SPO2 Respiration Signal Synchronization for Arrhythmia Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional methods for cardiac arrhythmia detection and diagnosis are limited by their reliance on electrophysiological data and waveform morphologies, which require extensive clinical knowledge, are subjective, and fail to efficiently differentiate arrhythmia types and severity, especially in critically ill patients, and are sensitive to noise.
Innovation Solution
A framework that synchronizes saturation of hemoglobin with oxygen (SPO2) signal data with respiration signal data to generate waveform parameters, allowing for the characterization of biological tissue function and early detection of cardiac arrhythmias through SPO2-respiration signal integration, providing quantitative and qualitative analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional electrophysiological signal analysis methods are used for cardiac arrhythmia detection, then the analysis can be performed with standard ECG equipment, but the detection accuracy is reduced due to noise sensitivity and inability to efficiently differentiate arrhythmia types
Solution Approach 1:
The patent combines SPO2 signal data with respiration signal data to create a synchronized multi-parameter analysis framework. This merging of physiological signals allows for more robust arrhythmia detection by cross-validating findings across different signal types, thereby reducing noise sensitivity while maintaining detection accuracy.
Solution Approach 2:
The framework is designed to analyze multiple physiological parameters simultaneously (SPO2, respiration, and other tissue function markers), making it universally applicable to various arrhythmia types and patient conditions. This multi-functional approach enables differentiated diagnosis across various cardiac pathologies while maintaining high reliability.
2Measurement precision
If extensive clinical knowledge and experience are required for accurate interpretation of electrophysiological data, then the analysis can be performed with standard equipment, but the evaluation becomes subjective and time-consuming
Solution Approach 1:
The patent replaces manual, experience-based interpretation of electrophysiological signals with an automated computational framework. The system automatically synchronizes SPO2 and respiration signals, extracts waveform parameters, and generates quantitative assessments, substituting the 'mechanical' process of human expert analysis with an automated digital system that maintains or improves measurement precision.
Solution Approach 2:
The framework transforms qualitative clinical assessment into quantitative parameters by extracting measurable waveform characteristics from the synchronized signals. This parameter transformation enables objective, reproducible arrhythmia characterization without requiring extensive clinical expertise, reducing subjectivity while maintaining precision.
3Ease of operation
If non-invasive blood pressure monitoring is used to observe hemodynamic changes, then the monitoring can be performed without invasive procedures, but the differentiation of various cardiac malfunction arrhythmia types is insufficient
Solution Approach 1:
The patent introduces SPO2 signal data as an intermediary parameter that bridges non-invasive monitoring with detailed arrhythmia characterization. By analyzing the relationship between oxygen saturation waveforms and respiration patterns, the system provides sufficient differentiation of arrhythmia types while maintaining the ease of non-invasive monitoring.
4Loss of time
If conventional ECG and multi-channel intracardiac echocardiography are used for evaluating cardiac rhythm, then the evaluation can be performed with standard cardiac monitoring equipment, but the early detection of circulatory function changes is delayed
Solution Approach 1:
The framework performs preliminary analysis of circulatory function changes through continuous monitoring of SPO2 and respiration signals, which reflect early hemodynamic alterations before they manifest in traditional ECG waveforms. This preliminary detection capability enables earlier intervention while the automated nature of the system keeps the complexity manageable.
Data Source
AI summary
Disclosed herein is a framework for facilitating biological tissue function analysis. In accordance with one aspect, saturation of hemoglobin with oxygen (SPO2) signal data is synchronized with respiration signal data. One or more waveform parameters may be generated based on the synchronized SPO2 signal data and the respiration signal data. One or more respiration-SPO2 parameters may then be determined based on the one or more waveform parameters and used to characterize the biological tissue function.