Atrial Fibrillation Electrogram Activation Point Annotation
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Solution Overview
Problem
Conventional methods for annotating electrogram signals during atrial fibrillation are inadequate due to the irregularity and variability of the signals, making it difficult for physicians to identify activation points, especially in cases of atrial fibrillation or other arrhythmias.
Innovation Solution
A system comprising an electrical interface and a processor that processes electrogram signals by dividing them into time periods, selecting candidate activation points based on magnitude and threshold calculations, and removing duplicate points within a specific interval to accurately annotate and display activation points corresponding to respective electrical activations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods are used to annotate electrogram signals, then the process can be performed with simple equipment, but the annotation accuracy and consistency deteriorate due to signal irregularity and variability
Solution Approach 1:
The patent divides the electrogram signal into discrete time periods and identifies activation points by examining specific features within each period. The signal processing is segmented into distinct steps: detecting signal points exceeding thresholds, determining time periods for each activation, and calculating cycle lengths. This segmentation enables consistent automated annotation despite signal variability.
Solution Approach 2:
The patent employs dynamic threshold adjustments and multiple parameter comparisons (amplitude, duration, timing intervals) to distinguish true activation points from noise. By changing detection parameters adaptively based on signal characteristics, the system maintains high annotation accuracy across varying signal conditions without requiring overly complex equipment.
2Productivity
If manual interpretation of electrogram signals is used, then equipment complexity remains low, but productivity and real-time analysis capability deteriorate
Solution Approach 1:
The system performs automated signal analysis and annotation without requiring continuous manual intervention. The processor independently detects signal points, determines time periods, identifies activation points, and calculates cycle lengths. This self-service capability enables real-time productivity enhancement while maintaining manageable system complexity through algorithmic automation rather than complex hardware.
Solution Approach 2:
The patent replaces manual visual inspection and interpretation (mechanical human process) with automated digital signal processing algorithms. The processor executes programmed instructions to detect, analyze, and annotate electrogram signals, substituting human cognitive work with computational processes that enable faster productivity while keeping device complexity at an acceptable level.
3Reliability
If simplified detection methods are used, then device complexity is reduced, but measurement precision and reliability of activation point identification deteriorate
Solution Approach 1:
The system uses feedback mechanisms where previously identified activation points inform the detection of subsequent points. The processor calculates cycle lengths based on identified activations and uses this temporal information to refine detection of subsequent activation points. This feedback loop enhances reliability by ensuring consistent identification across the electrogram signal while maintaining reasonable processing complexity.
Solution Approach 2:
The patent establishes detection thresholds and time period parameters in advance before analyzing the electrogram signal. By pre-defining criteria for signal point detection and activation point identification, the system ensures reliable and consistent results without requiring complex real-time adjustments during signal processing.
Data Source
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AI summary
A system includes an electrical interface and a processor configured to receive, via the electrical interface, a signal sensed by at least one electrode in contact with tissue of a subject's heart, the signal spanning successive time periods that are each of length T1 and including multiple signal points, to calculate respective thresholds for the time periods, to select a set of points that includes, for each of the time periods, a signal point of greatest magnitude in the time period, provided that the greatest magnitude is greater than the threshold for the time period, to remove, from the set, one of any pair of the selected points that are within an interval T2 of one another, T2 being less than T1, and to generate, subsequently to the removing, an output that is based on the points remaining in the set corresponding to respective electrical activations of the tissue.