Extended Reality Fatigue Detection Using Biometric and Motion Data
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Solution Overview
Problem
Extended reality (XR) devices struggle to dynamically adapt virtual content based on real-world environment features and effectively detect user fatigue, which can lead to dangerous situations or user exhaustion.
Innovation Solution
The system monitors user activity through image and biometric data to detect fatigue, adjusting XR applications by adapting virtual content based on physiological and motion information to prevent exhaustion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If XR devices create fully immersive virtual environments, then user engagement is improved, but user safety deteriorates due to inability to detect fatigue and adapt to real-world conditions
Solution Approach 1:
The system continuously monitors user biometric data (heart rate, temperature, galvanic skin response) and motion data from sensors, providing real-time feedback about user fatigue levels. This feedback loop enables the XR device to detect fatigue states and automatically adjust virtual content or alert users, thereby maintaining safety while preserving engagement.
Solution Approach 2:
The XR device autonomously monitors its own user's physiological state and automatically adapts the virtual environment without requiring external intervention. The system self-adjusts content difficulty, provides breaks, or modifies sensory output based on detected fatigue, enabling safety management to be integrated into the immersive experience itself.
2Reliability
If XR devices provide dynamic adaptation of virtual content, then user safety is improved, but device complexity increases due to multiple sensors and processing requirements
Solution Approach 1:
The XR device integrates multiple sensors (biometric sensors, motion sensors, cameras) that serve dual purposes: capturing data for virtual reality rendering and simultaneously monitoring user fatigue. This multi-functionality reduces the need for separate dedicated monitoring hardware, managing complexity while enabling comprehensive safety monitoring.
Solution Approach 2:
The system combines virtual content rendering functions with fatigue detection and adaptation functions into a unified processing pipeline. The same processors and sensors used for immersive experience delivery are also utilized for safety monitoring, merging previously separate functions to manage device complexity.
3Reliability
If XR devices monitor user fatigue continuously, then user safety is improved, but energy consumption increases due to continuous sensor operation and data processing
Solution Approach 1:
Instead of continuous monitoring at maximum intensity, the system employs periodic sampling of biometric data and motion data at optimized intervals. The monitoring frequency adapts based on user activity level and detected fatigue trends, reducing energy consumption during stable states while maintaining safety during critical transitions.
Solution Approach 2:
The monitoring system dynamically adjusts its operational intensity based on user state. During low-risk periods, monitoring operates at minimal energy consumption; when fatigue indicators suggest increased risk, the system intensifies monitoring frequency and sensitivity, optimizing the balance between safety and energy usage.
Data Source
AI summary
System and techniques are described herein for providing variable rate touch sampling for touch sensors. In one illustrative example, a method of monitoring activity of a person includes obtaining one or more images of a user performing a first movement during a usage instance of an extended reality (XR) device; obtaining first biometric information of the user from at least one first biometric sensor of the XR device while the user performs the first movement; determining fatigue information of the user at least in part based on the one or more images and the first biometric information of the user; and determining an action based on the fatigue information.