EEG Brain Signature Extraction for Single-Trial Identification

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Current EEG data processing methods are limited in accurately and efficiently capturing unique individual brain activity for identification and authentication, as they often require multiple trials, leading to information loss and reliance on subjective evaluations, while existing biometric systems face security challenges and environmental limitations.

Innovation Solution

A novel system and method for EEG recording and processing that utilizes eigenvectors, eigenvalues, and 4D visualization to create a specific brain signature, allowing for accurate and efficient person identification and personality assessment by analyzing EEG signals from multiple scalp locations and applying techniques like wavelet transforms and fast Fourier transforms.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If multiple trials are conducted to average out random brain activity and obtain ERP, then the reliability of brain response detection is improved, but the loss of distinctive physiological information increases and recording time increases

Engineering Contradiction:

Improvebrain response detection reliabilityVSAvoiddistinctive physiological information

Core Design Contradiction:

ReliabilityVSLoss of information

Solution Approach 1:

The patent extracts distinctive physiological information from individual EEG trials without requiring multiple trial averaging. By using advanced signal processing techniques, the system isolates and preserves unique brain characteristics that would otherwise be lost in traditional ERP averaging, enabling reliable identification from single-trial data

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent applies preprocessing and feature extraction techniques to EEG signals before analysis to enhance the visibility of brain responses to specific stimuli. This preliminary processing allows the system to detect relevant brain activity in single trials without needing to average multiple trials, thus preserving distinctive physiological information

Inventive Principle:

Principle #10Preliminary action

2Reliability

If multiple trials are conducted to average out random brain activity and obtain ERP, then the reliability of brain response detection is improved, but the recording time increases

Engineering Contradiction:

Improvebrain response detection reliabilityVSAvoidERP recording time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent extracts reliable brain response signals from single EEG trials using advanced signal processing, eliminating the need for multiple trial averaging. This extraction approach maintains detection reliability while reducing recording time from multiple trials to a single trial or fewer

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent skips the traditional multiple-trial averaging process by using techniques that can reliably detect brain responses in single trials. This rushing through the data collection process reduces recording time while maintaining or improving detection reliability through sophisticated analysis methods

Inventive Principle:

Principle #21Skipping (Rushing through)

3Ease of operation

If traditional EEG interpretation methods are used by visual analysis by highly trained experts, then the ease of operation is maintained, but the productivity and accuracy of brain function evaluation decrease

Engineering Contradiction:

ImproveEEG interpretation easeVSAvoidbrain function evaluation productivity

Core Design Contradiction:

Ease of operationVSProductivity

Solution Approach 1:

The patent replaces the mechanical process of visual analysis by experts with automated computational methods including signal processing, pattern recognition, and machine learning algorithms. This substitution maintains ease of operation while dramatically improving productivity and objectivity of EEG interpretation

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent enables the EEG system to perform self-analysis through automated processing and interpretation algorithms. The system automatically detects features, processes signals, and generates evaluations without requiring manual visual analysis by experts, thereby improving productivity while maintaining operational simplicity

Inventive Principle:

Principle #25Self-service

4Ease of operation

If traditional EEG interpretation methods are used by visual analysis by highly trained experts, then the ease of operation is maintained, but the measurement precision and objectivity decrease

Engineering Contradiction:

ImproveEEG interpretation easeVSAvoidbrain function evaluation precision

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The patent replaces subjective visual analysis with objective computational methods including signal processing and pattern recognition algorithms. This substitution maintains ease of operation while dramatically improving measurement precision and objectivity through automated, consistent, and reproducible analysis

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS10318833B2System and method for person identification and personality assessment based on EEG signal

Publication Date: 2019.06.11 AGARWAL PUNEET

AI summary

The present invention relates a novel system and method for person identification and personality assessment based on electroencephalography (EEG) signal. More particularly, this invention relates to a novel method of EEG recording and processing to map the inherent and unique properties of brain in the form of highly specific brain signature to be used as means for person identification and personality assessment.