Mental State Data Sharing Across Social Networks
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Solution Overview
Problem
Current technologies face challenges in accurately and automatically evaluating mental states of individuals, particularly in the virtual world, as human emotions can be complex and difficult to summarize, and existing methods lack effective means for real-time or near-real-time analysis and communication of emotional data across social networks.
Innovation Solution
A computer-implemented method for collecting and analyzing mental state data, including facial image data and physiological data, to produce mental state information that can be shared across social networks, using web-enabled devices for data collection, analysis, and sharing, with features like webcam-based facial data capture and biosensor integration for real-time processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated mental state analysis is implemented using web-enabled devices, then productivity and real-time analysis capability are improved, but device complexity and data processing requirements increase
Solution Approach 1:
The patent segments the mental state analysis system into multiple web-enabled devices that can independently collect and process data. Each device performs localized analysis of facial images and physiological data, then shares results across the network. This segmentation distributes the computational burden, improving real-time analysis capability while managing device complexity through modular architecture.
Solution Approach 2:
The patent employs web-enabled devices with multi-functionality, using standard webcams and biosensors for both data collection and initial processing. These devices serve multiple purposes: capturing facial images, collecting physiological data, performing local analysis, and sharing results. This universal approach improves productivity by leveraging existing infrastructure while managing complexity through standardized multi-functional components.
2Measurement precision
If multiple data sources (facial images, physiological data) are integrated for comprehensive mental state analysis, then measurement precision is improved, but device complexity and data integration requirements increase
Solution Approach 1:
The patent merges multiple data sources including facial images from webcams and physiological data from biosensors into a unified mental state analysis system. By combining these diverse data types and processing them through integrated algorithms on web-enabled devices, the system achieves comprehensive and precise mental state evaluation. The merging of data sources improves measurement precision while the web-based architecture manages integration complexity through standardized interfaces.
3Loss of information
If mental state data is shared across social networks, then information communication and empathetic interaction are improved, but loss of information and privacy concerns increase
Solution Approach 1:
The patent extracts and shares only the essential mental state information (emotional states, moods) across social networks while leaving out sensitive personal data. By extracting only the necessary psychological indicators for communication and interaction, the system improves information sharing effectiveness while minimizing privacy risks. The extracted mental state data is sufficient for empathetic interaction without exposing underlying personal information.
Data Source
AI summary
Facial image data of an individual is collected of the individual to provide mental state data using a first web-enabled computing device. The mental state data is analyzed to produce mental state information using a second web-enabled computing device. The mental state information is shared across a social network using a third web-enabled computing device. The mental state data is also collected from the individual through capture of sensor information. The mental state data is also collected from the individual through capture of audio data. The individual elects to share the mental state information across the social network. The mental state data may be collected over a period of time and analyzed to determine a mood of the individual. The mental state information is translated into a representative icon for sharing, which may include an emoji. An image of the individual is shared along with the mental state information.