Electrophysiological Signal Conduction Timing Detection
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Solution Overview
Problem
Existing methods for detecting conduction timing in electrograms are prone to signal distortion due to aggressive filtering and rely on non-robust zero-crossing measurements, especially in noisy conditions like baseline drifting during body-surface recordings.
Innovation Solution
A system and method that analyze the morphology and amplitude of electrophysiological signals to identify candidate segments with predetermined conduction pattern criteria, ensuring spatial and temporal consistency across neighboring segments to determine activation times without aggressive filtering or phase calculation, enabling robust detection of conduction patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If aggressive filtering is applied to remove noise from electrograms, then noise is reduced, but signal information is lost and downward slopes are distorted
Solution Approach 1:
The patent extracts only the essential features (downward slope detection, zero-crossing points) needed for activation time determination, rather than processing the entire filtered signal. This allows selective removal of noise components while preserving critical signal information for conduction timing analysis.
Solution Approach 2:
The patent applies different processing strategies to different parts of the electrogram signal. Critical regions (downward slopes containing activation information) are preserved with minimal filtering, while non-critical regions undergo more aggressive noise reduction. This localized approach maintains signal integrity where it matters most.
2Measurement precision
If zero-crossing of electrograms is used as a surrogate for activation time, then activation timing can be identified, but the measure is non-robust in the presence of noise and baseline drifting
Solution Approach 1:
The patent incorporates feedback mechanisms where detected activation times from multiple electrodes and time points are used to refine and validate subsequent detections. Consistency checks across neighboring electrodes provide feedback that filters out false positives caused by noise, while confirming true activation events.
Solution Approach 2:
The patent dynamically adjusts detection parameters such as slope thresholds and time windows based on local signal characteristics and noise levels. This adaptive parameter adjustment maintains robustness across varying noise conditions while preserving measurement precision for activation time identification.
Data Source
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AI summary
An example method includes analyzing morphology and/or amplitude of each of a plurality of electrophysiological signals across a surface of a patient's body to identify candidate segments of each signal satisfying predetermined conduction pattern criteria. The method also includes determining a conduction timing parameter for each candidate segment in each of the electrophysiological signals.