Electrode Effectiveness Identification via Signal Correlation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing electrode systems for cardiac therapy face challenges in identifying effective electrodes for sensing signals and delivering therapy due to issues like improper contact or damaged connections, leading to ineffective signal transmission and therapy delivery.
Innovation Solution
A system and method that utilize a computing apparatus to perform effectiveness tests on electrodes by monitoring signals over a preset time period, calculating correlation values such as Pearson correlation coefficients, and comparing signal portions to determine electrode effectiveness, enabling or disabling electrodes based on threshold values, and using spatial or morphological features to assess electrode performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple electrodes are used for sensing signals and delivering therapy, then the coverage and potential effectiveness increase, but the difficulty of identifying effective electrodes and ensuring reliable operation increases
Solution Approach 1:
The system performs self-diagnosis by automatically evaluating electrode effectiveness through signal analysis. The computing apparatus compares signals from multiple electrodes and autonomously identifies which electrodes are effective without requiring manual testing or external intervention, allowing the system to self-assess its own operational status
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring signals from electrodes and using this information to determine electrode effectiveness. The comparison of signals between different electrodes provides feedback that enables the system to identify effective electrodes and adjust operation accordingly
2Productivity
If manual evaluation of electrode effectiveness is performed, then operator control is maintained, but the time required and operator input needed increase
Solution Approach 1:
The patent replaces manual mechanical evaluation processes with automated computational analysis. The computing apparatus uses algorithms to automatically compare signals and determine electrode effectiveness, substituting human operator actions with automated electronic processing that occurs rapidly without manual intervention
Solution Approach 2:
The system performs preliminary evaluation of electrode effectiveness automatically before clinical use. By pre-assessing which electrodes are effective through automated signal comparison, the system prepares the configuration in advance, eliminating the need for time-consuming manual evaluation during patient procedures
3Measurement precision
If signal analysis is performed to determine electrode effectiveness, then accurate identification is achieved, but the computational processing requirements increase
Solution Approach 1:
The system performs partial signal analysis by focusing computational resources on comparing specific signal characteristics between electrodes rather than analyzing entire signal waveforms. This selective approach achieves sufficient precision for electrode effectiveness determination while reducing overall computational energy requirements
Data Source
AI summary
Systems, methods, and interfaces are described herein for identification of effective electrodes to be used in sensing and/or therapy. Two or more portions of a signal monitored using an electrode may be compared to determine whether the electrode is effective. The two or more portions may correspond to the same portion or window of a cardiac cycle. Further, signals from a first electrode and from a second electrode located proximate the first electrode may be compared to determine whether one or both of the electrodes are effective.