Automated ECG Signal Change Analysis for Wide Complex Heart Beat Classification
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Solution Overview
Problem
Current methods for differentiating wide complex tachycardias (WCTs) into ventricular tachycardia (VT) and supraventricular wide complex tachycardia (SWCT) using 12-lead electrocardiograms (ECGs) are unreliable, especially for less experienced interpreters, due to their manual nature and limited ability to estimate VT probability.
Innovation Solution
A computerized method that analyzes ECG, electrogram (EMG), and vectorcardiogram (VCG) data to automatically classify wide complex heart beats by determining signal changes between WCT and baseline waveforms, using percent amplitude and time-voltage area changes to indicate whether the beat is of ventricular or supraventricular origin, thereby providing a VT probability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual ECG interpretation methods are used, then diagnostic capability is available, but reliability and accuracy deteriorate when used by less experienced interpreters
Solution Approach 1:
The patent replaces manual mechanical interpretation of ECG criteria with an automated computerized system that calculates signal changes and generates VT probability estimates. This substitution eliminates the dependency on interpreter expertise while maintaining diagnostic capability, directly resolving the contradiction between reliability and ease of operation.
2Measurement precision
If conventional ECG interpretation methods are used, then differentiation of VT and SWCT is attempted, but measurement precision and diagnostic accuracy are insufficient
Solution Approach 1:
The patent transforms the interpretation approach by changing from qualitative manual assessment to quantitative measurement of signal changes (amplitude, duration, morphology) and calculating VT probability as a precise parameter. This parameter change enables accurate differentiation while the automated calculation handles the complexity, resolving the contradiction between measurement precision and device complexity.
3Productivity
If automated computerized classification is implemented, then productivity and diagnostic speed are improved, but the system requires complex processing capabilities
Solution Approach 1:
The patent applies partial action by focusing on specific key parameters (signal change amplitude, duration, morphology) rather than attempting to analyze all ECG features. This selective approach enables automated processing and high diagnostic throughput while keeping computational complexity manageable through targeted analysis of the most discriminative features.
Data Source
AI summary
An apparatus and computerized method of classifying a wide complex heart beat(s) comprising: providing a computing device having an input/output interface, one or more processors and a memory; receiving one or more wide complex heart beat waveform amplitudes and/or time-voltage areas, and one or more baseline heart beat waveform amplitudes and/or time-voltage areas via the input/output interface or the memory; determining a signal change between the wide complex heart beat waveform amplitudes and/or time-voltage areas and the baseline heart beat waveform amplitudes and/or time-voltage areas using the one or more processors; and providing the signal change via the input/output interface, wherein the signal change provides an indication whether the wide complex heart beat(s) is from a ventricular source or a supraventricular aberrant condition.