Neuroanalysis System for Banknote Classification via Biometric Signals

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Solution Overview

Problem

Conventional methods for assessing human perception of banknotes and communication materials rely on explicit responses, which are prone to social desirability effects and provide less reliable results due to the inability to accurately capture implicit mental processes, leading to incomplete and inaccurate research on human decision-making.

Innovation Solution

A neuroanalysis method that acquires biometric signals from users interacting with banknotes and communication materials, using techniques such as eye tracking, facial expression analysis, and physiological responses to classify banknotes based on neurometric indicators, integrating both conscious and unconscious processes for objective characterization.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If explicit response methods (questionnaires, interviews) are used to assess human perception, then the assessment process is simple and direct, but the results are unreliable due to social desirability effects and inability to capture implicit mental processes

Engineering Contradiction:
Improveaccuracy of perception assessmentVSAvoidcomplexity of measurement system
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent replaces explicit self-reporting methods with implicit biometric measurement systems. Sensors detect physiological signals (electroencephalogram, electrocardiogram, electromyogram, skin conductance, pupil dilation) that automatically reflect mental processes without requiring conscious participant involvement, thereby eliminating social desirability effects and providing more accurate perception assessment.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent introduces biometric sensors as intermediary devices that indirectly measure mental processes through physiological correlates. Instead of directly asking participants about their perceptions, the system uses physiological signals as mediators that reflect underlying cognitive and emotional states, providing objective data without requiring participant introspection or verbal reporting.

Inventive Principle:
Principle #24Intermediary (Mediator)

2Reliability

If implicit measurement techniques (biometric signals, brain imaging) are used, then the accuracy of capturing unconscious processes improves, but the device complexity and measurement difficulty increase

Engineering Contradiction:
Improvevalidity of perception dataVSAvoiddifficulty of biometric signal acquisition
Core Design Contradiction:
ReliabilityVSDifficulty of detecting and measuring

Solution Approach 1:

The patent employs a multi-functional measurement system that simultaneously captures multiple types of biometric signals (electroencephalogram, electrocardiogram, electromyogram, skin conductance, pupil dilation) using a single integrated apparatus. This universal system can detect various physiological correlates of mental processes through multiple sensors working together, reducing the difficulty of measuring complex unconscious processes by combining multiple measurement capabilities in one system.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Solution Approach 2:

The biometric measurement system operates automatically without requiring manual intervention or complex operational procedures. Sensors continuously monitor physiological signals and the system automatically processes the data to extract perception-related information, eliminating the need for manual measurement techniques and reducing operational difficulty.

Inventive Principle:
Principle #25Self-service

3Loss of information

If multiple biometric signals are simultaneously measured, then the comprehensiveness of neural response characterization improves, but the data processing complexity increases

Engineering Contradiction:
Improvecompleteness of mental process dataVSAvoidcomplexity of signal processing system
Core Design Contradiction:
Loss of informationVSDevice complexity

Solution Approach 1:

The patent segments the complex measurement process into distinct functional components, each responsible for detecting specific physiological signals. The system divides the overall task of measuring mental processes into separate channels (electroencephalogram for cortical activity, electrocardiogram for autonomic arousal, electromyogram for motor preparation, skin conductance for emotional activation, pupil dilation for cognitive load), allowing parallel processing and reducing overall system complexity.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent merges multiple biometric signal streams into a unified perception assessment framework. By integrating data from different physiological systems (nervous, cardiovascular, muscular, sudoriferous) into a single analytical model, the system achieves comprehensive characterization of mental processes while managing complexity through unified data processing algorithms that synthesize multiple inputs into coherent perception metrics.

Inventive Principle:
Principle #5Merging (Combining)

Data Source

PatentEP3757950B1Method and system for selecting parameters of a design or security element of banknotes based on neuroanalysis
Publication Date: 2023.08.02 BANCO DE ESPANA
  • EP3757950B1 patent drawingFigure 1
  • EP3757950B1 patent drawingFigure 2~3
  • EP3757950B1 patent drawingFigure 4

AI summary

The present invention relates to a system and a method for classifying banknotes based on neuroanalysis, comprising: providing a user with visual information of a banknote; acquiring, by means of sensors of an input module, biometric signals of the user; segmenting the acquired biometric signals into predetermined periods of time in a process module; identifying certain events as a result of the comparison of each of the segments with pre-established patterns; obtaining at least one biometric variable based on the identified events; analysing the biometric variables according to previously known results stored in a database; establishing a neurometric indicator based on the preceding analysis; and classifying the banknote in an output module according to the established neurometric indicators.