Biometric Task Load Control Using Emotion Synchronization
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Solution Overview
Problem
Existing technologies fail to make tasks enjoyable for multiple individuals performing the same activity by inferring relationships between them.
Innovation Solution
An information processing device that computes synchronization and emotion sharing degrees from biometric data to adjust task difficulty, using a load controlling section to maintain, increase, or decrease task load based on these metrics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the task load is increased to improve engagement, then user motivation is enhanced, but user fatigue and dropout rate increase
Solution Approach 1:
The task load is made dynamically adjustable based on real-time biometric feedback. The system continuously monitors synchronization degrees and emotion sharing degrees, and automatically adjusts task parameters to maintain optimal engagement levels without causing excessive fatigue. This dynamic adjustment allows the system to respond to changing user states and prevent harmful effects before they occur.
Solution Approach 2:
The system implements a closed-loop feedback mechanism where biometric information from multiple users is continuously collected, processed to calculate synchronization and emotion sharing degrees, and used to adjust task load. This feedback loop enables real-time optimization of task difficulty to maintain engagement while preventing fatigue accumulation.
2Ease of operation
If the task load is decreased to reduce fatigue, then user comfort is improved, but task engagement and motivation decrease
Solution Approach 1:
The system dynamically adjusts task load based on real-time biometric feedback rather than using fixed difficulty levels. When users show signs of fatigue through biometric changes, the system automatically reduces load to maintain comfort. When users are engaged and performing well, the system increases load to maintain motivation. This dynamic approach allows the system to optimize both comfort and engagement simultaneously.
Solution Approach 2:
The system changes task parameters (difficulty, complexity, intensity) based on calculated synchronization and emotion sharing degrees. By adjusting these parameters in response to biometric feedback, the system can maintain task engagement at optimal levels while preventing user fatigue, thus resolving the contradiction between comfort and engagement.
3Manufacturing precision
If individualized task loads are assigned to accommodate different skill levels, then each user's performance is optimized, but system complexity increases
Solution Approach 1:
The system merges individual task management into a unified group task framework. Instead of managing completely separate individual tasks, the system creates a shared task experience where biometric feedback from all users is aggregated to calculate group synchronization and emotion sharing degrees. This unified approach allows individualized adaptation without requiring separate complex control systems for each user.
Solution Approach 2:
The system uses automated biometric analysis and AI-based calculations to determine optimal task loads for each user based on their real-time state and group synchronization levels. This self-service approach eliminates the need for manual configuration or complex user input, allowing the system to automatically optimize individual performance within the group context while keeping the interface simple.
Data Source
AI summary
There is provided an information processing device 10 including: a synchronization degree computing section 103 computing, from time-series biometric information formed from plural physiological indices and of each of plural users who are carrying out a same task, a degree of synchronization of the time-series biometric information of the users; an emotion sharing degree computing section 104 computing a degree of sharing emotion among the respective users by using the degree of synchronization computed by the synchronization degree computing section 103; and a load controlling section 105 controlling changes in load of the task on the basis of a degree of achievement relating to an extent of achievement of each user with respect to the task, and the degree of sharing emotion of the respective users computed by the emotion sharing degree computing section 104.