Acoustic Sleep Score Calculation for Respiratory Therapy Adherence
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Solution Overview
Problem
Individuals with sleep-related and respiratory disorders, such as Sleep Disordered Breathing, often find existing respiratory therapy systems uncomfortable, difficult to use, and aesthetically unappealing, leading to non-compliance and a lack of perceived benefits, which hinders effective treatment of their conditions.
Innovation Solution
A system that captures noise data during sleep using a microphone to detect trigger events and calculate a sleep score, allowing for the evaluation of sleep quality and potential therapy adherence, even when the respiratory therapy device is not in use, by storing and analyzing noise data to provide insights on sleep disturbances and recommending therapy usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If respiratory therapy systems are used to treat sleep-related disorders, then treatment effectiveness is improved, but user comfort and ease of use deteriorate
Solution Approach 1:
The system provides feedback to users about their sleep quality and therapy effectiveness through sleep scores and detailed reports. This feedback mechanism helps users understand the benefits of using the respiratory therapy system, thereby improving treatment effectiveness while maintaining user comfort through informed decision-making.
Solution Approach 2:
The patent replaces direct mechanical monitoring with acoustic sensing and automated analysis. Instead of requiring users to manually track their sleep or wear complex monitoring devices, the system uses microphones to capture sleep-related sounds and automatically analyzes them to generate sleep scores, simplifying the user experience while maintaining treatment effectiveness.
2Reliability
If respiratory therapy systems are used, then sleep quality improves, but device complexity and cost increase
Solution Approach 1:
The system extracts and focuses on specific acoustic features related to sleep quality (such as snoring, apnea events, and respiratory sounds) from the overall ambient noise. By isolating and analyzing only the relevant acoustic parameters, the system achieves detailed sleep quality assessment without requiring complex multi-sensor systems or expensive hardware.
Solution Approach 2:
The respiratory therapy system integrates multiple functions into a single device: it provides respiratory support, captures acoustic data, processes sleep information, generates sleep scores, and creates detailed reports. This multi-functionality reduces the need for separate monitoring devices and simplifies the overall system architecture while maintaining comprehensive sleep quality monitoring.
3Reliability
If respiratory therapy systems are used, then treatment effectiveness improves, but aesthetic appeal and user acceptance worsen
Solution Approach 1:
The system creates a digital copy of sleep quality through sleep scores and visual reports, replacing the need for users to physically interact with complex monitoring equipment. This digital representation maintains treatment effectiveness while presenting information in an aesthetically pleasing and easily digestible format, improving user acceptance.
4Measurement precision
If noise data is captured and analyzed to calculate sleep scores, then sleep quality evaluation improves, but data processing complexity increases
Solution Approach 1:
The system segments the sleep night into distinct events and phases (e.g., sleep periods, wake periods, apnea events, snoring episodes) and analyzes each segment separately. This segmentation approach simplifies the overall data processing complexity by breaking down the complex task of sleep quality evaluation into manageable, sequential analysis steps, while maintaining measurement precision through detailed event-by-event assessment.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables effective monitoring and improvement of sleep quality and therapy adherence by providing a user-friendly method to assess sleep scores and therapy effectiveness, encouraging consistent use of respiratory therapy systems.
Implementation Method 1
capturing, via a microphone, noise data associated with the user sleeping
Data Source
AI summary
A method includes capturing, via a microphone, noise data associated with the user sleeping. The method also includes detecting, based on the noise data, a trigger event. The method also includes, in response to detecting the trigger event, storing at least a portion of the noise data. The method also includes calculating, by a control system based on the at least a portion of the noise data, the sleep score for the user.