Recommended Load Modeling From Motion Data for Skill Training
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing technologies fail to impart an appropriate load to improve user skill in motor tasks due to inability to distinguish between load-induced fluctuations and user progress, making it difficult to adjust loads effectively for skill enhancement.
Innovation Solution
A recommended load determining device utilizing an estimation model that calculates user capability based on load and motion data to determine optimal loads for skill improvement, incorporating features like displacement data, muscle activity, and success expectation values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If biometric information is used to determine control values, then automation is improved, but the ability to distinguish between load-induced fluctuations and user progress deteriorates
Solution Approach 1:
The patent segments the analysis by separating users into different groups (first group and second group) based on their response characteristics to load changes. This segmentation allows the system to identify users whose biometric fluctuations are primarily due to load changes versus those whose fluctuations indicate skill improvement, thereby resolving the contradiction between automation and measurement precision.
Solution Approach 2:
The patent changes the parameter being measured from raw biometric information to a derived parameter representing the relationship between load changes and biometric response. By analyzing how biometric information changes in response to controlled load variations, the system can distinguish between load-induced fluctuations and genuine skill progress, maintaining both automation and precision.
2Productivity
If load is increased to improve user skill, then productivity is improved, but the ability to accurately assess user capability deteriorates
Solution Approach 1:
The patent implements a dynamic load adjustment system that continuously adapts the load based on real-time assessment of user capability. By dynamically changing the load and observing the user's response, the system can maintain optimal challenge levels for skill improvement while accurately assessing capability through the relationship between load changes and biometric responses.
Solution Approach 2:
The patent employs feedback mechanisms where the system observes biometric responses to load changes and uses this information to adjust future load levels. This feedback loop enables the system to maintain accurate capability assessment while progressively increasing load to improve user skill, as the system learns from each interaction how the user responds to different load levels.
Data Source
AI summary
In a recommended load determining device (10) utilizing an estimation model (18) that outputs a parameter related to a capability of a user calculated based on load data expressing a load imparted to the user and on motion data expressing motion of a single motion unit of the user under the load, an acquisition section (12) acquires load data expressing a load imparted to a target user who is a target for determining a recommended load, and motion data expressing motion of a single motion unit of the target user under the load, and a determination section (20) determines recommended load data expressing a recommended load for the target user based on a parameter related to the capability of the target user as output from the estimation model (18) by inputting the acquired load data and the acquired motion data into the estimation model (18).