Automated Sensing Vector Selection in Implantable Cardiac Devices
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Solution Overview
Problem
Implantable cardiac stimulus devices face challenges in selecting optimal sensing vectors for cardiac event detection, requiring operator input and increasing the risk of using sub-optimal vectors due to the complexity of vector selection and potential changes in patient physiology.
Innovation Solution
An automated method for analyzing available sensing vectors to select a suitable vector for cardiac event detection, which includes characterizing detected events, assessing signal quality, and requesting operator input when necessary, to determine the best vector for cardiac signal sensing without relying on operator intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If automated sensing vector selection is implemented, then operator input is reduced and selection efficiency is improved, but the device complexity increases due to the need for automated analysis algorithms
Solution Approach 1:
The patent applies preliminary action by performing automated sensing vector analysis during device initialization or programming sessions, before clinical use begins. The system pre-evaluates multiple sensing vectors using automated algorithms to identify optimal vectors, storing these selections for subsequent use without requiring operator intervention during actual cardiac monitoring. This resolves the contradiction by automating the complex analysis upfront while keeping the operational device simple.
Solution Approach 2:
The patent implements self-service through automated algorithms that independently evaluate sensing vector quality without operator input. The system uses built-in computational resources to automatically analyze signal characteristics, assess vector suitability, and select optimal sensing configurations. This self-automated approach reduces dependency on operator expertise while managing device complexity through integrated software solutions.
2Reliability
If multiple sensing vectors are analyzed to ensure optimal detection, then detection reliability is improved, but the time required for vector selection increases
Solution Approach 1:
The patent applies preliminary action by conducting comprehensive analysis of multiple sensing vectors during initialization or programming sessions, well before clinical deployment. The system evaluates all available vectors, compares their suitability for detecting specific cardiac events, and pre-selects optimal configurations. This upfront analysis ensures detection reliability is established in advance, eliminating time consumption during actual patient monitoring and treatment.
Solution Approach 2:
The patent implements partial action by analyzing only the most promising sensing vectors based on preliminary criteria, rather than exhaustively evaluating every possible vector configuration. The system uses initial signal quality metrics to filter and prioritize vectors, then performs detailed analysis only on top candidates. This selective approach maintains high detection reliability while significantly reducing the time required for vector selection.
3Ease of operation
If automated analysis algorithms are used to evaluate sensing vectors, then operator expertise requirements are reduced, but the computational resources required increase
Solution Approach 1:
The patent applies preliminary action by performing computationally intensive automated sensing vector analysis during initialization or programming sessions when the device is not actively monitoring or treating the patient. The system uses this offline computational effort to pre-determine optimal vectors, storing results for rapid retrieval during clinical use. This timing strategy reduces real-time energy consumption while maintaining ease of operation through automated decision-making.
Solution Approach 2:
The patent implements partial action by using simplified evaluation criteria and analyzing only a subset of the most promising sensing vectors, rather than performing exhaustive computational analysis on all possible vectors. The system applies basic signal quality metrics to quickly filter vectors, then performs more detailed analysis only on top candidates. This selective computational approach reduces energy consumption while still providing automated ease of operation for vector selection.
Data Source
AI summary
Methods and devices for sensing vector analysis in an implantable cardiac stimulus system. In an illustrative example, a first sensing vector is analyzed to determine whether it is suitable, within given threshold conditions, for use in cardiac event detection and analysis. If so, the first vector may be selected for detection and analysis. Otherwise, one or more additional vectors are analyzed. A detailed example illustrates methods for analyzing sensing vectors by the use of a scoring system. Devices adapted to perform these methods are also discussed, including implantable medical devices adapted to perform these methods, and systems comprising implantable medical devices and programmers adapted to communicate with implantable medical devices, the systems also being adapted to perform these methods. Another example includes a programmer configured to perform these methods including certain steps of directing operation of an associated implanted or implantable medical device.