Eye-Tracking and EEG Target Selection for XR Intent Detection
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Solution Overview
Problem
Existing human-computer interface systems lack intuitive and accurate methods for selecting targets in extended reality environments, particularly in scenarios where gaze-based interactions are employed, often leading to false positives and negatives.
Innovation Solution
A system and method utilizing an oculomotor-brain-computer interface that combines eye-tracking and neural signal analysis, specifically detecting anticipatory negative potentials like Stimulus-Preceding Negativity (SPN) and Contingent Negative Variation (CNV), to determine user intent for target selection, with feedback mechanisms to confirm selections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If gaze-based interaction is used for target selection, then ease of operation is improved, but measurement precision deteriorates due to false positives and negatives
Solution Approach 1:
The patent combines multiple data sources (gaze patterns from eye-tracking and neural signals from EEG) into a unified target selection system. The processing unit integrates these different data types to make more accurate intent detection, resolving the contradiction by merging the ease of gaze-based operation with the precision of multi-modal validation.
Solution Approach 2:
The patent introduces neural signal analysis as an intermediary layer between gaze detection and target selection confirmation. This intermediary validates gaze-based selections by detecting anticipatory negative potentials, reducing false positives while maintaining the intuitive gaze-based interaction flow.
2Measurement precision
If multiple data sources are integrated for target selection, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The processing unit is designed to handle multiple data types (gaze coordinates, neural signals, fixation duration) through a single integrated architecture. This multi-functional approach allows the system to process diverse data sources without proportionally increasing complexity, as the same processing framework handles all inputs.
Solution Approach 2:
The system incorporates feedback mechanisms where neural signal analysis validates gaze-based selections in real-time. This feedback loop allows the system to correct false positives dynamically, improving precision while the automated feedback process manages complexity by handling validation automatically rather than requiring additional manual intervention.
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
Enhances target selection accuracy by reducing false positives and negatives, providing intuitive interaction in extended reality environments, and offering adaptable feedback to users.
Implementation Method 1
an eye-tracking unit configured to capture gaze patterns of a user
Implementation Method 2
a neural signal capture unit configured to detect neural signals dependent on brain electrical activity from the user
Implementation Method 3
The anticipatory negative potential may comprise a Stimulus-Preceding Negativity (SPN) and/or a Contingent Negative Variation (CNV)
Implementation Method 4
The anticipatory negative potential may comprise a Stimulus-Preceding Negativity (SPN) and/or a Contingent Negative Variation (CNV)
Data Source
AI summary
A human-computer interface system and method for target selection on a computer-generated display includes an eye-tracking unit configured to capture gaze patterns of a user, a neural signal capture unit configured to detect neural signals (such as electroencephalogram (EEG) signals) from the user, and a processing unit. The processing unit is configured to analyze the gaze patterns and neural signals to identify an anticipatory negative potential associated with the user's intent to select a particular target, and to initiate a target selection based on the identified anticipatory negative potential.