Emotion-Based Game Selection System
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Solution Overview
Problem
Users face difficulty in selecting a game from a large library or subscription service due to the impracticality of conventional methods like reviewing game information, especially when they have hundreds of options.
Innovation Solution
A game selection system utilizing an emotion processor to determine the user's current emotional state and matching it with emotion descriptors of games, using machine learning to predict the emotional outcome and select games that meet predetermined criteria, such as desired emotional experiences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually review game information (reviews, trailers, screenshots) to select a game, then they can assess game quality, but the process becomes impractical when facing hundreds of game options
Solution Approach 1:
The patent replaces the manual mechanical process of reviewing game information with an automated emotion recognition system. The system captures user emotional state through physiological signals (facial expressions, body language, voice tone) and automatically matches it with game emotion descriptors, eliminating the need for manual review while maintaining accurate game selection guidance
Solution Approach 2:
The patent changes the selection parameter from traditional game attributes (reviews, trailers, screenshots) to emotional parameters. By detecting user emotional state and matching it with game emotion descriptors, the system transforms the selection criterion into an emotion-based matching process, making it both accurate and time-efficient
2Reliability
If users manually review game information to assess games, then they can make informed decisions, but the process is inefficient for large game libraries
Solution Approach 1:
The patent replaces manual information review with automated emotion-based matching. The system captures user emotional state through physiological signals and automatically compares it with pre-defined game emotion descriptors, providing reliable recommendations without requiring manual assessment of hundreds of games
Solution Approach 2:
The system enables self-service game selection by automatically detecting user emotional state and generating appropriate game recommendations without requiring user intervention in the assessment process. Users simply need to be present while the system captures their emotional state and autonomously performs the matching and selection
3Measurement precision
If the system captures multiple types of physiological data (facial expressions, body language, voice tone), then emotion detection accuracy improves, but the complexity of the emotion processor increases
Solution Approach 1:
The patent merges multiple emotion detection modalities (facial expression analysis, body language recognition, voice tone detection) into a unified emotion processing system. These separate detection mechanisms work together to comprehensively capture user emotional state, with the results integrated to produce accurate emotion descriptors for game matching
Data Source
AI summary
A game selection system includes: an emotion processor configured to obtain a current emotional state of a user; a descriptor processor configured to obtain one or more emotion descriptors associated with one or more games; an evaluation processor configured to predict an emotion outcome for the user for the or each game, based upon the user's current emotional state and the one or more emotion descriptors of the respective games; and a selection processor configured to select one or more games in response to whether their respective emotion outcomes meet at least a first predetermined criterion.