Cloud-Based EP Data Integration for ECG and Vital Sign Analysis
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Solution Overview
Problem
Conventional systems for cardiovascular monitoring and electrophysiology procedures face limitations in collecting, storing, and analyzing large datasets from multiple disparate systems, which hinders robust analysis and decision-making for cardiologists.
Innovation Solution
A cloud-based system that seamlessly collects and analyzes cardiovascular data before, during, and after electrophysiology procedures, integrating with body-worn and implanted devices, using algorithm-based tools to process ECG waveforms and vital signs, and generate reports for clinicians.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional systems collect and store cardiovascular data from multiple disparate systems, then the quantity of data increases, but the ability to perform robust analysis deteriorates due to system incompatibility and data fragmentation
Solution Approach 1:
The patent merges data from multiple disparate monitoring systems (ECG, vital signs, implanted devices) into a unified cloud-based database. This integration allows comprehensive data collection while maintaining analysis reliability through standardized data structures and centralized processing, directly resolving the contradiction between data quantity and analysis reliability
Solution Approach 2:
The system creates a universal platform that can process and analyze data from various sources (holter monitors, event monitors, implanted devices, vital sign monitors) through a common interface. This multi-functional approach enables robust analysis of heterogeneous data types, allowing the system to handle increasing data quantities without compromising analysis quality
2Adaptability or versatility
If conventional systems use multiple disparate monitoring systems, then the variety of data sources increases, but the complexity of data integration and analysis increases
Solution Approach 1:
The patent introduces a cloud-based server as an intermediary between diverse monitoring systems and analysis tools. This intermediary layer handles data standardization, storage, and processing, simplifying the integration complexity while maintaining versatility in accepting data from multiple sources including ECG monitors, vital sign monitors, and implanted devices
Solution Approach 2:
The system transitions from local, system-specific data processing to a cloud-based dimension, elevating the architecture to handle multiple data sources simultaneously. This dimensional shift allows complex integration tasks to be performed centrally, reducing the complexity burden on individual monitoring systems while maintaining high adaptability
3Loss of information
If comprehensive cardiovascular data is collected before, during, and after EP procedures, then the completeness of patient characterization improves, but the time required for data processing and analysis increases
Solution Approach 1:
The system performs preliminary data collection and storage in a standardized cloud-based format before EP procedures, during procedures, and after procedures. By pre-organizing data structures and maintaining continuous data availability in a centralized repository, the system enables rapid retrieval and analysis without time loss, resolving the contradiction between information completeness and processing time
Data Source
AI summary
The invention provides a system for evaluating a patient featuring: 1) an ECG-measuring system connected to the patient and configured to sense ECG information from the patient; 2) a data-acquisition system interfaced to a vital sign-monitoring system configured to sense vital sign information from the patient during an electro-physiology (EP) procedure; and 3) an external software system interfaced to both systems. The external software system includes a first software interface that receives ECG information measured from the patient by the ECG-measuring system, and a second software interface that receives vital sign and EP-related information from the data-acquisition system measured from the patient during an EP procedure. A database stores physiological and EP-related information measured from the patient before, during, and after the EP procedure. And an algorithm interfaced with the database determines an efficacy of the EP procedure by collectively analyzing information measured during each of these phases.