Atrial Flutter Decision Support System for Automated Electrogram Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current diagnostic processes for atrial flutter are largely dependent on physician experience and manual analysis of complex electrogram data, which can be overwhelming and inefficient, especially in identifying specific arrhythmogenic regions and mechanisms.
Innovation Solution
A computer-based decision support system that receives electrical reference signals and multiple sensor signals to automatically determine active and resting intervals, calculates cycle length coverage, and visualizes potential focal sources or re-entries in the atria, providing a more precise diagnostic aid for physicians.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If comprehensive electrogram data is acquired using multi-polar mapping catheters, then diagnostic information completeness is improved, but data complexity and analysis burden increase
Solution Approach 1:
The patent segments the complex electrogram data analysis into distinct automated components: activation time annotation, voltage calculation, and diagnostic feature extraction. Each component processes specific aspects of the data independently, reducing the overall complexity burden on physicians while maintaining comprehensive diagnostic information.
Solution Approach 2:
The system introduces an automated analysis intermediary that acts as a bridge between the complex multi-polar mapping data and the physician. This intermediary automatically processes the comprehensive electrogram data, extracting key diagnostic features and presenting simplified results, thereby reducing the analysis burden while preserving diagnostic completeness.
2Measurement precision
If manual visual inspection is used to evaluate additional features, then diagnostic accuracy is improved, but time consumption and workload increase
Solution Approach 1:
The system enables self-service automated analysis where the computer automatically performs feature evaluation without requiring manual visual inspection. The system autonomously annotates activation times, calculates voltages, identifies double potentials, and determines fractionation indices, thereby maintaining diagnostic accuracy while eliminating time-consuming manual analysis.
Solution Approach 2:
The patent replaces the mechanical manual visual inspection process with an automated computational system. The automated analysis engine substitutes the physician's manual evaluation with algorithm-based processing, maintaining diagnostic precision while dramatically reducing time consumption and workload.
3Productivity
If automated analysis techniques are implemented, then productivity is improved, but measurement precision may deteriorate
Solution Approach 1:
The system incorporates feedback mechanisms where automated analysis results are continuously refined based on comparison with established diagnostic criteria and clinical guidelines. The automated annotation and measurement processes use feedback loops to ensure precision, maintaining diagnostic accuracy while achieving high productivity through automation.
Solution Approach 2:
The patent employs parameter changes in the automated analysis algorithms to optimize both productivity and precision. By adjusting analysis parameters such as voltage thresholds, activation time windows, and fractionation indices based on clinical data and validation studies, the system achieves high diagnostic precision while maintaining efficient automated processing.
Data Source
Figure 1
Figure 2A
Figure 2B
AI summary
A decision support computer system (100), computer implemented method, and computer program product for supporting diagnostic analysis of atrial flutter types. The system includes an interface component (110) to receive an electrical reference signal (RS) generated by a reference sensor (CSCS). The reference signal (RS) provides a time reference for electrical activity of one or more atria of a patient wherein the time interval between two subsequent electrical activities is referred to as basic cycle length (BCL). The interface further receives a plurality of electrical signals (P1 to Pi) generated by one or more further sensors (S1 to Sn) wherein the plurality of electrical signals (P1 to Pi) relate to a plurality of locations in the one or more atria. The plurality of locations comprising locations different from the location of the reference sensor (CSCS). A signal analyzer component (120) of the system determines, for each signal of at least a subset of the received signals originating from locations within a selected area of the one or more atria, an active interval when electrical activity occurs, and a resting interval when no electrical activity occurs. Based on the determined intervals, a subset cycle length coverage is computed as the ratio of duration of activity (DoA) and the basic cycle length (BCL) wherein the duration of activity includes the active intervals for the entire subset of signals. A visualizer component (130) of the system indicates the selected area as an area including a potential focal source if the subset cycle length coverage is smaller than a predefined ratio. Else it indicates the selected area as an area including a potential re-entry.