Morphological R-Wave Screening for False Arrhythmia Detection
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Solution Overview
Problem
Existing implantable medical devices (IMDs) face challenges in accurately distinguishing R-waves from over-sensed P-waves and T-waves, leading to false detections of cardiac arrhythmias and inappropriate therapy delivery, which can deplete battery power and cause patient discomfort.
Innovation Solution
A method and device that utilize morphological and temporal criteria, such as peak amplitude, area under the curve, and R-R interval duration, to classify R-wave detections as false due to T-wave or P-wave oversensing, using comparisons with earlier detections to establish specific criteria for differentiation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional ICDs use bipolar intracardiac electrogram signals for rhythm detection, then accurate arrhythmia detection is achieved, but device complexity and manufacturing difficulty increase
Solution Approach 1:
The patent extracts the rhythm detection function from the complex intracardiac electrogram signal processing and applies it to simplified subcutaneous ECG signals. By using far-field subcutaneous EGMs instead of bipolar intracardiac signals, the system maintains arrhythmia detection capability while significantly reducing device complexity and manufacturing difficulty.
Solution Approach 2:
The patent uses subcutaneous ECG signals as a simplified copy or representation of the more complex intracardiac electrogram signals. These subcutaneous EGMs resemble surface ECGs and provide sufficient information for arrhythmia detection without requiring the complex intracardiac electrode configuration, thus reducing device complexity while maintaining measurement precision.
2Device complexity
If S-ICDs use far-field subcutaneous EGMs for rhythm detection, then device complexity is reduced, but false detections of ventricular tachycardia or fibrillation occur due to T-wave or P-wave oversensing
Solution Approach 1:
The patent applies different detection criteria and thresholds for different wave types (P-waves, QRS complexes, T-waves) within the subcutaneous EGM signal. By analyzing the local morphological characteristics of each wave type and applying appropriate discrimination criteria, the system reduces false detections while maintaining the simplicity of subcutaneous EGM recording.
Solution Approach 2:
The patent modifies detection parameters such as amplitude thresholds, slope criteria, and morphological characteristics to distinguish true R-waves from oversensed P-waves and T-waves. By dynamically adjusting these parameters based on signal context and historical data, the system improves detection reliability without increasing device complexity.
3Measurement precision
If false positive VT and VF detections are made, then arrhythmia monitoring sensitivity is improved, but inappropriate therapy delivery occurs which depletes battery power and causes patient discomfort
Solution Approach 1:
The patent performs preliminary analysis of each detected rhythm to determine whether it represents a true arrhythmia or a false detection before initiating therapy. By pre-screening using morphological criteria, R-R interval analysis, and discrimination algorithms, the system filters out false positives and only delivers therapy when truly necessary, thereby conserving battery power while maintaining monitoring sensitivity.
Solution Approach 2:
The patent implements feedback mechanisms that continuously monitor and learn from detection patterns to refine future detections. By analyzing the consequences of previous detections and adjusting thresholds based on patient-specific characteristics and response patterns, the system reduces false positives and optimizes battery usage while maintaining high sensitivity for real arrhythmias.
4Adaptability or versatility
If ICMs monitor for AF by measuring R-R interval variability, then AF detection capability is improved, but false positive AF detections increase which consumes clinical resources
Solution Approach 1:
The patent applies local quality analysis by examining the specific morphological characteristics of each R-wave and its surrounding EGM features. By analyzing the local signal properties around each R-R interval measurement, the system can distinguish true AF from false positives, improving detection reliability while maintaining the versatility of R-R variability monitoring for AF detection.
Data Source
AI summary
Described herein are methods, devices and systems for classifying an R-wave detection as a false R-wave detection due to T-wave oversensing (TWO) or P-wave oversensing (PWO), by determining whether at least one of first TWO or PWO temporal criteria or second TWO or PWO temporal criteria are met for R-wave detections in a window leading up to an arrhythmic episode detection, and based on an extent of the R-wave detections classified as being false R-wave detections due to TWO or PWO selectively preventing or aborting delivery of therapy intended to treat the arrhythmic episode, selectively preventing transmission by the IMD to an external device of data corresponding to the arrhythmic episode that can be used for diagnostic purposes, or selectively adjusting at least one parameter of the R-wave detection threshold that can be used by the IMD for detecting further R-waves and thereby detecting a further arrhythmic episode.