Wearable Sensor Fusion for Automatic Device Login
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Solution Overview
Problem
Users face the inconvenience of needing to log in to devices without their identity associated, such as public computers, by manually providing credentials, which disrupts the personalized configuration typically found on devices with their identity, like smartphones or smartwatches.
Innovation Solution
A system that uses sensors on devices with and without user identities to correlate gestures, allowing the identity from a device with the user to be associated with a device without the identity, enabling seamless configuration and login based on gesture recognition and correlation values exceeding a threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual login with username and password is used on Type 2 devices, then security is improved, but ease of operation deteriorates
Solution Approach 1:
The patent replaces the mechanical interaction of manually typing credentials with a gesture-based recognition system. Sensors detect gestures (such as hand movements or device handling patterns) to automatically identify and authenticate users, substituting the manual login process with automated gesture recognition while maintaining security through correlation analysis of gesture patterns.
2Reliability
If Type 2 devices require manual login, then device security is improved, but productivity deteriorates
Solution Approach 1:
The system performs preliminary gesture pattern analysis and user identification before the actual login is required. By pre-establishing the connection between gesture patterns and user identities through sensor data correlation, the system prepares authentication credentials in advance, enabling rapid access without interrupting the user's workflow when login is actually needed.
3Reliability
If gesture correlation with threshold validation is implemented, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent introduces a server as an intermediary that handles the complex gesture correlation analysis and threshold validation processes. The server receives sensor data from multiple devices, performs the correlation analysis to determine if gestures match known user patterns, and returns authentication results. This distributes the computational complexity from individual devices to a centralized system, reducing device complexity while maintaining high authentication reliability.
Data Source
AI summary
A user may have a device that contains the user's identity. Rather than log into a second device that user may make use of the fact that the user is already logged into a device as disclosed herein. The user may perform a gesture that may be observed or sensed by one or more sensors on a first device and a second device that contains the user's identity. A correlation between the sensor data may be performed and, if the correlation value exceeds a threshold value, a portion of the user's identity may be shared with the first device.


