Automated Electrogram Time Delay Analysis for Arrhythmia Risk
Solution Overview
Problem
Current methods for analyzing heart electrical data are inefficient due to reliance on human expertise, time-consuming manual annotation, and difficulty in comparing and interpreting patterns across different heart locations, leading to scarce analysis capabilities and multiple conflicting interpretations.
Innovation Solution
A method and apparatus that compare electrograms from multiple locations on the heart between a reference and a stimulated state to calculate time delays, allowing for automated analysis and visualization of changes, enabling quicker and more accurate identification of arrhythmia susceptibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual annotation by human experts is used to identify electrical events, then interpretation accuracy may be maintained, but analysis time and productivity are severely limited
Solution Approach 1:
The system performs self-service by automatically identifying electrical events and calculating time delays without requiring human expert intervention. The automated processing engine analyzes electrograms, detects electrical events, and computes spatial-temporal patterns independently, eliminating the bottleneck of manual annotation while maintaining consistent interpretation standards.
Solution Approach 2:
The patent replaces the mechanical system of manual human annotation with an automated computational system. The processing engine uses algorithmic methods to identify electrical events and calculate time delays, substituting human cognitive processes with machine-based signal processing and pattern recognition techniques.
2Quantity of substance
If large volumes of electrogram data from multiple electrodes are collected, then comprehensive heart coverage is achieved, but data processing complexity and time requirements increase
Solution Approach 1:
The patent segments the large volume of electrogram data by spatial location and temporal characteristics. The system divides electrograms into discrete segments corresponding to different electrodes and time intervals, allowing parallel processing of multiple segments simultaneously. This segmentation enables efficient handling of data from 100+ electrodes by processing each location's electrograms independently through the automated engine.
Solution Approach 2:
The system performs preliminary actions by pre-processing electrograms to identify key features and electrical events before full analysis. The automated processing engine prepares data structures and identifies candidate events in advance, reducing the computational burden during the main analysis phase and enabling faster processing of large datasets.
3Adaptability or versatility
If visual inspection of electrogram curves is used to identify electrical events, then expert judgment can be applied, but reliability and consistency of event timing identification decrease
Solution Approach 1:
The patent replaces visual inspection with automated signal processing methods that consistently identify electrical events based on objective criteria. The processing engine uses algorithmic detection of voltage thresholds, slope changes, and waveform characteristics to identify electrical events, eliminating the subjectivity and variability inherent in visual curve interpretation by human experts.
Solution Approach 2:
The system changes the approach from qualitative visual assessment to quantitative parameter-based detection. The automated engine measures specific electrical parameters such as voltage amplitude, time intervals, and rate of change to objectively identify electrical events, providing reliable and consistent timing measurements that are not subject to inter-expert variability.
4Adaptability or versatility
If comparison of electrical signals from adjacent points is performed manually, then pattern recognition may occur, but uncertainty in identifying corresponding instants on different curves increases
Solution Approach 1:
The patent replaces manual comparison of adjacent electrogram points with automated cross-correlation and time-delay calculation algorithms. The processing engine systematically compares corresponding instants on different curves using computational methods, precisely calculating time delays between electrical events at adjacent locations without the uncertainty of manual visual alignment.
Solution Approach 2:
The system uses feedback mechanisms by iteratively refining time delay measurements through comparison of adjacent electrograms. The automated engine calculates initial time delays, verifies consistency across multiple adjacent points, and adjusts measurements to ensure pattern coherence, providing precise and reliable time delay data for arrhythmia risk assessment.
Data Source
AI summary
A method of analysing changes in the electrical activity of a patient's heart between a reference state and a test state, the method using a reference data set of electrophysiological data captured from the patient in the reference state and at least one test data set of electrophysiological data captured from the patient in the test state, each data set defining a plurality of electrograms for a respective plurality of spatial locations relative to the heart, the method comprising processing the electrophysiological data by, matching each electrogram in the reference data set to a corresponding electrogram in the at least one test data set to create a pair of electrograms for each of the plurality of spatial locations, and deriving a time delay for each spatial location by calculating the time delay between the electrograms of the pair of matched electrograms for that spatial location.