Time-Frequency ECG Maps for Myocardial Ischemia Detection

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Solution Overview

Problem

Conventional electrocardiogram (ECG) testing often fails to detect developing abnormal heart conditions promptly, leading to misdiagnosis, as it primarily relies on time-domain signals that do not effectively visualize or quantify heart conditions like myocardial ischemia, limiting the information provided and its intuitiveness.

Innovation Solution

The system converts ECG signals into two-dimensional time-frequency maps through transforms like wavelet or Fourier analysis, allowing for visualization and quantification of heart conditions by analyzing repolarization measures and indices, which are then displayed in a user-friendly format to aid diagnosis.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If conventional ECG testing using time-domain signals is used, then the testing method is simple and widely applicable, but it fails to detect developing abnormal heart conditions promptly and provides limited diagnostic information

Engineering Contradiction:

Improvedetection accuracy of abnormal heart conditionsVSAvoidinformation provided by ECG

Core Design Contradiction:

Measurement precisionVSLoss of information

Solution Approach 1:

The patent transforms one-dimensional time-domain ECG signals into two-dimensional time-frequency maps using wavelet transform or short-time Fourier transform. This dimensional transformation reveals hidden patterns and features in the ECG data that are not visible in traditional time-domain representations, enabling detection of developing abnormal heart conditions like myocardial ischemia with greater precision while preserving all original information.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

2Measurement precision

If time-frequency transforms are applied to ECG signals to enhance diagnostic capabilities, then detection accuracy improves, but computational complexity and processing requirements increase

Engineering Contradiction:

Improvedetection accuracy of heart conditionsVSAvoidsignal processing complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent divides the ECG signal into overlapping segments and applies wavelet transform or short-time Fourier transform to each segment individually. This segmentation approach reduces the computational burden of processing entire long ECG recordings at once, while still capturing transient abnormalities. The segmented processing allows for efficient generation of time-frequency maps that maintain high diagnostic accuracy.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces time-frequency maps as an intermediary representation between the raw ECG signal and the final diagnostic interpretation. These maps serve as a bridge that transforms complex temporal patterns into visualizable frequency-time distributions, making it easier for both automated systems and clinicians to identify abnormal patterns without directly analyzing raw ECG waveforms.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Loss of information

If quantitative repolarization measures are calculated from time-frequency maps, then diagnostic information increases, but processing time and computational resources increase

Engineering Contradiction:

Improvediagnostic information providedVSAvoidprocessing time

Core Design Contradiction:

Loss of informationVSLoss of time

Solution Approach 1:

The patent performs wavelet transform or short-time Fourier transform to generate time-frequency maps as a preliminary step before calculating repolarization measures. By pre-processing the ECG signals into time-frequency representations, the system creates a structured format that facilitates efficient extraction of quantitative repolarization features. This preliminary transformation organizes the data in a way that accelerates subsequent measurement calculations.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent extracts multiple repolarization measures (such as repolarization time, amplitude, and morphology) from the time-frequency maps by analyzing specific frequency bands and time intervals. By changing the parameter space from time-domain voltage measurements to frequency-domain energy distributions, the system efficiently captures comprehensive repolarization characteristics that provide rich diagnostic information with optimized processing requirements.

Inventive Principle:

Principle #35Parameter changes

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach enhances diagnostic capabilities by visualizing information not discernible in traditional ECGs, improving the detection of conditions like myocardial ischemia and providing quantitative metrics for better assessment of heart function.

Implementation Method 1

converting the one or more electrocardiograms by time-frequency transform into one or more respective two-dimensional time-frequency maps

Methodology Applied

Scientific EffectWavelet transform:

Implementation Method 2

transforms like wavelet or Fourier analysis

Methodology Applied

Scientific EffectFourier analysis:

Data Source

PatentUS11445968B2Quantitative heart testing

Publication Date: 2022.09.20 HEARTSCIENCES INC

AI summary

Heart condition and function can be quantified using repolarization measures and/or repolarization indices derived from a time-frequency transform of an electrocardiogram, e.g., based on points in time associated with the T wave. The electrocardiograms, time-frequency maps derived therefrom, and/or indices obtained by analysis of the time-frequency maps and electrocardiograms may be assembled into a user interface. Further embodiments are described.