Cardiac Arrhythmia Detection Using Waveform Area Analysis
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Solution Overview
Problem
Current cardiac arrhythmia detection and characterization systems are subjective, time-consuming, and require extensive medical expertise, failing to accurately quantify the severity of myocardial ischemia and infarction, particularly with intra-cardiac electrograms, and often result in false alarms and delayed treatment.
Innovation Solution
A system that analyzes cardiac electrophysiological signals by calculating time-spatial, area, and energy ratios between repolarization and depolarization portions within a heart beat for real-time monitoring, using pattern analysis and artificial neural networks to differentiate cardiac arrhythmias, characterize pathology, and predict life-threatening events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If known waveform morphology parameter analysis systems are used for cardiac arrhythmia monitoring, then cardiac arrhythmia detection is achieved, but the analysis becomes subjective and time-consuming requiring extensive medical expertise
Solution Approach 1:
The patent transforms the analysis from subjective waveform morphology assessment to objective quantitative parameter measurement. It introduces specific measurable parameters including area under the waveform at predetermined amplitude levels, time-spatial ratios, area ratios, and energy ratios. These parameter changes enable automated, objective analysis that reduces dependence on medical expertise while maintaining detection reliability.
Solution Approach 2:
The patent replaces the manual, expert-dependent waveform interpretation process with an automated computational system. The signal processor automatically calculates area ratios, time-spatial ratios, and energy ratios from the ECG signal, substituting the mechanical process of expert visual analysis with an automated electronic system that provides consistent, objective results without requiring extensive medical expertise.
2Reliability
If ST segment voltage deviation analysis is used for myocardial ischemia detection, then ischemia event detection is achieved, but quantitative characterization of severity is not provided
Solution Approach 1:
The patent extends the analysis from single-dimensional ST segment voltage deviation to multi-dimensional parameter assessment. It introduces area under the waveform at multiple predetermined amplitude levels, time-spatial ratios comparing different signal portions, area ratios, and energy ratios. This dimensional expansion provides comprehensive quantitative characterization of both ischemia detection and severity assessment.
Solution Approach 2:
The patent segments the ECG waveform analysis into multiple amplitude level partitions, dividing the signal into distinct portions for separate area calculation. By segmenting the waveform at predetermined amplitude levels and calculating area ratios between different segments, the system provides detailed quantitative information about ischemia severity that goes beyond simple voltage deviation measurement.
3Reliability
If known signal analysis methods are used, then cardiac rhythm monitoring is achieved, but precise localization of malfunction and severity determination cannot be performed
Solution Approach 1:
The patent applies local quality analysis by examining specific portions of the ECG signal with distinct characteristics. It identifies and analyzes the QRS complex portion and T wave portion separately, calculating area ratios and time-spatial ratios for each localized segment. This localized analysis enables precise determination of malfunction location and severity by comparing characteristics of specific signal portions rather than treating the entire waveform uniformly.
Data Source
AI summary
A system for heart performance characterization uses an interface to receive waveform signal data representing electrical activity of a patient heart over at least one heart beat cycle. The signal processor uses a signal peak and amplitude detector for, identifying a first signal portion of a first heart cycle of the signal data, identifying multiple different amplitude levels within the first signal portion, determining a first area under the waveform in the first signal portion corresponding to at least one particular amplitude level and deriving a parameter in response to the determined first area. The output processor generates an alert message if at least one of, (a) the derived parameter and (b) a difference between the derived parameter and a corresponding derived parameter for a different heart cycle for the same patient, exceeds a predetermined threshold value.