Retractable Classification Windows for Cardiac Capture Detection
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Solution Overview
Problem
Current cardiac rhythm management systems face challenges in accurately distinguishing between captured responses and fusion/pseudofusion beats, leading to inefficient energy expenditure and potential discomfort for patients due to incorrect capture threshold determination.
Innovation Solution
The implementation of retriggerable classification windows and multiple cardiac response classification windows to sense and classify cardiac signals post-pacing stimulation, allowing for precise differentiation between captured, non-captured, and fusion/pseudofusion responses, thereby optimizing pacing energy and reducing unnecessary pulse generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single classification window is used to detect cardiac responses, then the device complexity is reduced, but the measurement precision of capture detection deteriorates due to inability to distinguish fusion/pseudofusion beats from captured responses
Solution Approach 1:
The patent divides the detection process into multiple sequential classification windows (first, second, and third windows) with different detection characteristics. The first window detects early cardiac signals, the second window detects later signals with different morphology, and the third window provides additional verification. This segmentation allows the system to distinguish captured responses from fusion/pseudofusion beats by comparing signals across multiple time windows, thereby improving measurement precision without requiring a single complex window.
2Reliability
If pace pulse energy is increased to ensure reliable capture, then the reliability of cardiac contraction is improved, but the energy consumption increases and patient discomfort increases
Solution Approach 1:
The patent implements a feedback mechanism where the classification results from multiple windows are used to determine whether a captured response occurred. Only when the signal characteristics match the captured response pattern across the classification windows does the system confirm capture and potentially adjust pacing energy. This feedback-based approach allows the system to use minimal energy while maintaining reliability by accurately identifying true captures and avoiding unnecessary high-energy pulses.
Solution Approach 2:
The system changes detection parameters (window timing, amplitude thresholds, morphology criteria) based on the detected signal characteristics. By adapting the detection parameters to match the specific response type, the system can reliably detect captures at lower energy levels and distinguish them from fusion beats, thereby reducing overall energy consumption while maintaining capture reliability.
3Productivity
If a single classification window is used, then the ease of operation is improved, but the productivity of capture threshold determination deteriorates due to false detections requiring manual verification
Solution Approach 1:
The patent segments the capture detection process into multiple automated classification windows that operate sequentially. Each window analyzes specific signal characteristics and contributes to the overall classification decision. This automated multi-window approach eliminates the need for manual verification of each capture event, thereby improving productivity. The system maintains ease of operation by automating the complex analysis that would otherwise require manual intervention.
4Measurement precision
If pace pulse width is increased to improve capture detection, then the measurement precision of cardiac signal detection is improved, but the energy consumption increases
Solution Approach 1:
The patent uses periodic sampling of cardiac signals across multiple classification windows instead of continuous monitoring with high energy pulses. The system periodically checks for characteristic signal patterns at specific time points (windows) rather than continuously delivering high-energy pacing pulses. This periodic approach maintains detection precision by sampling at critical moments while significantly reducing overall energy loss compared to continuous high-energy pacing.
Data Source
AI summary
Methods and devices for classifying a cardiac response to pacing involve establishing a retriggerable cardiac response classification window. A first cardiac response classification window is established subsequent to delivery of a pacing pulse. A cardiac signal following the pacing stimulation is sensed in the first classification window. A second cardiac response classification may be triggered if a trigger characteristic is detected in the first classification window. The cardiac signal is sensed in the second classification window if the second classification window is established. The cardiac response to the pacing stimulation is determined based on characteristics of the cardiac signal. The cardiac response may be determined to be one of a captured response, a non-captured response, a non-captured response added to an intrinsic beat, and a fusion/pseudofusion beat, for example.