REM-Aware PAP Pressure Modulation for Sleep Apnea
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Solution Overview
Problem
Existing positive airway pressure (PAP) therapy for sleep-disordered breathing conditions, such as obstructive sleep apnea, is ineffective during Rapid Eye Movement (REM) sleep due to muscle atonia, leading to increased airway collapsibility and discomfort, causing arousals, sleep fragmentation, and REM sleep deprivation.
Innovation Solution
A method to determine sleep characteristics by analyzing sleep stage and respiratory event information, adjusting PAP therapy intensity based on REM vs. non-REM ratios and REM occurrence, using sensors and machine learning to optimize therapy for REM-dominant OSA, including respiratory support devices and therapy devices for positional therapy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If high pressure is applied during REM sleep to reduce SDB events, then the number of respiratory events decreases, but subject comfort deteriorates and arousals increase
Solution Approach 1:
The PAP therapy system dynamically adjusts pressure levels based on detected sleep stages. During REM sleep, the system transitions from static high-pressure therapy to dynamic pressure modulation, reducing pressure when muscle atonia is detected to minimize discomfort while maintaining airway patency when needed.
Solution Approach 2:
The system changes the pressure parameter based on sleep stage detection. During REM sleep, pressure settings are modified according to the detected muscle atonia state, transitioning from fixed high pressure to variable pressure levels that adapt to the physiological conditions of different sleep stages.
2Reliability
If high pressure therapy is maintained throughout the night, then SDB events are reduced, but REM sleep duration decreases due to sleep fragmentation
Solution Approach 1:
The therapy is segmented according to sleep stages. The system divides the nighttime therapy into distinct phases based on detected sleep stages (REM vs. non-REM), applying different pressure strategies to each segment. This allows optimized pressure control during REM sleep while preserving REM sleep duration.
Solution Approach 2:
The system implements periodic assessment of sleep stages and respiratory events, adjusting therapy in periodic cycles that align with natural sleep architecture. This periodic action allows the system to respond to transitions between REM and non-REM sleep, maintaining effective SDB control while preserving healthy sleep patterns.
3Object-affected harmful factors
If pressure is reduced during REM sleep to improve comfort, then subject comfort improves, but airway collapsibility increases during muscle atonia
Solution Approach 1:
The system uses feedback from respiratory sensors to monitor airway status in real-time during REM sleep. When muscle atonia is detected and airway collapsibility increases, the system provides feedback-driven pressure adjustments to maintain patency while minimizing discomfort, balancing the competing requirements of comfort and airway support.
Solution Approach 2:
The system introduces an intermediary control mechanism that mediates between the conflicting requirements of comfort and airway support. This intermediary layer monitors physiological parameters and adjusts pressure accordingly, acting as a buffer that allows reduced base pressure during REM sleep while providing supplemental support when airway collapse is detected.
Data Source
AI summary
There is provided a there is a computer program product, comprising instructions which, when executed by a processing system, cause the processing system to carry out a method for determining a sleep characteristic of a subject during a sleep session. The method comprises receiving sleep stage information and respiratory event information. The method comprises determining a REM value and a NREM value based on the sleep stage information and the respiratory event information. The method comprises determining a first ratio between the REM value and the NREM value; determining whether the first ratio exceeds a first threshold; determining a REM occurrence value representative of an amount of REM sleep during the sleep session; and determining whether the REM occurrence value exceeds a second threshold.


