Biometric User Identification for Automatic Interface Configuration
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Solution Overview
Problem
Current user interfaces for virtual and augmented reality environments are cumbersome, inefficient, and place a significant cognitive burden on users, requiring multiple inputs and being error-prone, which wastes energy and detracts from the experience, especially in battery-operated devices.
Innovation Solution
The implementation of a computer system that automatically applies user settings and device calibration based on user identification, using biometric information from input devices such as cameras and sensors to provide personalized interfaces and settings, reducing the number and complexity of user inputs and enhancing the human-machine interface efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If automatic user identification and settings application is implemented, then user interaction efficiency is improved and cognitive load is reduced, but device complexity increases due to biometric processing systems
Solution Approach 1:
The system automatically identifies users and applies their settings without requiring manual input. The biometric authentication and settings application occur autonomously based on detected user presence and characteristics, eliminating the need for users to manually configure their preferences each time they use the device.
Solution Approach 2:
User settings and preferences are pre-configured and stored in advance. When a user is detected, the system retrieves and applies the pre-stored settings associated with that user's biometric identification, eliminating the need for real-time configuration and reducing interaction requirements.
2Reliability
If multiple manual inputs are required for user configuration, then system security is maintained, but user cognitive burden increases and interaction time is extended
Solution Approach 1:
The system extracts and processes only the essential biometric information needed for identification and settings retrieval. By focusing on key identifying characteristics rather than requiring comprehensive manual verification procedures, the system maintains security while significantly reducing interaction time and cognitive burden.
3Device complexity
If manual user settings configuration is used, then device complexity is kept low, but energy consumption increases due to prolonged operation and processing
Solution Approach 1:
User settings are pre-loaded and stored in the device memory during initial configuration. Subsequent user identifications trigger automatic retrieval and application of pre-stored settings, eliminating the need for real-time processing and configuration operations that would consume additional energy.
Solution Approach 2:
The system performs automatic settings application based on biometric detection without requiring active user participation. This autonomous operation reduces the time the device remains in active processing states, thereby lowering overall energy consumption compared to manual configuration methods.
Data Source
AI summary
The present disclosure generally relates to user interface for electronic devices, including wearable electronic devices, and device settings based on user identification.