Conducted PAC Burden Estimation in Ambulatory Cardiac Monitoring
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Solution Overview
Problem
Current ambulatory medical devices lack the capability to accurately detect conducted premature atrial contractions (PACs), which are predictors of Atrial Fibrillation, stroke, and mortality.
Innovation Solution
The development of an ambulatory medical device (AMD) equipped with a cardiac signal sensing circuit and a control circuit that monitors cardiac depolarizations, detects bimodal heart rate distributions, identifies conducted PACs, and computes a PAC burden value to alert healthcare providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If ambulatory medical devices monitor cardiac signals continuously, then early detection of worsening patient condition is improved, but device complexity and energy consumption increase
Solution Approach 1:
The monitoring system is segmented into specific detection modules: a sensing circuit for cardiac signals, a classification circuit for identifying PAC types (conducted vs. non-conducted), and a burden calculation module. This segmentation allows targeted monitoring of PACs without requiring full continuous analysis of all cardiac signals, reducing overall system complexity while maintaining early detection capability.
Solution Approach 2:
The device performs preliminary classification of cardiac depolarizations to identify potential PACs before full analysis. By detecting premature depolarizations and classifying them as conducted or non-conducted PACs in advance, the system prepares data for burden calculation, enabling early detection without requiring continuous full-signal processing.
2Reliability
If the device accurately identifies conducted PACs and computes PAC burden, then prediction of Atrial Fibrillation and stroke risk is improved, but measurement precision requirements increase device complexity
Solution Approach 1:
The system uses feedback mechanisms where detected cardiac depolarizations are continuously compared against established patterns for conducted PACs. The classification circuit receives feedback from the sensing circuit and adjusts identification based on morphological comparisons, improving detection precision through iterative validation without requiring excessively complex measurement systems.
Solution Approach 2:
The device creates template copies of typical conducted PAC waveforms and compares incoming signals against these templates. By using reference copies of expected PAC patterns, the system achieves high measurement precision in distinguishing conducted PACs from other cardiac events without requiring overly complex real-time analysis capabilities.
3Reliability
If the device monitors and counts conducted PACs over time, then PAC burden estimation is improved, but loss of time for data processing increases
Solution Approach 1:
The device performs PAC burden estimation at periodic intervals rather than continuously processing every detected PAC. The system accumulates conducted PAC counts over defined time periods and computes burden estimates periodically, reducing total data processing time while maintaining reliable burden estimation accuracy through structured temporal sampling.
Data Source
AI summary
Systems and methods are disclosed to an ambulatory medical device comprising a cardiac signal sensing circuit configured to sense a cardiac signal representative of cardiac activity of a patient when connected to electrodes, and a control circuit. The control circuit is configured to monitor cardiac depolarizations in the sensed cardiac signal, detect a bimodal distribution of heart rate of the patient, identify cardiac depolarization intervals shorter than a predetermined interval threshold, identify premature atrial contractions (PACs) in the sensed cardiac signal that are conducted normally and conducted aberrantly, and count a number of conducted PACs and produce an alert related to PC burden of the patient based on the number.