Closed-Loop Cardiac Resynchronization Therapy System
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Solution Overview
Problem
Current methods for providing cardiac resynchronization therapy (CRT) lack quantitative assessments of heart function, relying on qualitative and operator-dependent mechanical and electrical measures, which are insufficient for precise pacing site determination and parameter setting due to the complex nature of ventricular activation.
Innovation Solution
A system that analyzes electrical data from multiple sensors to compute quantitative indices of heart function, such as synchrony, using a combination of sensor arrays, geometry data, and image processing to adjust therapy parameters in a closed-loop feedback manner, allowing for precise delivery of CRT based on real-time functional assessments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If qualitative and operator-dependent mechanical and electrical measures are used to assess heart function, then the assessment process is simple, but the measurement precision and reliability are insufficient for precise pacing site determination
Solution Approach 1:
The system segments the heart into multiple regions of interest (ROIs) and places virtual electrodes at specific locations within each ROI. Electrical data is then acquired and analyzed separately for each region, allowing quantitative assessment of regional cardiac function and synchrony. This segmentation enables precise localization of pacing sites based on regional electrical activity patterns.
Solution Approach 2:
The system introduces virtual electrodes as intermediary elements that are not physically implanted but are computationally defined on the cardiac surface. These virtual electrodes serve as mediators to capture and analyze electrical activity from multiple cardiac regions simultaneously, providing quantitative data without requiring complex physical sensor arrays on the heart surface.
2Measurement precision
If multiple sensors and complex analysis methods are implemented to achieve quantitative assessment, then measurement precision improves, but ease of operation decreases due to operator dependency
Solution Approach 1:
The system implements closed-loop feedback by continuously analyzing electrical data from virtual electrodes and using the quantitative results to automatically adjust therapy parameters. The analysis system computes functional assessments and feeds this information back to the therapy delivery system, enabling automated pacing parameter optimization based on real-time cardiac function assessment, thereby reducing operator dependency.
Solution Approach 2:
The system automatically changes therapy parameters (pacing amplitude, pulse width, rate, and timing intervals) based on quantitative analysis of electrical data. The analysis system identifies optimal parameter settings that maximize cardiac synchrony and function, automatically adjusting these parameters without requiring manual operator intervention, thus improving ease of operation while maintaining high measurement precision.
3Reliability
If electrical data is analyzed at multiple iterations with parameter adjustments, then therapy effectiveness improves, but loss of time increases due to repeated measurements and adjustments
Solution Approach 1:
The system performs preliminary analysis by computing functional assessments from electrical data acquired at multiple iterations before finalizing therapy parameter adjustments. By analyzing trends and patterns across multiple measurement iterations, the system can predict optimal parameter settings in advance, reducing the time required for final optimization while ensuring reliable therapy effectiveness.
Solution Approach 2:
The system maintains continuous analysis of electrical data throughout the therapy delivery process, rather than performing discrete batch analyses. This continuous monitoring and adjustment approach allows the system to track cardiac function in real-time and make incremental parameter optimizations, reducing overall procedure time while maintaining high therapy reliability through constant feedback.
Data Source
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AI summary
A method can include providing (302) at least one parameter to control a therapy that is applied to at least one internal anatomical structure of a patient. Electrical data can be obtained from the patient (304), including electrical data acquired via a plurality of sensors during each of a plurality of iterations of the therapy. The electrical data can be analyzed (306) for a respective value of the at least one parameter of the therapy at each of the plurality of iterations of the applied therapy to compute an indication of at least one function of the at least one internal anatomical structure of the patient at each respective iteration of the applied therapy. The computed indication can be stored in memory (308). At least one parameter of the therapy can be adjusted (310) for delivery in a subsequent one of the plurality of iterations based on the indication of the at least one function.