Respiratory Flow Sleep Staging for CPAP Therapy Assessment
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Solution Overview
Problem
Existing respiratory disorder treatments, such as CPAP therapy, face issues with patient compliance due to discomfort, difficulty of use, aesthetics, and inefficiencies in monitoring sleep stages, leading to inaccurate assessment of therapy efficacy.
Innovation Solution
A method and apparatus for inferring sleep stages from respiratory flow rate signals, using multiple detection pathways to generate and prioritize sleep stage events, and combining these to produce a more accurate hypnogram for CPAP therapy patients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional respiratory pressure therapy devices are used, then therapy delivery is achieved, but sleep stage inference accuracy is insufficient leading to underestimated apnea-hypopnea index calculations
Solution Approach 1:
The patent segments the sleep staging process into multiple detection pathways (e.g., respiratory event pathway, breathing stability pathway) that independently analyze different aspects of respiratory signals. Each pathway detects specific sleep stage indicators, and their results are combined to produce a comprehensive sleep stage inference, thereby improving measurement precision without losing therapeutic assessment information.
2Device complexity
If simple sleep stage detection methods are used, then device complexity is reduced, but therapy efficacy assessment becomes suboptimal
Solution Approach 1:
The patent implements dynamic adjustment of therapy pressure based on real-time sleep stage detection. The system continuously monitors respiratory signals, dynamically identifies sleep stages through multiple detection pathways, and adjusts CPAP pressure accordingly. This dynamic approach maintains reliability of therapy efficacy assessment while managing device complexity through adaptive algorithms.
Solution Approach 2:
The system incorporates feedback loops where sleep stage detection results are fed back to adjust therapy delivery. The detection of sleep stages provides feedback that informs pressure adjustments, creating a closed-loop control system that improves therapy efficacy assessment reliability without requiring overly complex standalone detection mechanisms.
Data Source
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AI summary
Methods and apparatus infer or indicate wakefulness stages(s) of a patient from a respiratory flow rate signal of the patient. The method of indicating wakefulness of a patient may comprise applying, in a wakefulness detector of one or more processors, first and second parallel detection pathways to breath features derived from a signal representing a respiratory flow rate of the patient, in each of the first and second parallel detection pathways, assessing the breath features, wherein the first parallel detection pathway is configured to evaluate variation in a short term and wherein the second parallel detection pathway is configured to evaluate variation in a long term; and generating, from the wakefulness detector of the one or more processors, start events and end events from the evaluations of the first parallel detection pathway and the second parallel detection pathway to produce indications of wakefulness of the patient.