ECG Activity Visualization With Time-Aligned Clinical Event Filtering
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Solution Overview
Problem
Current ECG data visualization systems fail to present cardiac medical data in a coordinated, clinically relevant manner at differing levels of granularity, often requiring unintuitive steps to highlight clinically important points, and do not effectively relate ECG data to activity intensity, making it difficult for clinicians to correlate these data.
Innovation Solution
An interactive user interface that allows independent sorting and filtering of ECG and activity data within different sections, aligning them in time and intensity to provide contextual displays, enabling intuitive navigation and visualization of clinically relevant events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If current ECG data visualization approaches are used, then data can be displayed, but data marks are not presented in a coordinated, clinically relevant fashion at differing levels of granularity
Solution Approach 1:
The data visualization is segmented into multiple hierarchical levels (overview level, detailed level, and event-specific level), allowing clinicians to navigate from broad temporal contexts to specific clinically relevant events. Each level displays data marks with appropriate granularity, preventing information loss while maintaining ease of navigation through progressive disclosure of details.
Solution Approach 2:
The system adds a temporal dimension to data visualization by displaying ECG data, activity data, and symptom data aligned in time across different sections. This temporal alignment allows clinicians to correlate events across multiple data types without losing clinical context, while the hierarchical structure provides another dimensional organization for intuitive navigation.
2Loss of information
If manual filtering and sorting steps are required to produce desired data visualization, then data can be organized, but the process becomes complex and time-consuming
Solution Approach 1:
The system performs preliminary organization and alignment of ECG data, activity data, and symptom data before presentation to the clinician. Data marks are pre-sorted by temporal alignment and clinical relevance, and hierarchical structures are pre-computed, eliminating the need for manual filtering and sorting steps while preserving complete clinical context.
Solution Approach 2:
The system introduces an intermediary processing layer that automatically correlates ECG events with corresponding activity and symptom data based on temporal alignment. This intermediary layer handles the complex data integration and sorting operations, preserving clinical context while eliminating time-consuming manual processing steps for the clinician.
3Loss of information
If ECG data and activity data are displayed separately, then each data type can be visualized, but correlation between ECG events and activity intensity is difficult
Solution Approach 1:
The system merges ECG data, activity data, and symptom data into a unified temporal framework where all data types are aligned and displayed in coordinated sections. This merging allows direct correlation between ECG events and activity intensity while maintaining organized, sectioned displays that do not overwhelm the clinician with excessive complexity.
Solution Approach 2:
Different sections of the visualization are optimized for their specific data types while maintaining temporal alignment. The ECG section displays cardiac waveforms with appropriate detail, the activity section shows intensity levels, and the symptom section captures patient reports. Each section has tailored visualization quality while contributing to the overall correlated view, balancing information completeness with manageable complexity.
Data Source
AI summary
An embodiment includes a system having an ambulatory patient sensor, such as a cardiac sensor, that provides data via a network to remote device configured to prepare and display interactive user interface(s) used for visualizing data, for example in an interactive web application. The interactive user interface(s) are provided with interactive element(s) configured to support data sort or filtering operations for visualizing patient metrics and data activity included in the data visualization. In an embodiment, the interactive user interfaces provide different filtered views of the data responsive to user interaction for easily transitioning between data visualizations in an intuitive manner.