Nonlinear Analysis of Physiological Patterns for Disease Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for diagnosing psychiatric and physical conditions fail to effectively capture the nonlinear dynamics of biological systems, leading to inadequate understanding and treatment of maladaptive patterns and diseases.
Innovation Solution
The use of nonlinear mathematical tools and physiological measures to track spatial-temporal patterns in brain and body functions, allowing for the identification of healthy and pathological states by analyzing heart rate variability, movement variability, and other physiological parameters over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If linear mathematical tools are used to analyze physiological data, then the analysis is simple and computationally efficient, but the measurement precision and accuracy of biological system states deteriorate because biological systems are inherently nonlinear
Solution Approach 1:
The patent changes the mathematical parameters from linear to nonlinear tools. Specifically, it employs nonlinear dynamic analysis methods including correlation dimension, entropy measures, and attractor reconstruction to analyze physiological time series data. This parameter change enables accurate characterization of the nonlinear behavior inherent in biological systems, resolving the contradiction between measurement accuracy and analytical simplicity.
2Loss of information
If nonlinear mathematical tools are used to track spatial-temporal patterns, then the understanding of adaptive and maladaptive patterns improves, but the computational requirements and data processing complexity increase
Solution Approach 1:
The patent extracts key nonlinear dynamic parameters from complex physiological time series data. By calculating specific metrics such as correlation dimension, entropy, and attractor characteristics, it extracts essential information about system behavior without requiring full reconstruction of the underlying nonlinear dynamics. This extraction approach maintains information completeness while reducing computational burden.
Solution Approach 2:
The patent creates simplified representations (copies) of the complex nonlinear system behavior through phase space reconstruction and attractor analysis. Instead of directly analyzing the full complexity of nonlinear differential equations governing physiological systems, it creates lower-dimensional copies that preserve essential dynamic characteristics, making the analysis computationally tractable while retaining information about adaptive and maladaptive patterns.
3Reliability
If physiological parameters are monitored continuously over time to capture nonlinear dynamics, then the detection of early disease stages and maladaptive patterns improves, but the quantity of data collected and processing time increase
Solution Approach 1:
The patent performs preliminary nonlinear analysis of physiological data to identify early markers of disease before full pathological patterns emerge. By continuously monitoring and analyzing nonlinear dynamic parameters such as changes in correlation dimension and entropy, the system detects early deviations from healthy system behavior, enabling early intervention while minimizing the total quantity of data that must be processed and stored.
Data Source
AI summary
A method, apparatus and software for diagnosing the state or condition of a human, animal or other living thing, which always generates physiological modulating signals having temporal-spatial organization, the organization having dynamic patterns whose structure is fractal, involving the monitoring of at least one physiological modulating signal and obtaining a set of temporal-spatial values of each of said physiological modulating signals, and processing the respective temporal-spatial values using linear and nonlinear tools to determine the linear and nonlinear characteristics established for known criteria to determine the state or condition of the person, being or living things, and to use this data for diagnosis, tracking, and treatment and developmental issues.