Foot Shape Prediction Using Loaded State Data
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Solution Overview
Problem
Existing methods for measuring the shape of a person's foot in an unloaded state are time-consuming, require expert skills, and are not suitable for retail environments, as they involve casting plaster bandages and require specific spaces, making it difficult to obtain accurate measurements.
Innovation Solution
A prediction device and system that acquires measurement data of a foot in a loaded state and uses pre-calculated sample data from both loaded and unloaded states to predict the foot shape in an unloaded state, allowing for the production of custom shoe insoles without the need for expert skills or extensive space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If plaster bandage method is used to measure foot shape in unloaded state, then accurate measurement can be obtained, but measurement time becomes long and expert skills are required
Solution Approach 1:
The patent pre-calculates and stores the relationship between loaded and unloaded foot shapes for multiple sample persons before actual measurement. This preliminary preparation creates a prediction model that can quickly transform loaded state measurements into unloaded state predictions without requiring time-consuming plaster bandage procedures during the actual measurement process.
Solution Approach 2:
The patent creates a virtual copy of the unloaded foot shape by using measurement data from the loaded state and applying pre-calculated prediction information. Instead of directly measuring the unloaded foot shape with plaster, the system generates an accurate digital replica through data processing and prediction algorithms.
2Measurement precision
If plaster bandage method is used to measure foot shape in unloaded state, then accurate measurement can be obtained, but device complexity and space requirements increase
Solution Approach 1:
The patent replaces the mechanical plaster bandage system with an information processing system. Instead of using physical plaster materials and manual casting procedures, the system uses sensors to capture foot shape data in the loaded state and applies computational algorithms to predict the unloaded state, significantly reducing device complexity and space requirements.
Solution Approach 2:
The patent introduces prediction information as an intermediary element that connects the loaded state measurement data with the unloaded state foot shape. This intermediary data layer allows the system to infer unloaded characteristics without directly interacting with the foot in the unloaded state, simplifying the measurement process.
3Manufacturing precision
If measurement of both loaded and unloaded foot shapes is performed in store, then accurate shoe insole production is enabled, but measurement time becomes long
Solution Approach 1:
The patent extracts only the necessary measurement data from the loaded state foot shape and uses pre-stored prediction information to derive the unloaded state characteristics. This extraction approach eliminates the need to perform separate unloaded state measurements, reducing the total measurement time while maintaining the accuracy needed for custom shoe insole production.
Solution Approach 2:
The patent performs the complex analysis of the relationship between loaded and unloaded foot shapes in advance during the sample collection phase. This preliminary action creates a ready-to-use prediction database that enables rapid determination of unloaded foot shape characteristics during actual store measurements, significantly reducing on-site measurement time.
Data Source
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AI summary
A prediction device (1) includes: a communication device (16) that acquires measurement subject data including measurement data of a shape of a foot of a measurement subject person in a loaded state; a storage (13) that stores first sample data in the loaded state and second sample data in an unloaded state, the first sample data and the second sample data being calculated from measurement data of foot shapes of a plurality of samples, the samples being identical both in the loaded state and the unloaded state; and a processor (11) that predicts the shape of the foot of the measurement subject person in the unloaded state. The processor calculates a difference between the measurement subject data and the first sample data, and predicts the shape of the foot of the measurement subject person in the unloaded state based on the difference and the second sample data.