Digital Twin Verification via Biometric Signal Comparison
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Solution Overview
Problem
Verifying the authenticity of a digital twin of a biological system to ensure it accurately represents the subject it is associated with, particularly in healthcare settings where multiple providers may need to access and utilize the digital twin for accurate decision-making and treatment planning.
Innovation Solution
A method involving obtaining sensor signals from the subject, processing these signals with a digital twin to generate simulated signals, and comparing them to determine a verification result, using feature extraction algorithms and biometric templates to assess matching scores and verify the digital twin's accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a digital twin is constructed using imaging data and biometric information of a subject, then the digital twin can provide accurate clinical decision support and treatment planning, but verifying the authenticity and correspondence of the digital twin to the subject becomes challenging and complex
Solution Approach 1:
The system uses feedback loops where sensor signals from the subject are continuously compared with signals generated by the digital twin. The verification process incorporates feedback from multiple biometric parameters (facial geometry, voice characteristics, gait patterns) to continuously assess and confirm the digital twin's accuracy in representing the subject, allowing for dynamic adjustment and validation.
Solution Approach 2:
The invention transforms the verification problem from a complex qualitative assessment into a quantitative parameter-based system. Multiple biometric parameters (facial landmark coordinates, voice frequency spectra, gait temporal-spatial metrics) are extracted and compared numerically. The system changes the verification approach by using parameter matching scores and threshold-based validation to simplify the confirmation process while maintaining high accuracy.
2Adaptability or versatility
If multiple healthcare providers need to access and utilize the digital twin for decision-making, then collaborative care and comprehensive treatment planning are enabled, but ensuring the digital twin's authenticity and preventing unauthorized access becomes more difficult
Solution Approach 1:
The system performs preliminary verification actions before granting access to healthcare providers. Biometric templates are pre-computed and stored securely, and authentication checks are performed in advance before any healthcare provider can access or utilize the digital twin. This preliminary validation ensures that only authorized providers can access the digital twin while maintaining security.
Solution Approach 2:
The invention introduces an intermediary verification system that acts as a mediator between healthcare providers and the digital twin. This intermediary layer performs authentication and authorization checks, validating the provider's credentials and the digital twin's authenticity before allowing access. The intermediary ensures secure multi-provider access without compromising the digital twin's integrity or security.
3Measurement precision
If biometric templates and feature extraction algorithms are used to verify the digital twin, then verification accuracy and matching scores can be improved, but computational requirements and processing time increase
Solution Approach 1:
The verification process is segmented into multiple independent stages: facial feature extraction, voice feature extraction, gait feature extraction, template matching, and score aggregation. Each stage processes specific biometric parameters separately, allowing for optimized computation at each step and enabling parallel processing to reduce overall verification time while maintaining high accuracy.
Solution Approach 2:
The system implements a multi-level verification approach where critical biometric parameters are verified with high precision while less critical parameters use simplified validation. The verification process can stop early if confidence thresholds are met, avoiding unnecessary computation. This partial action approach maintains high verification accuracy for essential parameters while reducing overall processing time through selective computation.
Data Source
AI summary
Systems and methods are proposed for verifying whether a digital twin of abiological asset (or biological system) of a subject (110) indeed relates to the subject (110). Such proposals may be based on obtaining: a first signal comprising a value of a physiological parameter of the subject (e.g. determined by a physical and/or virtual sensor arrangement); and a second signal generated by the digital twin that simulates a value of a physiological parameter of the subject (110). By comparing the first and second signals, a verification result may then be determined.