Chaos-Based Physiological Abnormality Detection
Solution Overview
Problem
Current methods for detecting physiological abnormalities, such as sleep apnea, are invasive, require large amounts of data, and struggle to accurately detect sympathetic behavior, leading to low sensitivity and high false detection rates.
Innovation Solution
A system that measures and quantifies chaos in heart rate variability combined with non-increasing parasympathetic activity to determine sympathetic activity, allowing for non-invasive detection of physiological abnormalities with high sensitivity and specificity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If large amounts of data are collected to accurately represent the heart system, then measurement precision is improved, but device complexity and loss of time increase
Solution Approach 1:
The patent transforms the heart rate variability signal into phase space using specific parameter transformations (logarithmic transformation of interbeat intervals, construction of phase space maps with specific dimensions). This transformation converts the complex temporal dynamics into a geometric representation that can be analyzed with much less data, reducing the time required for accurate characterization while maintaining measurement precision.
Solution Approach 2:
The patent applies dimensionality transformation by converting the one-dimensional time series of heart rate intervals into a two-dimensional or three-dimensional phase space representation. This dimensional transformation reveals the underlying chaotic structure more effectively, allowing accurate system representation with reduced data量 and shorter collection periods.
2Measurement precision
If large amounts of data are collected to accurately represent the heart system, then measurement precision is improved, but processing power requirements increase
Solution Approach 1:
The patent applies parameter transformations including logarithmic transformation of interbeat intervals and construction of phase space maps with specific dimensional parameters. These transformations simplify the data structure and reduce the computational complexity required for analysis, enabling accurate heart system representation with lower processing power requirements.
Solution Approach 2:
By transforming the one-dimensional time series into multi-dimensional phase space representations, the patent reduces the computational burden of analyzing heart rate variability. The geometric structure in phase space can be analyzed with less processing power compared to analyzing large amounts of raw time series data, while maintaining or improving measurement precision.
3Measurement precision
If data is collected over a protracted period to ensure accuracy, then measurement precision is improved, but reliability decreases due to time-dependent changes
Solution Approach 1:
The patent uses parameter transformations including logarithmic transformation and phase space construction to capture the essential dynamics of the heart system in a compressed representation. This allows accurate characterization to be achieved quickly, before time-dependent changes occur, thereby maintaining both measurement precision and reliability.
Solution Approach 2:
The patent performs preliminary data transformation and phase space construction during the data collection process itself, rather than requiring extensive post-processing of large datasets. This preliminary action enables accurate system representation to be established early, before significant time-dependent changes occur, thus maintaining reliability.
4Difficulty of detecting and measuring
If traditional methods are used to detect sympathetic behavior, then detection capability is improved, but ease of operation deteriorates due to invasive techniques
Solution Approach 1:
The patent uses heart rate variability as an intermediary parameter to indirectly detect sympathetic behavior. Instead of directly measuring sympathetic nerve activity through invasive techniques, the system analyzes the parasympathetic modulation of heart rate, which reflects autonomic balance. This intermediary approach maintains detection capability while eliminating invasiveness.
Solution Approach 2:
The patent replaces invasive mechanical or electrical measurement techniques with non-invasive optical or electrical sensing of heart rate variability. By substituting the measurement approach, the system achieves the same detection goal (sympathetic behavior assessment) without requiring invasive procedures, thereby improving ease of operation.
Data Source
AI summary
A method and associated apparatus combine a calculation of chaos of a quantifiable cardiac characteristic associated with a patient with a measurement of a non-increasing parasympathetic activity of the patient to detect a physiological abnormality of the patient.