Lead Condition Detection via Non-Sustained Tachyarrhythmia Analysis
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Solution Overview
Problem
Implantable medical devices, such as cardiac pacemakers and defibrillators, face issues with lead-related conditions like intermittent connections, short circuits, and impedance changes due to mechanical stresses and movement, affecting sensing and stimulation integrity.
Innovation Solution
The system analyzes cardiac electrical signals during non-sustained tachyarrhythmias to determine metrics such as R-R interval durations, identifying lead-related conditions and triggering alerts or therapy modifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If implantable medical devices are used to deliver electrical stimulation and monitor physiological conditions, then therapeutic benefits are achieved, but lead-related conditions such as intermittent connections, short circuits, and impedance changes occur due to mechanical stresses and patient movement
Solution Approach 1:
The system performs preliminary analysis of cardiac electrical signals during non-sustained tachyarrhythmias to calculate metrics such as average R-R interval durations. This advance detection and calculation of lead-related conditions allows the system to identify issues before they compromise sensing and stimulation integrity, enabling preventive action rather than reactive response.
2Reliability
If the device continuously monitors cardiac signals to detect lead-related conditions, then sensing integrity is maintained, but energy consumption increases
Solution Approach 1:
Instead of continuous monitoring, the system employs periodic analysis of cardiac electrical signals specifically during non-sustained tachyarrhythmia events. This periodic approach triggered by specific cardiac conditions reduces overall energy consumption while maintaining reliable detection capability for lead-related conditions during critical periods when arrhythmias occur.
Solution Approach 2:
The system changes operational parameters by analyzing signal characteristics specifically during tachyarrhythmia states rather than during normal sinus rhythm. This parameter-based approach focuses computational resources on periods when lead-related conditions are most likely to manifest, reducing energy consumption during normal operation while maintaining high reliability during critical events.
3Loss of time
If metrics are calculated from cardiac electrical signals during non-sustained tachyarrhythmias to identify lead-related conditions, then timely detection is achieved, but device complexity increases
Solution Approach 1:
The system extracts and focuses analysis on specific, critical parameters from cardiac electrical signals during non-sustained tachyarrhythmias, such as average R-R interval durations. By taking out only the essential metrics needed for lead-related condition detection rather than analyzing all signal characteristics, the system achieves timely detection while limiting the increase in device complexity to only the necessary computational functions.
Data Source
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AI summary
Techniques for determining whether a lead related condition exists based on analysis of a cardiac electrical signal associated with a non-sustained tachyarrhythmia (NST) are described. In some examples, the techniques include determining the duration of intervals between consecutive cardiac events, e.g., R-R intervals, during an NST. The techniques may further include determining one or more metrics based on the durations of the intervals during the NST. Examples of metrics include an average, a minimum, a maximum, a range, a median, a mode, or a mean. A lead related condition is identified based on the values of the one or more metrics, e.g., by comparison to respective thresholds. In some examples, an alert is provided or a therapy modification is suggested if a lead related condition is identified.