CPAP Mask Fit Analysis Using Facial Image and Usage Data
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Solution Overview
Problem
Existing respiratory masks for CPAP therapy are often uncomfortable, difficult to use, and poorly fitting, leading to reduced patient compliance due to their obtrusive nature and aesthetic unappeal, which is exacerbated by the need for customization and labor-intensive sizing processes that hinder accessibility.
Innovation Solution
A system that collects user feedback data by correlating facial image data with operational and subjective data to refine mask designs, using machine learning to adjust mask characteristics for improved comfort and fit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If masks are customized to fit individual facial anatomy, then comfort and seal effectiveness are improved, but device complexity and manufacturing cost increase
Solution Approach 1:
The patent applies parameter changes by adjusting mask dimensions and facial seal characteristics based on quantitative facial measurements. The system collects facial images, extracts dimensional parameters (nose width, face height, cheek bone distance), and uses these to calculate optimal mask parameters, thereby achieving customized fits without manual intervention.
Solution Approach 2:
The patent replaces manual mechanical sizing processes with an automated image processing system. Instead of requiring physical measurements or manual fitting adjustments, the system uses computer vision to capture facial geometry and automatically determines mask specifications, reducing complexity while maintaining customization.
2Manufacturing precision
If manual sizing processes are used to ensure proper fit, then manufacturing precision is improved, but loss of time and productivity decrease
Solution Approach 1:
The patent applies preliminary action by pre-establishing a database of facial measurements and mask specifications. The system pre-processes facial images to extract dimensional data before mask manufacturing, enabling rapid automated sizing without time-consuming manual measurement processes during production.
Solution Approach 2:
The patent substitutes manual mechanical measurement with automated optical scanning and image analysis. The system captures facial images, processes them through algorithms to extract dimensional parameters, and generates mask specifications automatically, eliminating manual sizing time while maintaining precision.
3Ease of operation
If masks are made more comfortable and aesthetically pleasing, then ease of operation is improved, but device complexity increases due to customization requirements
Solution Approach 1:
The patent applies parameter changes by adjusting mask physical characteristics (size, shape, cushioning dimensions) based on calculated facial parameters. The system uses formulas that relate facial measurements to optimal mask dimensions, enabling automated customization of comfort parameters without manual intervention.
Solution Approach 2:
The patent applies self-service by enabling patients to undergo automated facial scanning and receive customized mask recommendations without requiring manual fitting services. The system autonomously processes facial images, calculates optimal mask parameters, and provides personalized recommendations, reducing dependency on manual customization services.
Data Source
AI summary
A system and method to collect feedback data from a patient wearing an interface such as a mask when using a respiratory pressure therapy device such as a CPAP device. The system includes a storage device including a facial image of the patient. An interface in communication with the respiratory pressure therapy device collect operational data from when the patient uses the interface. A patient interface collects subjective patient input data from the patient in relation to the patient interface. An analysis module correlates a characteristic of the interface with the facial image data, operational data and subjective patient input data.