Motion Data Training Assessment Using Intensity and Volume
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Solution Overview
Problem
Current training assessment methods rely solely on training amount, such as time and distance, providing unilateral assessment information that fails to accurately reflect a user's training status, leading to poor accuracy and effectiveness.
Innovation Solution
A training assessment method that determines an achievement rate and a completion rate based on motion data during a preset training plan, characterizing training intensity and volume, respectively, to provide a comprehensive assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If training assessment is based only on training amount (time and distance), then the assessment method is simple, but the assessment accuracy and effectiveness deteriorate due to unilateral assessment information
Solution Approach 1:
The patent segments the training assessment into two distinct dimensions: achievement rate (training intensity) and completion rate (training volume). This segmentation allows comprehensive assessment while maintaining clear calculation methods for each dimension, resolving the contradiction between simplicity and accuracy.
Solution Approach 2:
The patent transitions from one-dimensional assessment (training amount only) to two-dimensional assessment by introducing the achievement rate dimension based on motion data. This dimensional expansion enables more accurate training status evaluation without excessive complexity.
2Measurement precision
If motion data is collected and processed to determine achievement rate and completion rate, then training status assessment accuracy improves, but the device complexity and data processing requirements increase
Solution Approach 1:
The patent extracts only the essential motion data parameters needed for achievement rate calculation from the complex motion data stream. This extraction approach maintains high assessment accuracy while reducing processing complexity by focusing on critical data points.
Solution Approach 2:
The system automatically processes motion data to calculate both achievement rate and completion rate without requiring manual intervention. This self-service approach handles the increased data processing requirements through automated algorithms, maintaining accuracy while managing system complexity.
Data Source
AI summary
A training assessment method includes obtaining motion data of a user when executing a preset training plan, and determining an achievement rate and a completion rate corresponding to the user based on the motion data and the preset training plan. The achievement rate corresponding to the user characterizes an achievement situation of the user in terms of training intensity, and the completion rate corresponding to the user characterizes a completion situation of the user in terms of training volume. The method further includes determining an assessment result based on the achievement rate corresponding to the user and the completion rate corresponding to the user.