Apparatus, method, and computer program for identifying a user of a display unit
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Solution Overview
Problem
Existing display units, such as interactive mirrors, face challenges in reliably identifying users to ensure privacy, particularly in multi-user settings where personal health data is shared, as current methods are not accurate enough to prevent incorrect data dissemination.
Innovation Solution
An apparatus and method that utilize physiological measurements, such as weight, height, or biometric data, by comparing received measurements with time series data of multiple users to determine identity with high confidence, allowing seamless user-specific content presentation without manual login.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single physiological measurement is used for user identification, then the identification process is simple and fast, but the accuracy is insufficient leading to incorrect user identification
Solution Approach 1:
The system performs preliminary actions by collecting and storing multiple physiological measurements over time for each user, creating a baseline profile before actual identification is needed. This time series data is prepared in advance, allowing the system to compare new measurements against established patterns rather than relying on single-point comparisons.
Solution Approach 2:
The patent transitions from single-dimensional identification (one measurement) to multi-dimensional identification (time series of measurements). By adding the time dimension and analyzing measurement trends across multiple data points, the system achieves higher identification accuracy while managing complexity through structured data organization.
2Reliability
If physiological measurements are analyzed using time series data, then user identification accuracy is improved, but the processing complexity and computational requirements increase
Solution Approach 1:
The identification process is segmented into distinct stages: data collection, time series analysis, pattern recognition, and final identification decision. Each stage processes specific aspects of the data independently, reducing overall complexity while maintaining high reliability through systematic multi-step analysis.
Solution Approach 2:
The system incorporates feedback mechanisms where identification results and measurement patterns are continuously refined. The time series data provides feedback on user physiological trends, allowing the system to adjust identification thresholds and improve reliability over time while managing computational complexity through adaptive processing.
Data Source
AI summary
An apparatus, method, and computer program for identifying a user of a display unit. The apparatus comprises a processor configured to receive a physiological measurement for a first user; compare the received physiological measurement with a plurality of time series of physiological measurements, each time series corresponding to one of a plurality of users; and determine, based on the comparison, an identity of the first user.