Pulse Oximeter Oxygen Saturation Analysis for Sleep Apnea Detection
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Solution Overview
Problem
Current methods for detecting obstructive sleep apnea, such as polysomnography, are expensive and difficult to implement on a large scale, and alternative diagnostic approaches that do not require polysomnography or specific event analysis are needed to identify unstable oxygen saturation and associated health risks.
Innovation Solution
A method using a pulse oximeter to analyze statistical properties of oxygen saturation values, calculating metrics like the ratio of saturation changes over different intervals, and determining relationships to detect cyclic saturation variations, which can indicate obstructive sleep apnea or hypopnea, with outputs such as alarms or reports to alert healthcare providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If polysomnography is used to detect obstructive sleep apnea, then detection accuracy is improved, but cost and implementation difficulty increase
Solution Approach 1:
The patent extracts only the essential oxygen saturation measurement function from the complex polysomnography system. By using a simple pulse oximeter to monitor SpO2 levels and analyzing the statistical properties of these measurements, the system detects cyclic saturation variations indicative of sleep apnea without requiring the full array of polysomnography sensors and procedures.
Solution Approach 2:
The patent replaces expensive, complex polysomnography equipment with inexpensive, widely available pulse oximeters. The system uses standard pulse oximetry technology that is already present in many clinical settings, eliminating the need for specialized sleep laboratory equipment while maintaining diagnostic capability.
2Measurement precision
If conventional polysomnography is implemented, then diagnostic capability is improved, but scalability and widespread use deteriorate
Solution Approach 1:
The patent creates a universal detection method that can be implemented using standard pulse oximeters already present in diverse clinical settings. The statistical analysis algorithm works with SpO2 data from any pulse oximeter, making the system universally applicable across different healthcare facilities without requiring specialized equipment or extensive training.
Solution Approach 2:
The system automatically analyzes oxygen saturation data using statistical metrics and algorithms that detect cyclic variations. The automated processing eliminates the need for manual review of sleep studies by specialists, allowing clinics to screen for sleep apnea without additional human resources while maintaining diagnostic accuracy.
3Ease of operation
If statistical metrics are calculated from oxygen saturation data, then detection simplicity is improved, but sensitivity to artifacts worsens
Solution Approach 1:
The patent incorporates signal quality metrics as feedback to the statistical analysis process. The system evaluates the reliability of SpO2 measurements and adjusts or excludes data points that show signs of artifacts such as motion interference or poor perfusion, thereby maintaining detection simplicity while improving reliability by filtering out false positives.
Data Source
AI summary
Methods and systems are described for simplified detection of unstable oxygen saturation of a patient by analysis of statistical variations in blood oxygen. One method for automatic detection of unstable oxygen saturation of a patient using a pulse oximeter comprises receiving at least a single time series input of oxygen saturation values and computing at least two metrics based on statistical properties of the single time series input of the oxygen saturation values.