External Computing Device for Electrogram Summary
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Solution Overview
Problem
Implantable medical devices (IMDs) face challenges in accurately classifying cardiac episodes due to artifact signals caused by device faults or failures, leading to misclassification and potential incorrect treatment decisions.
Innovation Solution
An external computing device receives EGM signal data from IMDs, categorizes cardiac episodes, and selects a subset for display based on priority rules, including classification, treatment, and user preferences, to provide a concise summary for clinicians, highlighting relevant episodes and allowing for further analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If IMDs collect and store large amounts of physiological data, then the capacity to analyze and diagnose patient conditions improves, but the complexity of data processing and the risk of misclassification increase
Solution Approach 1:
The patent segments the data processing task by separating IMD-level processing from external computing device processing. The IMD collects and stores raw EGM data, while the external device performs sophisticated algorithms for episode classification and device integrity analysis. This segmentation reduces the processing burden on the IMD while maintaining high analysis capability through external computing resources.
Solution Approach 2:
The patent introduces an external computing device as an intermediary between the IMD and the clinician. This intermediary receives raw EGM data from the IMD, performs complex data processing and analysis algorithms, and presents processed information to the clinician. The intermediary handles the complexity of data processing while the IMD remains focused on data collection.
2Reliability
If IMDs implement sophisticated algorithms to detect and classify cardiac arrhythmia episodes, then the ability to guide therapy improves, but the risk of misclassification due to artifact signals increases
Solution Approach 1:
The patent implements preliminary device integrity monitoring that continuously tracks events characteristic of physiological sensing issues and device impedance changes before they cause misclassification. By detecting potential faults in advance, the system can alert clinicians to investigate specific episodes, reducing the risk of misclassification due to artifact signals.
Solution Approach 2:
The patent establishes a feedback mechanism where the external computing device analyzes device integrity parameters and provides feedback to clinicians about potential sensing issues. This feedback loop allows clinicians to review specific EGM episodes where artifact signals may have caused misclassification, enabling corrective action to be taken.
3Reliability
If external algorithms process EGM data to analyze device integrity and classify episodes, then the ability to identify device issues improves, but the time required for data transfer and processing increases
Solution Approach 1:
The patent performs preliminary device integrity monitoring within the IMD itself, continuously tracking sensing issues and impedance changes. This preliminary action means that when data is transferred to the external computing device, the integrity data is already prepared and ready for immediate analysis, reducing the processing time required after data transfer.
Solution Approach 2:
The patent segments the analysis process into two phases: preliminary integrity monitoring performed by the IMD during normal operation, and comprehensive data analysis performed by the external computing device after data transfer. This segmentation allows time-efficient processing by performing basic integrity checks continuously while reserving intensive analysis for when data is available.
4Measurement precision
If clinicians review all cardiac episodes in detail, then the accuracy of analysis improves, but the time required for review increases
Solution Approach 1:
The patent extracts and presents only the most relevant EGM episodes to the clinician by using external algorithms to pre-filter and prioritize data based on device integrity status and episode characteristics. This extraction approach allows clinicians to review only the critical episodes that require their attention, reducing review time while maintaining analysis precision for those episodes.
Solution Approach 2:
The patent performs preliminary sorting and prioritization of EGM episodes by the external computing device before presentation to the clinician. Episodes are pre-organized based on device integrity issues detected during monitoring and other relevant criteria, so that when the clinician reviews the data, it is already arranged in order of importance, reducing the time needed for thorough review.
Data Source
AI summary
The present disclosure is directed to an electrogram summary. In various examples, a subset of cardiac episodes are selected and displayed based on a set of summary rules. The subset of cardiac episodes includes at least one episode from each of a plurality of episode categories with at least one cardiac episode. In some examples, the order in which the cardiac episodes selected are displayed is based on the set of summary rules. The electrogram summary may include images or information regarding each of the selected cardiac episodes.