Electrophysiological LAT Map Correction with Percentile Outlier GUI
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Solution Overview
Problem
Existing electrophysiological mapping techniques, such as LAT maps, are distorted by outlier data points, particularly those with very low or very high values, leading to misleading visualizations and incorrect information about cardiac electrical propagation.
Innovation Solution
A system and method using a graphical user interface (GUI) with percentile range selection and outlier detection algorithms to highlight and remove outlier data points, allowing for the generation of a corrected LAT map.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all data points including outliers are used to generate the LAT map, then the map covers the full range of electrophysiological values, but the visualization becomes distorted and misleading due to outlier influence
Solution Approach 1:
The patent extracts and removes outlier data points from the dataset before generating the LAT map. The system identifies outliers using statistical methods (e.g., data points beyond a certain standard deviation from the mean or outside interquartile range boundaries) and excludes them from the visualization, thereby preventing distortion while maintaining the integrity of the majority of valid data.
Solution Approach 2:
The patent applies different quality standards to different data points based on their statistical properties. Instead of treating all data points uniformly, the system evaluates each point's deviation from the norm and selectively excludes only those that meet outlier criteria, preserving the local quality and accuracy of the LAT map in regions affected by outliers.
2Measurement precision
If manual inspection and correction of outlier data points is performed, then the LAT map accuracy is improved, but the time and complexity of the mapping process increases
Solution Approach 1:
The patent performs preliminary automated identification and flagging of outlier data points before the physician generates or reviews the LAT map. By pre-processing the data to highlight potential outliers, the system reduces the time required for manual inspection and correction, allowing physicians to quickly review and confirm outlier removal without performing exhaustive manual analysis.
Solution Approach 2:
The system provides self-service outlier detection and removal capabilities that automatically process electrophysiological data without requiring extensive manual intervention. The automated algorithms identify, flag, and suggest removal of outliers, enabling the system to service itself in terms of data quality control while minimizing physician workload and time investment.
Data Source
AI summary
A system includes a display device, an input device, and a processor. The processor is configured to (i) receive a set of data points representing a full range of the EP parameter, (ii) responsively to one or more pre-defined percentile ranges, generate a partial-data EP map using only data points belonging to the one or more predefined percentile ranges, (iii) display the partial-data EP map to a user on the display device, (iv) receive from the user, via the input device, a selection on the partial-data EP map of one or more outlier data points belonging to one or more given percentile ranges, (v) regenerate the EP map using the set of data points without the selected outlier data points, and (vi) display the regenerated EP map to the user.