Temporal Model for Patient Mask Fit Stability
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Solution Overview
Problem
Current methods for creating custom masks for patients using 3D scans fail to accommodate variations in facial geometry during movement, leading to discomfort and instability, especially during sleep.
Innovation Solution
The method involves capturing a series of 3D images of the patient's face in various poses and expressions, generating a temporal model that includes both spatial and time-based information, and using this model to determine an appropriate mask that accommodates the patient's actual facial geometry during movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a single 3D scan is used to create a custom mask, then the manufacturing process is simple and quick, but the mask does not accommodate variations in facial geometry during movement, leading to discomfort and instability
Solution Approach 1:
The system performs preliminary actions by capturing multiple 3D scans of the patient's face in various poses and expressions before mask fabrication. This pre-acquisition of comprehensive facial geometry data across different states allows the mask design to anticipate and accommodate facial movements during sleep, resolving the contradiction between simple manufacturing and reliable fit stability.
Solution Approach 2:
The invention applies dynamics by creating a temporal model that captures the dynamic range of facial geometries rather than a static single-state model. The mask is designed to accommodate these dynamic variations, allowing it to maintain proper fit and stability throughout facial movements during sleep, thus improving reliability without significantly complicating the manufacturing process.
2Reliability
If multiple 3D scans in various poses are captured to create a temporal model, then the mask fit and comfort are improved, but the complexity of the scanning and processing procedure increases
Solution Approach 1:
The system achieves universality by developing a temporal model that serves multiple functions: it captures spatial geometry, temporal variations, and ranges of motion across different facial states. This multi-functional model allows a single mask design process to accommodate all facial variations, improving comfort without requiring separate processing for each pose or expression.
Solution Approach 2:
The invention uses copying by creating a digital temporal model that replicates the patient's facial geometries across multiple states. This virtual copy allows comprehensive analysis and mask design without requiring physical prototypes or multiple separate scanning sessions, reducing overall system complexity while maintaining high reliability.
3Ease of manufacture
If a mask is designed based on a single neutral facial scan, then the design process is straightforward, but the mask becomes unstable during facial movements such as sleep positioning
Solution Approach 1:
The system performs preliminary action by capturing facial scans in multiple poses and expressions before mask design. This pre-acquisition of movement data allows the mask to be designed with stability considerations built-in, accommodating the full range of facial geometries the patient exhibits during sleep, thus maintaining ease of manufacture while improving positioning stability.
Solution Approach 2:
The invention applies parameter changes by utilizing the temporal model to identify and accommodate variations in facial geometry parameters across different states. The mask design incorporates these parameter variations, allowing it to maintain stable positioning despite changes in facial shape during sleep movements, resolving the contradiction between simple design and stable composition.
Data Source
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AI summary
A method (40) for identifying a mask for a patient includes: receiving (42) a plurality of images of a patient's face; analyzing (44) the plurality of images to generate a temporal model of the patient's face, determining (46) a mask for the patient using the temporal model of the patient's face, and identifying (48) the mask to the patient.