AI Insole Manufacturing with Pressure-Based 3D Interpolation
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Solution Overview
Problem
Existing methods for designing and manufacturing custom insoles are difficult to automate, particularly due to the complexity of adapting to user anatomy, and current automation techniques involve long processing times and are not user-friendly.
Innovation Solution
A method using an interpolating surface and anchor coordinates for 3D characterization, incorporating computer vision and AI algorithms, allows for automated insole design and production, enabling efficient and fast design adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual annotation of pressure measurements with curves is used, then expert control and customization are improved, but automation capability deteriorates
Solution Approach 1:
The patent replaces manual mechanical annotation processes with automated computer vision and machine learning systems. The system automatically processes pressure measurements and generates insole designs without requiring expert manual curve drawing, thereby maintaining design quality while enabling full automation.
Solution Approach 2:
The system enables self-service automation where the computer vision algorithms and machine learning models automatically perform tasks previously requiring expert intervention. The system serves itself by autonomously converting pressure measurements into actionable design parameters without continuous human input.
2Extent of automation
If brute force application of computer techniques is used, then automation is improved, but processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-training machine learning models and establishing decision frameworks before actual insole design. The system pre-processes pressure measurement data into standardized formats and pre-loads material databases, so that when design is needed, the automated system can quickly generate results without extensive real-time computation.
Solution Approach 2:
The system changes parameters by transforming raw pressure measurement data into standardized design parameters through machine learning. This parameter transformation enables the system to work with optimized data structures that reduce computational complexity and accelerate processing while maintaining automation.
3Extent of automation
If black box application of computer techniques is used, then automation is improved, but interpretability for operators deteriorates
Solution Approach 1:
The patent implements feedback mechanisms where the system provides intermediate results and decision rationales to operators during the design process. The machine learning model outputs are accompanied by explanatory information that helps operators understand the automated decisions, maintaining interpretability while preserving automation benefits.
Solution Approach 2:
The system introduces an intermediary layer between the black box algorithms and the operator. This intermediary presents processed information in an interpretable format, translating complex algorithmic outputs into understandable design recommendations that operators can review and adjust if needed.
Data Source
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Figure 2B~3A
Figure 3B
AI summary
The present invention provides, inter alia, a method for designing an insole, comprising receiving a measurement of a foot sole associated with pressure, said measurement preferably being obtained by placing a load on a measurement surface; receiving a sole profile; determining, based on said measurement, one or more anatomical zones; determining, based on said anatomical zones, a foot profile comprising a major axis; determining, at least based on said foot profile and said anatomical zones, an interpolating surface; aligning the interpolating surface with the sole profile, to obtain an aligned 3D profile; generating, based on said aligned 3D profile, an instruction for manufacturing the insole; wherein said determining of the interpolating surface is realized according to a 3D characterization according to respective positions (y1, y2) on said major axis; wherein said determining of the interpolating surface comprises calculating, based on said foot profile and said anatomical zones, a plurality of at least two anchor coordinates (d0-d3) each lying in a respective cross-section corresponding to said respective positions (y1, y2), and calculating, based on said at least two anchor coordinates (d0-d3), an interpolating surface.