Biometric Identification Using Pulse Waveform Synchronous Averaging
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Solution Overview
Problem
Current biometric identification methods, such as fingerprint and facial scans, face challenges in specificity, constancy over time, and complexity, while single-parameter biometrics like pulse waveform analysis lack robustness and sensitivity to external conditions.
Innovation Solution
A biometric identity confirmation system utilizing pulse waveform data analysis, where subject characterization data is generated during enrollment and used for authentication, employing synchronous averaging and trigger candidate identification to determine the start points of pulse cycles, and featuring an algorithm that discards false triggers and synchronizes cycles for accurate identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image processing methods (fingerprint, retinal, iris, facial scans) are used for biometric identification, then identification accuracy is improved, but computational complexity and processing time increase
Solution Approach 1:
The patent extracts the essential biometric information from complex images by converting them into simplified time-series representations. Instead of processing entire images with sophisticated algorithms, the system extracts pulse waveform signals that capture the essential cardiovascular characteristics, thereby reducing computational complexity while maintaining identification accuracy.
Solution Approach 2:
The patent replaces complex image processing systems with a simpler time-series analysis approach. By substituting the mechanical/image-based identification system with a physiological signal-based system, the computational burden is significantly reduced while preserving the core identification function.
2Ease of operation
If single parameter biometrics (height, weight, pulse waveform) are used for identification, then simplicity is improved, but specificity and reliability deteriorate
Solution Approach 1:
The patent utilizes the periodic nature of pulse waves to enhance the information content of a single-parameter measurement. By analyzing multiple cycles of the periodic pulse waveform and applying synchronous averaging, the system extracts reliable biometric characteristics from what would otherwise be a simple temporal signal, thereby improving specificity while maintaining simplicity.
Solution Approach 2:
The patent transforms the simple pulse waveform signal into a more informative representation by analyzing multiple parameters including timing intervals, amplitude characteristics, and waveform morphology. This multi-parameter analysis of a single physiological signal enhances reliability without requiring multiple separate biometric measurements.
3Reliability
If pulse waveform data is used for biometric identification, then robustness to external conditions is improved, but sensitivity to metabolic fluctuations worsens
Solution Approach 1:
The patent applies preliminary processing steps including synchronous averaging and trigger candidate identification to establish a stable baseline representation of the pulse waveform. By pre-processing the data to eliminate noise and variability before comparison, the system creates a robust reference that is less sensitive to metabolic fluctuations while maintaining robustness to external conditions.
Solution Approach 2:
The system uses feedback mechanisms in the form of synchronous averaging where the detected trigger points are used to align and average multiple pulse cycles. This feedback-based alignment process enhances the signal-to-noise ratio and creates a more stable representation that is less susceptible to both external conditions and metabolic variations.
Data Source
AI summary
A biometric identity confirmation system is based on pulse waveform data for the subject. During an initial enrollment mode, pulse waveform data for a known subject are used to generate subject characterization data for the known subject. The subject characterization data includes an exemplar created by synchronous averaging of pulse waveform data over multiple pulse cycles. A number of trigger candidate are identified for the start point of each pulse cycle. The time delay between trigger candidates is analyzed to discard false trigger candidate and identify true candidates, which are then used as the start points for each pulse cycle in synchronous averaging of the pulse waveform data. During a subsequent identity authentication mode, pulse waveform data for a test subject are analyzed using the subject characterization data to confirm whether the identity of the test subject matches the known subject.