Respiratory Support Systems for Detecting PAP Sleep Misperception
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Solution Overview
Problem
Existing PAP therapy for sleep-disordered breathing conditions causes discomfort, leading to high dropout rates due to sleep misperception, where subjects believe they are sleeping less than they actually are, which can result in anxiety and reduced adherence to therapy.
Innovation Solution
A computer-implemented method to determine sleep misperception by combining sleep condition information, such as SDB and insomnia data, with sleep quality information, using questionnaires and physiological signals to calculate a sleep misperception index, allowing for adjustments to PAP therapy based on accurate sleep perception.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If PAP therapy is provided to treat SDB conditions, then airway patency is improved, but subject comfort deteriorates leading to sleep misperception and high dropout rates
Solution Approach 1:
The system continuously monitors objective sleep parameters (sleep time, respiratory events) and compares them with subjective patient reports to detect sleep misperception. This feedback loop enables identification of the contradiction between therapy effectiveness and patient comfort, allowing for timely intervention and therapy adjustment.
Solution Approach 2:
The system adjusts PAP therapy parameters (pressure levels, ramp time, etc.) based on detected sleep misperception patterns. By changing these parameters, the system maintains airway patency while reducing discomfort that causes sleep misperception, thereby resolving the technical contradiction.
2Duration of action of stationary object
If sleep misperception is not detected, then therapy continues unchanged, but subject adherence deteriorates due to anxiety and perceived insufficient sleep
Solution Approach 1:
The system provides continuous feedback to both patients and clinicians about objective versus subjective sleep measurements. This feedback corrects sleep misperception by showing patients their actual sleep performance, reducing anxiety and improving adherence while maintaining therapy continuity.
Solution Approach 2:
The system acts as an intermediary between objective sleep monitoring and subjective patient perception. By providing this intermediate information layer, it bridges the gap between actual therapy effectiveness and patient understanding, preventing adherence deterioration.
3Object-affected harmful factors
If subjective sleep perception is used to guide therapy, then patient comfort is improved, but measurement accuracy deteriorates due to bias and anxiety
Solution Approach 1:
The system merges objective sleep monitoring data with subjective patient reports to create a comprehensive assessment. This combination leverages the strengths of both approaches: objective data provides accurate measurement while subjective data provides context about patient experience and comfort.
Solution Approach 2:
The system serves multiple functions simultaneously: it monitors objective sleep parameters, assesses subjective patient perception, detects sleep misperception, and guides therapy adjustment. This multi-functionality allows it to address both measurement accuracy and patient comfort needs.
4Reliability
If PAP therapy pressure is increased to treat severe SDB, then respiratory event reduction is improved, but subject comfort deteriorates causing sleep misperception
Solution Approach 1:
The system dynamically adjusts PAP therapy parameters based on detected sleep misperception and objective sleep quality. Rather than static high pressure settings, the system adapts pressure levels to maintain respiratory event reduction while minimizing discomfort-induced sleep misperception.
Solution Approach 2:
The system changes therapy parameters (pressure, ramp time, humidity) based on the balance between respiratory event reduction effectiveness and patient comfort. This allows optimization of both contradictory goals simultaneously.
Data Source
AI summary
There is provided a computer-implemented method for determining sleep misperception of a subject during a sleep session. The method comprises receiving sleep condition information. The sleep condition information comprises at least one of SDB information and insomnia information. The SDB information is representative of a sleep disordered breathing (SDB) condition of the subject based on a number of SDB events of the subject per unit of time. The computer-implemented method comprises receiving sleep quality information representative of a quality of sleep of the sleep session experienced by the subject. The computer-implemented method comprises determining a degree of sleep misperception based on the sleep condition information and the sleep quality information. The sleep misperception is representative of a difference between a subjective total sleep time of the sleep session experienced by the subject and an objective total sleep time of the subject in the sleep session.