Adaptive Cardiac Event Detection Threshold Adjustment
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Solution Overview
Problem
Implantable cardiac stimulus devices face challenges in accurately detecting cardiac events, leading to potential overdetection and incorrect therapy decisions due to the misclassification of cardiac rhythms, which can result in inappropriate therapy delivery.
Innovation Solution
The implementation of a method that adjusts the sensitivity of the detection profile based on the similarity or dissimilarity of detected event peaks, using a 'similar' or 'dissimilar' detection profile to prevent overdetection, by comparing the amplitude of recent peaks to prior peaks and modifying the detection threshold accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the detection sensitivity is increased to improve cardiac event detection accuracy, then more cardiac events can be detected, but overdetection increases leading to incorrect therapy decisions
Solution Approach 1:
The patent applies dynamics by making the detection profile sensitivity adjustable and adaptive. The system dynamically modifies the detection threshold based on the similarity between recent and prior peak amplitudes. When peaks are similar, the system uses a less sensitive profile; when peaks are dissimilar, it uses a more sensitive profile. This dynamic adjustment allows the system to optimize detection accuracy while minimizing overdetection and incorrect therapy decisions.
Solution Approach 2:
The patent changes the detection parameter (sensitivity/threshold) based on the similarity ratio of peak amplitudes. By calculating the similarity between recent and prior peaks and adjusting the detection profile accordingly, the system adapts its detection characteristics to reduce overdetection while maintaining accurate detection of true cardiac events.
2Ease of operation
If a fixed detection profile is used to simplify device operation, then ease of operation is improved, but detection accuracy deteriorates due to inability to adapt to varying cardiac conditions
Solution Approach 1:
The system performs self-service by automatically adjusting its own detection profile based on the characteristics of the detected cardiac signals. The microprocessor calculates the similarity between recent and prior peaks and autonomously selects the appropriate detection profile sensitivity level, eliminating the need for manual intervention while maintaining high detection accuracy.
Solution Approach 2:
The system uses feedback by continuously monitoring the similarity between detected peak amplitudes and adjusting the detection profile accordingly. The similarity calculation provides feedback about the current cardiac condition, which then feeds back into the detection algorithm to optimize detection accuracy for the current physiological state.
Data Source
AI summary
Signal analysis in an implanted cardiac monitoring and treatment device such as an implantable cardioverter defibrillator. In some examples, detected events are analyzed to identify changes in detected event amplitudes. When detected event amplitudes are dissimilar from one another, a first set of detection parameters may be invoked, and, when detected event amplitudes are similar to one another, a second set of detection parameters may be invoked. Additional examples determine whether the calculated heart rate is “high” or “low,” and then may select a third set of detection parameters for use when the calculated heart rate is high.