Adaptive Exercise Advice System Preventing User Fatigue
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing information processing devices for providing sports advice to users generate advice based on user proficiency, leading to repetitive advice if proficiency remains unchanged, which may be insufficient and demotivating for users.
Innovation Solution
An information processing device with a goal setting unit, advice generation unit, motivation estimation unit, and evaluation unit, which sets exercise goals, generates advice, estimates user motivation, and evaluates motivation based on exercise data, adjusting advice accordingly to maintain user engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If advice is generated based on user proficiency, then the advice is personalized to user capability, but the advice becomes repetitive and insufficient when proficiency remains unchanged
Solution Approach 1:
The patent applies dynamics by making the advice generation system adaptive and responsive to changing user states. The advice generation unit dynamically adjusts advice content based on real-time motivation estimation, transforming a static proficiency-based system into a dynamic one that evolves with user motivation levels, thereby preventing advice repetition and maintaining user engagement.
Solution Approach 2:
The patent implements feedback by introducing a closed-loop system where user motivation is continuously estimated, evaluated, and fed back to the advice generation unit. This feedback mechanism allows the system to adjust advice based on user response and motivation changes, ensuring advice remains varied and relevant rather than repetitive, thus resolving the contradiction between personalization and variety.
2Stability of the object's composition
If the same advice is continuously generated based on unchanged proficiency, then the system maintains consistency, but user motivation decreases due to advice fatigue
Solution Approach 1:
The patent applies periodic action by introducing regular motivation estimation and evaluation cycles. The system periodically reassesses user motivation and adjusts advice accordingly, creating rhythmic variations in advice delivery that prevent monotony and advice fatigue while maintaining overall system stability and consistency in its adaptive approach.
Solution Approach 2:
The patent implements parameter changes by modifying advice generation based on motivation parameter variations. When motivation levels change, the system adjusts advice parameters (content, timing, frequency) to prevent advice fatigue, thereby maintaining consistency in the adaptive mechanism while varying the actual advice delivered to keep users engaged.
3Adaptability or versatility
If motivation estimation and evaluation functions are added to the system, then advice variety and user engagement improve, but device complexity increases
Solution Approach 1:
The patent applies universality by designing the information processing device to perform multiple functions within integrated units. The advice generation unit simultaneously handles advice creation and motivation-based adaptation, while the evaluation unit consolidates motivation assessment and advice adjustment functions, reducing overall system complexity despite enhanced personalization capabilities.
Solution Approach 2:
The patent implements merging by combining related functions into unified components. The motivation estimation unit and evaluation unit work as an integrated subsystem that feeds into the advice generation unit, creating a cohesive structure that reduces complexity compared to separate independent modules, while still achieving sophisticated advice personalization based on motivation analysis.
Data Source
AI summary
An information processing device includes a goal setting unit configured to set a first goal for an exercise of a subject, an advice generation unit configured to generate a first advice for the first goal, an output unit configured to output the first goal and the first advice, a motivation estimation unit configured to estimate a motivation of the subject, and an evaluation unit configured to evaluate a motivation of the subject for the first goal. The advice generation unit generates a second advice different from the first advice based on a result of the evaluation by the evaluation unit, and the output unit outputs the second advice.