P-wave Detection in Cardiac Arrhythmia Monitoring
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Solution Overview
Problem
Current implantable cardiac monitors (ICMs) face challenges in accurately detecting atrial fibrillation (AF) due to false detections caused by irregular RR intervals, inappropriate R-wave sensing, and misalignment of P-wave markers, leading to incorrect AF episode identification.
Innovation Solution
A computer-implemented method that aligns R-wave features in the P-wave analysis window, identifies and rejects outlier P-waves, and forms a P-wave segment ensemble template to improve the accuracy of AF detection by reducing false positives and accounting for P-R interval variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If R-wave markers are used for P-wave analysis, then the analysis can be performed, but the markers are misaligned for certain QRS morphologies leading to false AF detection
Solution Approach 1:
The patent replaces the mechanical/automatic R-wave marker placement system with a manual annotation system where clinicians mark P-wave features of interest. This substitution eliminates the misalignment problem caused by automated markers on atypical QRS morphologies, as the manual markers are deliberately placed on the actual P-wave features regardless of QRS shape.
Solution Approach 2:
The patent introduces an intermediary layer of manual clinician annotation between the ECG signal and the P-wave analysis algorithm. The manual markers serve as a mediator that translates the raw signal into annotated feature points, allowing the algorithm to accurately identify P-wave characteristics without being misled by atypical QRS morphologies.
2Adaptability or versatility
If P-R interval variation is present, then the heart rhythm can be irregular, but the P-waves are not aligned causing detection errors
Solution Approach 1:
The patent implements dynamic adjustment of the P-wave analysis window based on the detected P-R interval duration. The window position and size are made variable rather than fixed, allowing the system to adapt to different P-R intervals while maintaining proper P-wave alignment. This dynamic approach enables accurate P-wave detection across varying heart rhythms.
Solution Approach 2:
The patent changes the parameters of the P-wave analysis window (position, duration, size) based on the measured P-R interval. By adjusting these parameters dynamically according to the actual P-R interval duration, the system maintains optimal P-wave detection accuracy despite variations in P-R interval length.
3Object-affected harmful factors
If baseline drift or motion artifact is present, then the signal quality deteriorates, but the ensemble average template is distorted
Solution Approach 1:
The patent extracts and removes baseline drift and motion artifact components from the ECG signal before P-wave analysis. By separating and eliminating these harmful factors, the system preserves the true P-wave morphology and creates an accurate ensemble average template that reflects actual P-wave characteristics rather than signal artifacts.
Solution Approach 2:
The patent converts the presence of baseline drift and motion artifacts into a detection opportunity. By analyzing the signal for these artifact patterns, the system can identify and exclude contaminated beats from the ensemble average calculation, ultimately improving template accuracy by removing distorted P-waves caused by artifacts.
Data Source
AI summary
A computer implemented method for detecting arrhythmias in cardiac activity including obtaining far field cardiac activity (CA) signals for a series of beats. For at least a portion of the beats, the one or more processors perform, on a beat by beat basis: a) identifying first and second feature of interests (FOI) from a segment of the CA signal that corresponds to a current beat; and b) classifying the current beat into one of first and second groups. The method also includes designating one of the first and second groups to be a primary group based on a relation between the first and second groups, and for the beats in the primary group, selecting one of the first and second FOIs as the R-wave FOI. The method also includes rejecting an arrhythmia detection based on the P-waves detected.