Optimal Electrical Vector Selection for Cardiac Pacing
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Solution Overview
Problem
Current systems for delivering cardiac therapy using electrodes lack the ability to efficiently identify optimal electrical vectors for pacing, which affects the longevity and effectiveness of the therapy, leading to suboptimal cardiac function improvement.
Innovation Solution
The system configures multiple electrodes to deliver pacing therapy using various configurations, generates cardiac improvement information, and selects optimal electrical vectors based on longevity data, ensuring effective cardiac function enhancement while minimizing phrenic nerve stimulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple pacing configurations are tested to identify optimal electrical vectors, then cardiac function improvement is enhanced, but the time and complexity of therapy setup increases
Solution Approach 1:
The system performs preliminary testing of multiple pacing configurations during the implantation procedure to identify optimal electrical vectors before final device activation. This preliminary action allows the system to evaluate different electrode combinations and select the best configuration for each patient's anatomy, ensuring optimal cardiac function improvement while establishing the configuration selection before the device begins long-term operation.
Solution Approach 2:
The system uses feedback from measured cardiac response to each pacing configuration to automatically select the optimal electrical vectors. By monitoring parameters such as ventricular activation timing and mechanical contraction effectiveness, the system receives real-time feedback on which configurations produce the best cardiac function improvement, allowing for data-driven selection that balances effectiveness with efficient setup time.
2Reliability
If higher energy pacing vectors are used to improve cardiac function, then therapy effectiveness increases, but battery longevity decreases
Solution Approach 1:
The system changes the parameters of the pacing vectors by evaluating multiple electrical configurations with different energy requirements. By measuring the cardiac response to each configuration and selecting those that achieve therapeutic effect with lower energy consumption, the system optimizes the balance between therapy effectiveness and battery longevity. This involves adjusting vector orientation, electrode selection, and pacing amplitude to find the most energy-efficient effective configurations.
3Ease of operation
If electrical vectors are selected without considering longevity information, then implementation is simpler, but battery life is reduced
Solution Approach 1:
The system performs self-service by automatically evaluating multiple pacing configurations and selecting optimal electrical vectors based on both cardiac function improvement and energy consumption characteristics. Rather than requiring manual selection by the operator, the device autonomously tests different configurations, measures their effectiveness, and identifies those that provide the best balance between therapeutic benefit and energy efficiency, thereby extending battery life while maintaining ease of operation.
4Object-affected harmful factors
If optimal electrical vectors are identified through comprehensive testing, then phrenic nerve stimulation is reduced, but the complexity of the implantation procedure increases
Solution Approach 1:
The system uses feedback from monitoring phrenic nerve stimulation during pacing configuration testing to automatically adjust and select optimal electrical vectors. By detecting phrenic nerve capture and using this information to eliminate configurations that cause harmful stimulation, the system reduces the need for manual adjustment and complex procedural modifications. The feedback mechanism allows the device to self-optimize, reducing phrenic nerve stimulation while keeping the implantation procedure manageable through automated decision-making.
Data Source
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AI summary
Systems, methods, and graphical user interfaces are described herein for identification of optimal electrical vectors for use in assisting a user in implantation of implantable electrodes to be used in cardiac therapy. Cardiac improvement information may be generated for each pacing configuration, and one or more pacing configuration may be selected based on the cardiac improvement information. Optimal electrical vectors using the selected pacing configurations may be identified using longevity information generated for each electrical vector. Electrodes may then be implanted for use in cardiac therapy to form the optimal electrical vector.