Dynamic Arrhythmia Detection Parameter Adjustment
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Solution Overview
Problem
Current medical devices face challenges in accurately detecting long-duration arrhythmia events, such as atrial fibrillation, due to the risk of missing events when individual detection windows contain noisy data or signal quality issues, leading to false negatives and increased resource utilization.
Innovation Solution
The system dynamically adjusts arrhythmia detection parameters and thresholds based on the duration of detected events, increasing sensitivity for long-duration event detection while maintaining specificity in individual detection windows, thereby reducing false positives and optimizing resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fixed arrhythmia detection parameters and thresholds are used in individual detection windows, then detection specificity is maintained, but long-duration arrhythmia events may be missed due to noisy data or signal quality issues
Solution Approach 1:
The patent implements dynamic adjustment of arrhythmia detection parameters and thresholds based on the duration of detected events. The system transitions from fixed parameters to adaptive parameters that automatically modify detection sensitivity according to whether short or long-duration events are detected, thereby resolving the contradiction between maintaining specificity in individual windows and improving sensitivity for long-duration events
Solution Approach 2:
The system changes detection parameters (such as threshold values and detection criteria) based on the duration characteristic of arrhythmia events. By modifying parameters dynamically according to event duration, the system can accurately distinguish between transient noise and sustained arrhythmia, improving both reliability and measurement precision simultaneously
2Measurement precision
If detection parameters are adjusted to increase sensitivity for long-duration events, then detection accuracy improves, but false positives may increase in individual detection windows
Solution Approach 1:
The system dynamically adjusts detection parameters based on the duration of detected events, applying higher sensitivity only when long-duration patterns are identified. This prevents false positives in individual windows while maintaining high sensitivity for genuine long-duration arrhythmia events, resolving the contradiction between sensitivity and false positive rate
Solution Approach 2:
The system performs preliminary analysis of detection window patterns to determine whether to apply enhanced sensitivity parameters. By preliminarily identifying long-duration event characteristics before finalizing detection parameters, the system avoids false positives while preparing to detect sensitive long-duration arrhythmia events accurately
3Reliability
If multiple detection windows are analyzed to confirm arrhythmia events, then detection reliability improves, but resource utilization increases
Solution Approach 1:
The system dynamically adjusts the number and duration of detection windows based on initial findings. When short-duration events are detected, the system uses fewer windows with standard parameters, conserving resources. When long-duration patterns emerge, the system automatically extends detection windows and increases analysis depth, improving reliability only when necessary and optimizing resource utilization overall
Data Source
AI summary
This document discusses, among other things, systems and methods to detect an initial arrhythmia event indication and, after a threshold amount of detection window intervals detecting the initial arrhythmia event indication, adjust a set of arrhythmia parameters or at least one of a respective set of parameter thresholds to increase sensitivity of an extended arrhythmia event indication detection.