Activity State Evaluation System for Comprehensive Skill Training
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Solution Overview
Problem
Conventional methods for evaluating activity states in wearable devices often focus on a single activity, leading to biased skill improvement and difficulty in comprehensively enhancing skills related to multiple activities.
Innovation Solution
An information processing method that evaluates a first activity state and, upon receiving evaluation, executes a second event to evaluate a distinct activity state, allowing for comprehensive skill improvement by alternating between different activity states during training.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If only one activity state is evaluated, then the evaluation process is simple, but the skill improvement is biased and not comprehensive
Solution Approach 1:
The evaluation process is segmented into multiple independent events, each targeting a different activity state. The system divides the comprehensive skill improvement goal into separate evaluation components (first activity state evaluation event, second activity state evaluation event), allowing each event to focus on specific skills while collectively achieving comprehensive improvement.
Solution Approach 2:
The evaluation system is designed with multi-functionality to handle different activity states through a unified platform. The same evaluation infrastructure supports multiple activity types (first activity, second activity), enabling comprehensive skill improvement across diverse activities without requiring separate specialized systems for each activity state.
2Adaptability or versatility
If multiple activity states are evaluated sequentially, then comprehensive skill improvement is achieved, but the training period may be extended
Solution Approach 1:
The system implements periodic evaluation events where the first evaluation event for the first activity state and the second evaluation event for the second activity state are executed in an alternating or structured sequence. This periodic structure allows comprehensive skill assessment while maintaining a manageable training rhythm, preventing excessive extension of the overall training period.
3Productivity
If intensive training is conducted to improve skills quickly, then productivity increases, but the risk of injury increases due to burden
Solution Approach 1:
Each evaluation event is designed with local quality optimization, where the first evaluation event targets specific aspects of the first activity state while the second evaluation event targets different aspects of the second activity state. This localized approach allows intensive improvement in specific skill areas without overloading the subject, thereby maintaining high productivity while reducing overall injury risk through balanced distribution of training burden.
Data Source
AI summary
An information processing method causes a computer to: execute a first event for evaluating a first activity state of a subject when the subject is performing a first activity; determine whether the subject receives the evaluation in the first event; and execute a second event for evaluating a second activity state different from the first activity state, the second activity state being an activity state of the subject when the subject is performing a second activity, at least on a condition that it is determined that the subject receives the evaluation in the first event.