Sleep Matching Feedback for Respiratory Therapy Compliance
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Solution Overview
Problem
Individuals with sleep-related and respiratory disorders often find conventional respiratory therapy systems uncomfortable, difficult to use, aesthetically unappealing, or fail to perceive benefits, leading to non-compliance or discontinuation of treatment.
Innovation Solution
A system and method that utilizes an application on a user device to capture and analyze images using machine learning to determine a sleep score, incorporating a respiratory therapy system with sensors and a control system to improve user compliance and effectiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional respiratory therapy systems are used to treat sleep disorders, then therapeutic effectiveness is improved, but user compliance deteriorates due to discomfort and difficulty of use
Solution Approach 1:
The system captures images during sleep, analyzes them using machine learning to determine sleep scores and breathing patterns, then provides visual feedback to users through a mobile application. This feedback loop allows users to see the direct benefits of therapy adherence, motivating continued compliance while maintaining therapeutic effectiveness
Solution Approach 2:
The patent replaces complex mechanical monitoring equipment with smartphone-based image capture and machine learning analysis. Instead of requiring users to interact with complex respiratory therapy equipment, the system uses automated image analysis to monitor sleep quality and breathing patterns, significantly improving ease of operation
2Reliability
If complex respiratory therapy systems are implemented, then treatment effectiveness is improved, but device complexity increases leading to aesthetic unappeal and difficulty of use
Solution Approach 1:
The patent extracts the monitoring and analysis functions from the respiratory therapy system itself and places them in a separate mobile application. The therapy device remains simple and unobtrusive, while the complex image analysis and machine learning algorithms run independently on the user's smartphone, reducing overall system complexity
Solution Approach 2:
The system uses a universal smartphone device that users already possess to perform multiple functions: capturing sleep images, running machine learning analysis, providing feedback, and motivating compliance. This eliminates the need for specialized, complex monitoring equipment while maintaining treatment effectiveness
3Ease of operation
If users are encouraged to continue respiratory therapy, then treatment compliance is improved, but users require demonstration of symptom severity and treatment benefits
Solution Approach 1:
The system captures images during sleep, analyzes them using machine learning to determine sleep scores and breathing patterns, then provides visual feedback to users through a mobile application. This feedback loop allows users to see the direct benefits of therapy adherence, motivating continued compliance while maintaining therapeutic effectiveness
Solution Approach 2:
The system uses visual indicators and color-coded feedback in the mobile application to show users their sleep quality and treatment effectiveness. By transforming complex physiological data into intuitive visual representations, users can immediately perceive the benefits of their therapy adherence
Data Source
AI summary
A method includes storing, in a database, sleep information associated with a plurality of users, receiving, via a control system from a first user device, sleep information associated with a first user, comparing, by the control system, the sleep information associated with the first user to the sleep information associated with the plurality of users, determining, by the control system based on the comparing, that the sleep information associated with a second user corresponds to the sleep information associated with the first user, generating, by the control system based on the sleep information associated with the second user and the sleep information associated with the first user, a notification, and causing transmission, by the control system, of the notification to one or more of the first user device and a second user device, wherein the second user device is associated with the second user.