Microwave Scattering Data Classification for Internal Condition Estimation
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Solution Overview
Problem
The analysis and processing of complex and large-volume microwave scattering data for diagnostics, such as medical diagnostics, require advanced tools and methods to determine relevant data and obtain reliable results, as existing techniques are inadequate for interpreting these data effectively.
Innovation Solution
A device and system that utilize microwave scattering measurement data to estimate internal conditions of enclosed volumes by performing linear or nonlinear mapping and classification using a processing unit, which projects data onto a subspace and calculates distances based on training data sets, allowing for non-invasive monitoring and diagnosis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If microwave scattering measurement data is collected for diagnostics, then non-invasive measurement capability is improved, but data complexity and volume increase making analysis difficult
Solution Approach 1:
The patent extracts and separates relevant diagnostic information from the complex microwave scattering data through classification algorithms. The system identifies and isolates key features that indicate internal conditions (such as bleeding detection) while filtering out redundant or irrelevant data components, thereby resolving the contradiction between comprehensive measurement and data complexity.
Solution Approach 2:
The patent introduces classification algorithms and processing units as intermediary components between the microwave measurement system and the diagnostic interpretation. These intermediaries transform the raw complex scattering data into classified, interpretable results, mediating between the high-volume input data and the simplified diagnostic output needed for reliable diagnosis.
2Measurement precision
If complex microwave scattering data is processed using traditional methods, then measurement capability is maintained, but analysis accuracy and reliability are insufficient
Solution Approach 1:
The patent performs preliminary classification and feature extraction on microwave scattering data before full diagnostic analysis. By pre-processing the data to identify relevant patterns and characteristics in advance, the system improves subsequent analysis accuracy while maintaining processing efficiency, as the classification step prepares the data in an optimized format for detailed examination.
Solution Approach 2:
The patent transforms the microwave scattering data by changing its representation parameters through classification algorithms. The system converts raw scattering measurements into classified categories or transformed feature spaces where diagnostic patterns become more apparent, thereby improving measurement precision without requiring proportionally increased processing resources.
3Loss of information
If detailed analysis of microwave scattering data is performed, then diagnostic information is improved, but processing time and computational resources increase
Solution Approach 1:
The patent segments the analysis process into distinct stages: initial classification of microwave scattering data, identification of key features, and detailed diagnostic interpretation. This segmentation allows the system to process information in manageable portions, maintaining completeness of diagnostic information while reducing overall processing time by handling different aspects of analysis in separate, optimized steps.
Data Source
AI summary
Example embodiments presented herein relate to solutions for analyzing and/or classifying microwave scattering data. The analyzing and/or classifying may be utilized for estimating an internal condition in an enclosed volume.