VR Exertion Prediction System for Real-World Device Adaptation
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Solution Overview
Problem
Current systems fail to identify and mitigate physical strains on users after Virtual Reality (VR) sessions, leading to potential injuries or discomfort in real-world activities due to lack of correlation between VR interactions and subsequent real-world activities.
Innovation Solution
An electronic device with a processor and memory module that predicts physical strains during VR interactions, correlates them with upcoming real-world activities, and alters operational settings of real-world devices to minimize strain, using data aggregation, VR context analysis, and machine learning models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If VR sessions provide high physical exertions to enhance user experience, then user engagement and entertainment value improve, but user safety and comfort deteriorate due to unmitigated physical strains
Solution Approach 1:
The system performs preliminary actions by predicting physical strains before they occur during VR sessions. It analyzes upcoming VR interactions and forecasts potential physical exertions on specific body parts, then proactively recommends mitigating actions to users before the actual strain occurs, preventing harm rather than reacting to it afterward.
Solution Approach 2:
The system implements feedback by continuously monitoring VR interaction data, predicting physical strains, and providing real-time recommendations to users. It creates a closed-loop system where user responses to recommendations are tracked, and the prediction model is continuously refined based on actual strain outcomes, improving accuracy over time.
2Reliability
If the system provides detailed predictions and recommendations for physical strains, then user safety improves, but system complexity increases due to multiple data processing requirements
Solution Approach 1:
The system segments the complex prediction task into distinct modules: VR interaction data collection, physical strain prediction based on body part analysis, upcoming activity identification, and recommendation generation. Each module handles a specific aspect of the problem, making the overall system more manageable and maintainable while improving reliability through specialized processing.
Solution Approach 2:
The system achieves universality by creating a multi-functional platform that not only predicts physical strains but also identifies upcoming real-world activities, generates personalized recommendations, and adapts to different users based on historical data. This single system performs multiple functions that collectively improve user safety without requiring separate specialized systems.
3Measurement precision
If the system correlates VR interactions with upcoming real-world activities, then recommendation accuracy improves, but data processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-processing and storing VR interaction data as users engage in VR activities. It prepares prediction models in advance and pre-identifies upcoming real-world activities based on scheduled data, so that when prediction is needed, the processing time is minimized while maintaining high accuracy through pre-computed correlations.
Data Source
AI summary
According to an embodiment of the disclosure, a method performed by an electronic device for managing physical exertion of an user may include determining at least one physical strain exerted on at least one body part of the user in at least one Virtual Reality (VR) interaction of a VR session, identifying at least one real-world device where the at least one body part of the user performs at least one upcoming real-world activity subsequent to the at least one VR interaction, and altering at least one operational setting of the at least one identified real-world device, wherein the at least one operational setting corresponds to the at least one physical strain exerted on the at least one body part of the user.