Phase Space Volumetric Objects for Cardiac Disease Assessment
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Solution Overview
Problem
Current methods for diagnosing coronary artery disease (CAD) are complex and challenging due to the variability of electrical conduction characteristics in the myocardium, making accurate non-invasive assessment difficult, especially with traditional modeling techniques failing to efficiently capture complex nonlinear variability in cardiac phase gradient signals.
Innovation Solution
The method generates phase space volumetric objects from biophysical signals, such as cardiac signals, to represent the dynamics of quasi-periodic cardiac systems, allowing for the extraction of topographic and geometric parameters indicative of CAD, using fractional subspace derivative operations and triangulation to create three-dimensional structures with color maps for visualization and feature extraction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional modeling techniques are used to analyze cardiac phase gradient signals, then the analysis process is simple, but the techniques fail to efficiently capture complex nonlinear variability in the signals
Solution Approach 1:
The patent transforms the analysis from traditional time-domain or frequency-domain modeling to phase space representation, adding geometric dimensions to the analysis. By constructing phase space volumetric objects from cardiac phase gradient signals, the method captures complex nonlinear variability through three-dimensional geometric structures that traditional two-dimensional plots cannot represent, thereby improving measurement precision without requiring overly complex mathematical models.
Solution Approach 2:
The patent changes the parameter representation by using topographic and geometric parameters (volume, surface area, curvature, fractal dimension) derived from phase space volumetric objects instead of traditional signal parameters. This parameter transformation enables efficient capture of nonlinear variability through geometric properties that naturally encode complex signal dynamics, resolving the contradiction between precision and complexity.
2Measurement precision
If phase space volumetric objects are generated to represent cardiac dynamics, then diagnostic precision is improved, but the complexity of the analysis system increases
Solution Approach 1:
The patent segments the complex diagnostic process into distinct stages: signal acquisition, phase space transformation, volumetric object construction, parameter extraction, and diagnostic interpretation. By dividing the system into modular components, each handling a specific task, the analysis system complexity is managed while maintaining high diagnostic precision through the sophisticated phase space analysis.
Solution Approach 2:
The patent creates a geometric copy or representation of the cardiac signal dynamics in phase space volumetric objects. Instead of directly analyzing the raw complex signals, the system generates three-dimensional volumetric copies that preserve the essential dynamics while enabling simpler geometric parameter extraction, thereby improving diagnostic precision without proportionally increasing system complexity.
3Manufacturing precision
If fractional subspace derivative operations are used to define vertices, then the representation of cardiac dynamics becomes more accurate, but the computational complexity increases
Solution Approach 1:
The patent applies fractional subspace derivative operations selectively to define vertices of the phase space volumetric objects, rather than computing derivatives for all data points. By applying the computationally intensive fractional differentiation only where needed to define critical geometric features (vertices), the method achieves high representation accuracy while limiting the computational power required compared to applying such operations throughout the entire signal processing pipeline.
Data Source
AI summary
The exemplified methods and systems provide a phase space volumetric object in which the dynamics of a complex, quasi-periodic system, such as the electrical conduction patterns of the heart, or other biophysical-acquired signals of other organs, are represented as an image of a three dimensional volume having both a volumetric structure (e.g., a three dimensional structure) and a color map to which features can be extracted that are indicative the presence and/or absence of pathologies, e.g., ischemia relating to significant coronary arterial disease (CAD). In some embodiments, the phase space volumetric object can be assessed to extract topographic and geometric parameters that are used in models that determine indications of presence or non-presence of significant coronary artery disease.