EEG Processing System for Real-Time User Experience Customization
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Solution Overview
Problem
Current EEG technologies lack effective methods for personalized user experience management, as they fail to seamlessly integrate real-time brain activity data with device control systems to customize user experiences across various environments and devices.
Innovation Solution
The system utilizes EEG data to generate user-specific configurations by analyzing baseline readings, comparing subsequent readings, and transmitting control signals to devices to customize user experiences based on preferences and biometric data, integrating with networks for real-time data transfer and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If EEG data is integrated with device control systems to enable personalized user experience management, then user experience customization is improved, but system complexity increases
Solution Approach 1:
The patent introduces an EEG processing system as an intermediary between EEG devices and target devices. This mediator receives EEG data, processes it through spectral analysis to generate user-specific configurations, and transmits control signals to customize device experiences. The intermediary architecture allows complex EEG processing without directly complicating the target devices, resolving the contradiction between customization capability and system complexity.
2Adaptability or versatility
If real-time EEG data analysis is performed to identify and customize user experiences, then user experience personalization is improved, but processing time increases
Solution Approach 1:
The patent performs spectral analysis of EEG data to identify user-specific patterns and generates user-specific configurations in advance. By pre-processing EEG data and creating user profiles before actual device interaction, the system reduces real-time processing requirements. When a user interacts with a device, the pre-generated configurations enable immediate personalization without extensive real-time analysis, thus reducing processing time while maintaining personalization quality.
3Measurement precision
If multiple user-specific EEG configurations are stored and managed, then user identification accuracy is improved, but data storage requirements increase
Solution Approach 1:
The patent extracts and stores only the essential spectral characteristics and user-specific patterns from EEG data, rather than storing complete raw EEG datasets. By taking out only the critical identification features and configuration parameters needed for user recognition and customization, the system achieves high user identification accuracy while minimizing data storage requirements. This selective extraction approach maintains precision without proportionally increasing storage demands.
Data Source
AI summary
Embodiments of the invention are directed to systems, methods, and computer program products for collection of and utilization of electroencephalography (EEG) data for user experience and interaction management. The invention interconnects with a network for real-time user experience modification based on user identification via EEG data. In this way, upon recognition and analysis of EEG data, the invention forms and modify a user specific experience via integration within third party systems. EEG readings are segmented, sorted, and matched to a user baseline EEG reading to identify the user and modify the user experience based on quantifiable points.