Non-Invasive Detection of Subclinical Heart Failure Using E−M Timing
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Solution Overview
Problem
Current methods for diagnosing heart failure, particularly subclinical and diastolic heart failure, are inadequate as they primarily focus on mechanical parameters and ignore the electrical and patho-electrophysiological aspects, making them insensitive and unreliable for early detection and quantification.
Innovation Solution
A non-invasive method using the Wiggers Diagram to analyze electrical and mechanical data streams, such as ECG, phonocardiogram, and Left Ventricular Pressure, to derive the Electrical Mechanical Intervals (E−M) and calculate the ratio 1/(E−M), which is linearly proportional to strain rate, enabling the creation of individual calibration curves for early detection and quantification of heart failure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If mechanical parameters (ejection fraction, myocardial strain) are used to diagnose heart failure, then the diagnostic method is simple and non-invasive, but the detection sensitivity for subclinical and diastolic heart failure is insufficient
Solution Approach 1:
The patent merges electrical parameters (ECG intervals, heart rate) with mechanical parameters (strain rate, ejection fraction) to create a comprehensive diagnostic approach. This combination allows detection of both subclinical and diastolic heart failure by integrating multiple physiological domains, thereby improving detection sensitivity without relying on a single mechanical parameter.
Solution Approach 2:
The patent introduces a new dimensional analysis by calculating the ratio of electrical to mechanical time constants (τ_elec/τ_mech). This dimensional ratio provides an additional diagnostic dimension that captures the coupling between electrical and mechanical systems, enabling detection of heart failure subtypes that mechanical parameters alone cannot identify.
2Measurement precision
If electrical and mechanical parameters are combined to detect heart failure, then detection accuracy improves, but the complexity of data processing and analysis increases
Solution Approach 1:
The patent extracts key temporal features from the complex electrical and mechanical signals, specifically the electrical time constant (τ_elec) from ECG intervals and the mechanical time constant (τ_mech) from strain rate or ejection fraction data. By isolating these critical temporal parameters and forming their ratio, the method simplifies the complex interaction between electrical and mechanical systems into a single interpretable metric that maintains high quantification accuracy.
Solution Approach 2:
The patent transforms the complex multi-parameter assessment into a simplified parameter ratio (τ_elec/τ_mech). This parameter transformation maintains the essential information about heart failure while reducing the complexity of data processing, as the ratio provides a direct measure of electromechanical coupling without requiring complex multivariate analysis.
3Adaptability or versatility
If mechanical parameters alone are used, then the measurement system is simple, but the ability to detect diastolic heart failure and subclinical disease is lost
Solution Approach 1:
The patent creates a universal diagnostic framework that can detect multiple types of heart failure (systolic, diastolic, subclinical) using a single integrated approach. The electrical-mechanical time constant ratio serves as a universal marker that adapts to different heart failure phenotypes, allowing one measurement system to address diverse diagnostic needs without requiring separate specialized tests for each condition.
Data Source
AI summary
The system and method described provides for the non-invasive detection and quantification of systolic and diastolic heart failure, including subclinical, not-yet symptomatic systolic and diastolic heart failure.