Multi-Modal Biometric Validation Using Fingerprint and Tremor Sensors
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Solution Overview
Problem
Current biometric systems for user verification in electronic devices, such as mobile phones, often have a high False Rejection Rate (FRR), leading to insecure and inconvenient user access, as they rely solely on fingerprint recognition, which can incorrectly reject trusted users.
Innovation Solution
Combining fingerprint sensors with tremor sensors to validate users by matching detected fingerprint and tremor data, allowing for secure and simple user input detection by utilizing both biometric data types simultaneously.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If only fingerprint sensor is used for user verification, then the device operation is simple, but the False Rejection Rate is high (3% FRR)
Solution Approach 1:
The patent combines fingerprint sensor data with tremor sensor data to create a multi-modal biometric verification system. The processor analyzes both fingerprint patterns and tremor characteristics simultaneously, merging two different sensing modalities to improve verification reliability while maintaining operational simplicity for the user.
2Reliability
If tremor sensor is added to fingerprint sensor, then the user verification reliability is improved, but the device complexity increases
Solution Approach 1:
The tremor sensor serves multiple functions: it detects hand tremor characteristics for biometric verification, and can potentially detect other motion patterns. The processor is designed to handle both fingerprint data and tremor data, making the verification system multi-functional. This multi-functionality justifies the added complexity by providing improved verification reliability without requiring separate dedicated systems for each function.
3Reliability
If multiple sensors are used for validation, then the False Rejection Rate is reduced, but the processing time increases
Solution Approach 1:
The system performs preliminary processing of tremor data and fingerprint data in parallel during the sensor acquisition phase. The processor begins analyzing tremor characteristics while the fingerprint scan is still being taken, and vice versa. This preliminary action allows the system to reduce overall processing time despite using multiple sensors, as the analysis of different data types occurs concurrently rather than sequentially.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The combination of fingerprint and tremor sensors significantly reduces the FRR, enhancing user experience by providing a more reliable and efficient method for user verification without increasing user interaction, as demonstrated by the improved ROC curve results.
Implementation Method 1
a fingerprint sensor connected to the input surface for detecting user input fingerprint data
Implementation Method 2
a tremor sensor for detecting user input tremor data
Data Source
AI summary
Method for validating a trusted user of an electronic device, which electronic device comprises an input surface, e.g. on a key, dedicated for application of a user finger; a user input data sensor system, including a fingerprint sensor connected to the input surface for detecting user input fingerprint data, and a tremor sensor for detecting user input tremor data; data access to stored user input data corresponding to a trusted user; and a main processor system configured to match detected user input data with stored input data for validation of a trusted user. A triggering algorithm may run in a sub-sensor system, for sensing device handling and comparing sensed device handling with stored data. If the comparison reveals that user input is likely to occur based on the, a command is sent to the main processing system to trigger activation of tremor sensing and matching.