PVC-Burden-Adjusted AF Detection for Fewer False Positives
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Solution Overview
Problem
Existing atrial fibrillation (AF) detection systems fail to adequately account for premature ventricular contractions (PVCs), leading to false detections and inefficiencies in cardiac rhythm analysis.
Innovation Solution
A system and method that adjusts AF detection algorithms based on PVC burden, categorizing PVC states into low, high, and very-high categories, and adjusts detection parameters accordingly, including removing PVC events from detection windows to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If AF detection algorithms are applied without adjusting for PVC burden, then detection speed is maintained, but detection accuracy deteriorates due to false positives
Solution Approach 1:
The system dynamically adjusts AF detection parameters based on real-time PVC burden assessment. When PVC burden is high, the system modifies detection thresholds and algorithms to account for PVC interference, thereby maintaining accuracy without requiring complete reprocessing of all data.
Solution Approach 2:
The system changes detection parameters such as threshold values, window sizes, and algorithm selections based on the detected PVC burden level. This allows the system to adapt its sensitivity and specificity settings to match the current cardiac rhythm conditions.
2Reliability
If all cardiac electrical information is processed for AF detection, then detection sensitivity is maintained, but device power consumption increases
Solution Approach 1:
The system extracts and removes PVC events from the cardiac electrical information before performing AF detection. By separating PVC artifacts from genuine AF signals, the system reduces the amount of data that requires full processing, thereby lowering power consumption while maintaining detection sensitivity for actual AF episodes.
Solution Approach 2:
The system performs preliminary PVC detection and classification before the main AF detection process. This preliminary action identifies and filters out PVC-related signals in advance, reducing the computational load on subsequent AF detection algorithms and consequently reducing overall power consumption.
3Measurement precision
If PVC events are removed from detection windows, then false positive AF detections are reduced, but detection coverage may be compromised
Solution Approach 1:
The system segments the cardiac rhythm analysis into distinct PVC-related segments and AF detection segments. By isolating PVC events as separate entities and analyzing them separately, the system can remove their interfering effects from AF detection windows while preserving the overall detection coverage through structured multi-phase analysis.
Data Source
AI summary
This document discusses, among other things, systems and methods to receive cardiac electrical information of a subject, detect a premature ventricular contraction (PVC) event in a first detection window using the received cardiac electrical information, determine a count of detected PVC events in the first detection window, remove cardiac electrical information associated with the detected PVC event from the first detection window based on the determined count of detected PVC events, and detect an indication of atrial fibrillation of the subject for the first detection window using remaining cardiac electrical information in the first detection window.