Respiratory Therapy Comfort Score Estimation
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Solution Overview
Problem
Respiratory therapy systems for sleep apnea and related disorders often compromise user comfort, leading to poor initial experiences and potential abandonment of treatment, as existing comfort scores do not accurately reflect subjective discomfort, which can worsen quality of life by delaying effective therapy.
Innovation Solution
A system and method for estimating a subjective comfort level of a respiratory therapy system user by receiving data during therapy sessions, determining relevant parameters, and calculating a comfort score based on these parameters, which can adjust therapy settings and recommendations to improve user comfort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If respiratory therapy systems are used to treat sleep apnea, then health outcomes improve, but user comfort deteriorates leading to treatment abandonment
Solution Approach 1:
The system continuously monitors user physiological data and comfort indicators during therapy sessions, then uses this feedback to dynamically adjust therapy parameters and provide real-time recommendations, creating a closed-loop system that adapts to user needs while maintaining treatment effectiveness
Solution Approach 2:
The system dynamically modifies therapy parameters such as pressure levels, flow rates, and timing based on detected user comfort levels and physiological responses, allowing the therapy to adapt to changing user conditions while maintaining clinical effectiveness
2Loss of information
If existing comfort scoring systems are used, then user feedback is collected, but the accuracy of subjective discomfort measurement is insufficient
Solution Approach 1:
The system combines multiple data sources including physiological measurements, user self-reports, and objective comfort indicators into a unified comfort assessment model, creating a more comprehensive and accurate measurement of subjective discomfort than any single source could provide alone
Solution Approach 2:
The system introduces an intermediary computational model that processes and integrates raw data from multiple sources to generate a refined comfort score, acting as a mediator between raw measurements and the final comfort assessment to improve measurement accuracy
Data Source
AI summary
A method for predicting a subjective comfort level of a user of a respiratory therapy system is disclosed as follows. Data associated with the user of the respiratory therapy system during a therapy session is received. At least one parameter associated with the user is determined based at least in part on a first portion of the received data. A comfort score is determined based at least in part on the determined at least one parameter. The comfort score is indicative of the subjective comfort level of the user of the respiratory therapy system during at least a portion of the therapy session.