Implantable CRT Optimization Through Wavefront Fusion Analysis
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Solution Overview
Problem
Existing implantable medical devices (IMDs) like pacemakers often use standard settings for cardiac resynchronization therapy (CRT) that may not be optimal for individual patients, leading to suboptimal treatment of electrical dyssynchrony due to the difficulty in measuring and addressing unique patient-specific wavefront fusion and cancellation patterns.
Innovation Solution
A system and method to determine cardiac resynchronization index (CRI) values using measurement electrodes to assess wavefront fusion and cancellation, allowing for individualized optimization of IMD settings by analyzing electrical signals and generating graphical representations for optimal CRT programming.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If standard baseline CRT settings are used in the IMD, then device simplicity and ease of implantation are maintained, but treatment effectiveness and electrical synchronization improvement are suboptimal for individual patients
Solution Approach 1:
The system performs preliminary measurement of electrical dyssynchrony and wavefront fusion/cancellation characteristics during or shortly after implantation. These measurements are used to pre-optimize CRT settings before routine operation, allowing individualized treatment parameters to be established without complicating the implantation procedure itself.
Solution Approach 2:
The system continuously monitors electrical signals from measurement electrodes to detect wavefront fusion and cancellation patterns. This feedback information is processed to dynamically adjust and optimize CRT settings in real-time or near-real-time, improving treatment effectiveness while maintaining device simplicity through automated optimization.
2Reliability
If individualized CRT settings are determined through complex measurement methodologies, then treatment effectiveness is improved, but measurement complexity and clinical implementation difficulty increase
Solution Approach 1:
The measurement electrodes serve multiple functions: they monitor native cardiac electrical signals, detect wavefront fusion patterns, and provide data for optimizing CRT settings. By making the electrodes multi-functional, the system avoids adding separate complex measurement devices while still achieving individualized optimization.
Solution Approach 2:
The system replaces complex mechanical or invasive measurement approaches with non-invasive electrical signal analysis. By using standard ECG-like measurements from surface or intracardiac electrodes and processing them through computational algorithms, the system achieves individualized CRT optimization without complex physical measurement procedures.
3Reliability
If extensive optimization procedures are performed for each patient, then CRT effectiveness is maximized, but time consumption and productivity are reduced
Solution Approach 1:
The system performs self-optimization by automatically analyzing electrical signals and adjusting CRT parameters without requiring extensive manual intervention from clinicians. The device monitors its own performance and wavefront fusion characteristics, then autonomously tunes optimization parameters, significantly reducing the time needed for individualization while maintaining high effectiveness.
Solution Approach 2:
Rather than requiring a single extensive optimization procedure, the system performs periodic, brief measurements and adjustments. By conducting optimized measurements at key time points (e.g., during implantation and periodically thereafter) and using continuous monitoring for fine-tuning, the system achieves maximized effectiveness without the time burden of continuous complex optimization.
Data Source
AI summary
In some examples, a computing apparatus may determine information corresponding to a data structure and indicating delays associated with an atrium lead, a left ventricle (LV) lead, and a right ventricle (RV) lead based on one or more input variables. The computing apparatus may determine a plurality of individualized characteristics based on the information corresponding to the data structure. The computing apparatus may receive, from the plurality of measurement electrodes, a plurality of second sets of electrical measurements indicating second electrical signals applied to the patient's heart based on the plurality of individualized characteristics. The computing apparatus may determine cardiac resynchronization index (CRI) values using a first set of electrical measurements (e.g., native measurements) and the plurality of second sets of electrical measurements. The computing apparatus may generate a graphical representation based on a populated data structure and cause display of the graphical representation.


