Phrenic Nerve Stimulation Detection in Cardiac Pacing
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Solution Overview
Problem
Implanted cardiac pacing systems often experience unintended phrenic nerve stimulation due to the proximity of pacing leads to the phrenic nerve, leading to discomfort and requiring frequent adjustments and reprogramming, as the anatomical location of the phrenic nerve varies among patients and changes over time.
Innovation Solution
A method and system for detecting pace-induced phrenic nerve stimulation using cardiac paces, which involves pacing the heart, sensing physiological signals, building templates of beat signals, and using correlation and morphological feature analysis to identify and differentiate between phrenic nerve stimulation and non-stimulation beats, allowing for automatic detection and adjustment of pacing parameters to avoid nerve activation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If left ventricular pacing is used to deliver cardiac resynchronization therapy, then cardiac therapy efficacy is improved, but unintended phrenic nerve stimulation occurs causing patient discomfort
Solution Approach 1:
The system performs preliminary detection of phrenic nerve stimulation by analyzing beat signals and comparing them against stored templates before committing to a pacing configuration. This allows the system to identify potential phrenic nerve capture early and adjust parameters proactively to prevent patient discomfort while maintaining effective cardiac resynchronization therapy.
2Object-affected harmful factors
If pacing parameters are adjusted to avoid phrenic nerve stimulation, then patient comfort is improved, but detection and reprogramming requirements increase clinical burden
Solution Approach 1:
The system performs self-detection of phrenic nerve stimulation by automatically analyzing beat signals, comparing them against stored templates, and identifying PS beats without requiring external intervention. This self-service capability reduces the clinical burden by eliminating the need for manual detection and reprogramming, while maintaining patient comfort through automatic parameter adjustment.
Solution Approach 2:
The system implements continuous feedback by monitoring beat signals in real-time, comparing them against stored templates, and automatically adjusting pacing parameters based on detected phrenic nerve stimulation patterns. This closed-loop feedback mechanism reduces clinical burden by eliminating manual detection and reprogramming requirements while maintaining patient comfort.
3Ease of manufacture
If phrenic nerve stimulation detection is performed manually during implant, then initial setup is simplified, but post-implant phrenic nerve activation cannot be detected
Solution Approach 1:
The system maintains continuous detection capability by storing beat signal templates during implant and continuously comparing subsequent beats against these templates. This uninterrupted monitoring ensures that phrenic nerve stimulation detected during implant can be tracked throughout the patient's life, detecting post-implant activation that would otherwise go unnoticed.
4Measurement precision
If beat signal templates are stored and compared for PS detection, then detection accuracy is improved, but memory usage and processing complexity increase
Solution Approach 1:
The system extracts only the essential features of beat signals for template storage and comparison, focusing on the specific characteristics that differentiate PS beats from non-PS beats. By extracting only the necessary signal features rather than storing complete raw signals, the system achieves high detection accuracy while minimizing memory usage and processing complexity.
Data Source
AI summary
In an example, a system includes a cardiac pulse generator configured to generate cardiac paces to pace the heart, a sensor configured to sense a physiological signal for use in detecting pace-induced phrenic nerve stimulation where the pace-induced phrenic nerve stimulation is phrenic nerve stimulation induced by electrical cardiac pace signals, and a phrenic nerve stimulation detector configured to analyze the sensed physiological signal to detect PS beats where the PS beats are cardiac paces that induce phrenic nerve stimulation. The detector may be configured to correlate signal data for sensed beat signals to a PS template to detect PS beats, or may be configured to analyze morphological features of sensed beat signals to detect PS beats, or may be configured to detect PS beats using a combination that both correlates signal data for sensed beat signals to a PS template and analyzes morphological features of sensed beat signals.