Trained Model Personalizing Walking Instructions by Age
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing walking instruction systems fail to provide personalized training content and advice tailored to individual users, making it difficult to improve walking ability effectively.
Innovation Solution
An information processing device that acquires target person information, including age, exercise evaluation data, and stores a trained model to estimate exercise improvements, outputting personalized instruction reports based on age-specific analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a footprint image is merely displayed in accordance with a walking index, then the system is simple to operate, but it is not possible to output training content or advice on training suitable for each target person
Solution Approach 1:
The system introduces feedback loops where exercise evaluation information is continuously collected, processed through the trained model, and used to generate updated instruction content. This allows the system to adapt and personalize training content based on individual progress and responses, transforming a static display system into a dynamic, personalized coaching system.
Solution Approach 2:
The trained model enables the system to automatically generate personalized training content and advice without requiring manual intervention. The system serves itself by using the input data (target person information and exercise evaluation information) to automatically produce tailored instruction reports, eliminating the need for manual customization while maintaining high personalization levels.
2Device complexity
If generic walking instruction is provided without personalized analysis, then the device complexity is reduced, but it is difficult to improve walking ability of the target person
Solution Approach 1:
The system performs preliminary action by pre-training the model with extensive data before actual use. The trained model stores pre-computed relationships and patterns that enable rapid, accurate personalization during operation. This preliminary preparation allows the system to deliver reliable, personalized walking improvement advice without complex real-time processing.
Solution Approach 2:
The system changes parameters by inputting specific target person information (age, gender, height, weight, BMI, disease) and exercise evaluation information into the trained model. These parameter inputs trigger the model to generate customized instruction content, transforming generic instructions into personalized guidance that reliably improves walking ability based on individual characteristics.
3Adaptability or versatility
If personalized training content is generated using a trained model, then the adaptability to individual users is improved, but the device complexity increases
Solution Approach 1:
The system uses copying by storing the trained model as a reusable computational template. Once the model is trained with extensive data, it can be copied and deployed to generate personalized content for multiple users without retraining. This allows high adaptability to individual users while keeping the operational system relatively simple, as the complex learning process is captured in the reusable model copy.
Data Source
AI summary
Provided is an information processing device including a target person information acquisition unit configured to acquire target person information including age information indicating an age of a target person, an exercise evaluation information acquisition unit configured to acquire exercise evaluation information about evaluation of an exercise of the target person, a storage unit configured to store a trained model in which, when the target person information and the exercise evaluation information are input, evaluation of exercise information of the target person is estimated to be improved, and instruction content based on the age information is output, and a report output unit configured to input the target person information and the exercise evaluation information to the trained model and output an instruction report including the instruction content output from the trained model.