Sleep Biometric Dream Classification by Clarity and Emotion
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Solution Overview
Problem
Existing technologies do not effectively extract and display phenomena in dreams experienced by a subject during sleep, particularly focusing on the clarity and emotional aspects of dreams.
Innovation Solution
An information processing device and method that utilizes biological sensors to measure brain waves, heart rate, and other autonomic nervous system indicators to determine the clarity and emotional level of dreams, classifying them for output based on predefined threshold values, and optionally encrypting sensitive information for privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If biological information is continuously monitored during sleep to extract dream phenomena, then measurement precision of dream clarity and emotional level is improved, but device complexity increases due to multiple sensors and processing units
Solution Approach 1:
The system divides dream analysis into separate functional modules: one dedicated to measuring dream clarity through brain wave activity, and another for measuring emotional level through autonomic nervous system indicators. This segmentation allows each module to specialize in specific measurements, improving overall precision while maintaining manageable complexity through modular design
Solution Approach 2:
The information processing device integrates multiple measurement functions into a single system that simultaneously monitors both brain wave activity and autonomic nervous system indicators. This multi-functional approach consolidates what would otherwise require separate devices, improving measurement precision across multiple parameters while avoiding the complexity of multiple independent systems
2Loss of information
If all biological information during sleep is output externally for analysis, then information completeness is improved, but loss of information occurs through encryption of sensitive dream content
Solution Approach 1:
The system applies different processing treatments to different types of biological information based on their sensitivity. Non-sensitive dream content is output in plain form for complete analysis, while sensitive personal information is selectively encrypted. This local differentiation of information handling preserves analytical completeness for general data while protecting privacy for sensitive data
Solution Approach 2:
The system proactively identifies and encrypts sensitive information before external output, preventing potential privacy violations in advance. By anticipating which dream content may be sensitive and applying encryption preemptively, the system maintains information completeness for analysis while establishing privacy protection before any potential misuse can occur
3Productivity
If threshold-based classification is applied to filter dream output, then productivity of dream analysis is improved, but loss of information occurs by excluding dreams below threshold values
Solution Approach 1:
The system transforms raw biological information into classified dream categories by applying threshold-based parameter changes. Dreams are reclassified based on whether their measured characteristics exceed predefined thresholds for clarity and emotional level, enabling efficient prioritization of significant dreams while maintaining a complete record of all measured data for comprehensive analysis
Data Source
AI summary
An information processing device includes: a biological information acquiring unit configured to acquire biological information of a subject; an activity calculating unit configured to calculate activity of the subject based on the biological information acquired by the biological information acquiring unit; an emotional level calculating unit configured to calculate emotional level of the subject based on the biological information acquired by the biological information acquiring unit; and a classifying unit configured to classify the biological information based on the activity which is calculated by the activity calculating unit and the emotional level which is calculated by the emotional level calculating unit.