Dynamic Threshold Adjustment for Heart Failure Decompensation Detection
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Solution Overview
Problem
Current implantable medical devices lack effective methods for early detection and prediction of heart failure decompensation, leading to delayed hospitalization and potential worsening of the patient's condition.
Innovation Solution
An implantable medical device (IMD) that monitors physiological signals, specifically using heart failure variables such as transthoracic impedance and right ventricular pressure, to detect decompensation by adjusting detection thresholds based on interdependent variables, allowing for earlier and more accurate prediction of worsening heart failure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If implantable medical devices monitor physiological signals using fixed detection thresholds, then the device structure remains simple, but the detection precision and ability to predict heart failure decompensation are insufficient
Solution Approach 1:
The patent applies dynamics by transitioning from fixed detection thresholds to dynamic, adjustable thresholds. The detection threshold is modified based on the relationship between multiple heart failure variables (e.g., when one variable exceeds its threshold, the threshold for another variable is adjusted), enabling the system to adapt to changing physiological conditions and improve decompensation detection precision without requiring overly complex device architecture.
2Reliability
If early detection of heart failure decompensation is achieved through multiple monitored variables and adjusted thresholds, then detection sensitivity improves, but the complexity of the detection system increases
Solution Approach 1:
The patent implements feedback mechanisms where the monitored heart failure variables continuously inform the adjustment of detection thresholds. When specific variables exceed their respective thresholds, feedback loops trigger modifications to other thresholds in the system, creating a self-regulating monitoring mechanism that improves detection reliability while managing system complexity through automated adaptive control.
Data Source
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AI summary
Heart failure decompensation is detected by sensing at least one physiological signal. Values of at least two different heart failure variables are derived using one or more physiological signals and a threshold for the first heart failure variable is adjusted in response to the value of the second heart failure variable. The value of the first heart failure variable is compared to first threshold for detecting a heart failure condition.