than computing all possible metrics continuously. The system calculates precise measurements only for relevant behavior aspects, reducing unnecessary computational energy consumption while maintaining measurement precision where required.
Solution Approach 2:
The system performs preliminary processing of behavior data into standardized formats and pre-computes basic metrics during data collection. By preparing data in advance with preliminary calculations, the system reduces the computational burden during detailed analysis phases, balancing measurement precision with energy consumption through staged processing.
Data Source
AI summary
According to one aspect of the disclosure, a method of analyzing users in a Virtual Reality (VR) or Augmented Reality (AR) environment is provided. The method includes acts of receiving a data stream including information indicative of one or more user actions performed by a user in a simulated environment, analyzing the data stream to determine whether a first condition is satisfied, capturing, responsive to determining that the first condition is satisfied, first user behavior data including at least a portion of the information indicative of the one or more user actions, receiving a request for user behavior data satisfying the first criterion, extracting, from the user behavior data, a plurality of user behavior data segments, transmitting, responsive to receiving the request, the plurality of user behavior data segments, and displaying a visualization of the plurality of user behavior data segments.