Sleep Apnea Detection via Stage-Adaptive Algorithm Selection
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Solution Overview
Problem
Current methods for diagnosing sleep apnea are costly, resource-intensive, and often result in under-diagnosis due to the limited availability of sleep laboratories, and existing algorithms struggle to accurately detect apnea events without considering the physiological condition of the subject during sleep.
Innovation Solution
A system utilizing physiological sensors to generate signals for sleep apnea detection, which includes a processor that determines sleep stages and selects appropriate detection algorithms based on heart rate variability features to improve the accuracy of apnea event detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional polysomnography methods are used for sleep apnea diagnosis, then diagnostic accuracy is improved, but cost and resource requirements increase significantly
Solution Approach 1:
The patent extracts and focuses on specific critical parameters (heart rate variability features, oxygen saturation, respiratory effort) from the complete polysomnography protocol, using these extracted signals to detect apnea events without requiring the full array of sleep laboratory equipment and personnel
Solution Approach 2:
The patent creates a simplified model of sleep apnea detection that copies the essential diagnostic functionality from traditional polysomnography using alternative, less resource-intensive methods (e.g., using heart rate variability as a proxy for direct respiratory monitoring)
2Measurement precision
If sleep stage information is incorporated into detection algorithms, then apnea detection accuracy is improved, but algorithm complexity increases
Solution Approach 1:
The patent segments the detection process into distinct stages: first determining sleep stage from physiological signals, then selecting appropriate detection algorithms based on the identified stage. This segmentation allows the system to handle different physiological states with stage-appropriate methods, improving accuracy while managing complexity through modular processing
Solution Approach 2:
The patent performs preliminary classification of sleep stages before applying specific apnea detection algorithms. By pre-determining the physiological state, the system can select the most appropriate detection method for that state, avoiding the need for a single complex algorithm to handle all scenarios
3Reliability
If multiple sensor sources are used for comprehensive monitoring, then detection reliability is improved, but device complexity and cost increase
Solution Approach 1:
The patent makes the physiological signals multi-functional by extracting multiple types of information from the same sensor sources. For example, heart rate variability signals are used both for sleep stage classification and for apnea event detection, eliminating the need for separate dedicated sensors for each function
Data Source
AI summary
A method and system for detecting sleep apnea involves determining the sleep stage, and detecting an apnea event based on a physiological sensor signal using selection of a detection algorithm which is dependent on the determined sleep stage. By taking account of the sleep stage when performing an automated apnea detection process, the accuracy of the apnea detection is improved.