Internet-Based ECG T-Wave Analysis System for Cardiac Abnormality Detection
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Solution Overview
Problem
Current electronic medical record (EMR) systems are limited in their ability to collect and process large datasets from diverse systems used in cardiovascular procedures, such as electrophysiology (EP) procedures, making it difficult to analyze data from before, during, and after the procedures, which hinders the development of new therapies and treatment protocols.
Innovation Solution
An Internet-based system that seamlessly collects cardiovascular data from patients before, during, and after EP procedures, integrating with body-worn monitors and implanted devices, and utilizes a data-analytics module with algorithms to analyze large datasets, providing a GUI for clinicians to improve patient management and facilitate virtual clinical trials.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional EMR systems are used to collect cardiovascular data, then data collection from diverse systems is limited, but system complexity and integration requirements increase when attempting to analyze large datasets from multiple sources
Solution Approach 1:
The system segments data collection from different sources (body-worn monitors, implanted devices, EP procedure systems) into separate modular components that each interface with the central EMR through standardized protocols. This allows diverse data sources to be integrated without increasing overall system complexity, as each segment operates independently but connects through a common interface layer.
Solution Approach 2:
The EMR system implements universal data collection capabilities that can handle multiple types of cardiovascular data from various sources using a single integrated platform. The system is designed to accommodate body-worn monitors, implanted devices, and EP procedure systems through common data interfaces and standardized data structures, eliminating the need for separate specialized systems for each data source.
2Loss of information
If large datasets are collected from before, during, and after EP procedures, then analysis capability improves, but data processing time and computational resources increase
Solution Approach 1:
The system performs preliminary data processing and validation during data collection from body-worn monitors, implanted devices, and EP procedure systems. Data are cleaned, formatted, and pre-analyzed as they are entered into the EMR, reducing the computational burden during subsequent comprehensive analyses and enabling faster processing of large datasets while maintaining complete information.
3Measurement precision
If comprehensive ECG waveform analysis is performed to detect cardiac abnormalities, then diagnostic accuracy improves, but computational complexity and analysis time increase
Solution Approach 1:
The system applies different levels of analysis complexity to different portions of the ECG waveform based on local characteristics. Specific algorithms are targeted at identifying particular abnormality patterns (such as T-wave abnormalities) in relevant segments of the waveform, rather than applying uniform complex analysis to the entire signal. This maintains high diagnostic accuracy for specific conditions while reducing overall computational complexity.
Data Source
AI summary
The present invention provides an improved, Internet-based system that seamlessly collects cardiovascular data from a patient before, during, and after a procedure for EP or an ID. During an EP procedure, the system collects information describing the patient's response to PES and the ablation process, ECG waveforms and their various features, HR and other vital signs, HR variability, cardiac arrhythmias, patient demographics, and patient outcomes. Once these data are collected, the system stores them on an Internet-accessible computer system that can deploy a collection of user-selected and custom-developed algorithms. Before and after the procedure, the system also integrates with body-worn and/or programmers that interrogate implanted devices to collect similar data while the patient is either ambulatory, or in a clinic associated with the hospital. A data-collection/storage module, featuring database interface, stores physiological and procedural information measured from the patient.