Body Analysis System Using 2D Image Processing for Composition Estimation
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Solution Overview
Problem
Current methods for estimating body composition, such as medical imaging technologies and indirect estimation methods, are either costly, invasive, or lack accuracy, particularly for heterogeneous populations.
Innovation Solution
A device and method for analyzing a body using a controller guided by electronic program instructions, which processes input representations of the body to conduct an analysis and generate outputs, utilizing a database and advanced computer vision, machine learning, and artificial intelligence models to estimate 3D body shape and associated body composition and health risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If medical imaging technologies are used to estimate body composition, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent uses 2D photographs as simplified copies of the actual body, processing these images through machine learning models to estimate body composition. This avoids the need for complex medical imaging equipment while achieving accurate results through computational analysis of visual data.
Solution Approach 2:
The patent replaces complex mechanical and physical imaging systems (CT, MRI, DXA) with a computational system using 2D image processing and machine learning algorithms. This substitution maintains measurement precision while dramatically reducing device complexity and cost.
2Device complexity
If indirect estimation methods are used to assess body composition, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent transforms traditional indirect estimation approaches by changing the input parameters from simple anthropometric measurements to detailed 2D image data. This parameter change enables the system to maintain low device complexity while significantly improving measurement precision through richer visual information and advanced image processing.
Solution Approach 2:
The patent replaces traditional mechanical measurement tools (tapes, calipers) with digital image processing and machine learning systems. This substitution maintains simplicity while improving accuracy by utilizing computational algorithms to extract body composition information from 2D photographs.
3Ease of operation
If existing methods are used for heterogeneous populations, then ease of operation is maintained, but measurement precision deteriorates due to population-specific variations
Solution Approach 1:
The patent creates a universal machine learning model that can accurately estimate body composition across diverse populations (different ages, genders, ethnicities, body types). The system maintains ease of operation through simple photo capture while achieving population-independent accuracy through training on heterogeneous datasets and implementing adaptive algorithms.
Data Source
AI summary
In one aspect, a system 10 for analysing a body 14 using a device 12 is disclosed. In one arrangement and embodiment, the device 12 comprises: a controller 18; storage 20 storing electronic program instructions for controlling the controller 18; and an input means. In one form, the controller is operable, under control of the electronic program instructions, to: receive input via that input means, the input comprising at least one representation of the body 14; process the input to conduct an analysis of the body 14 and generate an output on the basis of the analysis, the processing comprising using a database 40; and communicate the output via a display 22. In an embodiment, the output comprises an estimation of an individuals three-dimensional (3D) body shape and associated body measurements, composition and health and wellness risks from a representation comprising human imagery.