Mobile Spirometry for Visceral Fat Estimation
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Solution Overview
Problem
Existing methods for determining body composition, such as weight and skinfold calipers, are invasive, expensive, and do not accurately reflect visceral fat levels, which are crucial for assessing obesity and related health risks.
Innovation Solution
A mobile device functions as a spirometer to measure forced breathing parameters, including lung function and blood oxygenation, to estimate body composition, particularly visceral fat, using spirometry tests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods like weight measurement and skinfold calipers are used to assess body composition, then the assessment can be performed with simple equipment, but the accuracy in detecting visceral fat and obesity is insufficient
Solution Approach 1:
The patent replaces mechanical measurement systems (skinfold calipers, weight scales) with a physiological measurement system based on pulmonary function testing. The mobile device captures acoustic signals from breathing patterns and processes them algorithmically to estimate body composition, substituting direct mechanical contact with remote acoustic sensing and computational analysis.
Solution Approach 2:
The patent introduces pulmonary function parameters as an intermediary measurement that indirectly reflects body composition. Instead of directly measuring visceral fat, the system measures breathing characteristics (flow rates, volumes, patterns) that are influenced by visceral fat levels, using these intermediate physiological parameters as proxies for body composition assessment.
2Measurement precision
If advanced body composition analysis methods are used to accurately measure visceral fat, then the measurement precision improves, but the cost and accessibility of the method increases
Solution Approach 1:
The patent utilizes a mobile device, which is a common, inexpensive, and readily available consumer electronic product, to perform body composition analysis. Instead of requiring expensive specialized medical equipment, the system leverages the microphone and processing capabilities of smartphones or tablets, making the technology accessible to the general population without significant additional cost.
Solution Approach 2:
The system enables individuals to perform their own body composition assessment using their personal mobile device. The mobile device captures the breathing signals, processes the data through embedded algorithms, and provides the analysis results without requiring professional medical personnel or specialized laboratory facilities, thus eliminating service delivery costs.
3Measurement precision
If invasive methods are used to measure body composition, then measurement precision may improve, but the ease of operation and user comfort deteriorates
Solution Approach 1:
The patent replaces invasive mechanical contact methods (skinfold calipers requiring pinching of skin, tape measures requiring circumferential measurements) with non-contact acoustic sensing. The mobile device's microphone captures breathing sounds from a distance, eliminating the need for physical contact with the user's body and thereby improving comfort while maintaining measurement capability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Provides a non-invasive, cost-effective method for accurately assessing body composition, including visceral fat, which can help prevent lifestyle-related diseases by identifying obesity early.
Implementation Method 1
a microphone associated with a mobile device receives the forced breath
Data Source
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AI summary
A method, electronic device, and non-transitory computer readable medium for estimating body composition are provided. The method includes receiving a set of forced breath data from an electronic device. The method also includes deriving a flow rate based on the set of forced breath data. The method further includes determining a body composition based on the derived flow rate of the set of forced breath data.