Face Mask Geometry Selection Using Facial Point Cloud Data
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Solution Overview
Problem
One-size-fits-all face masks often fail to form an effective seal, leading to leakage and discomfort, as they do not accommodate individual facial geometry, resulting in inadequate protection against airborne pathogens and skin abrasions.
Innovation Solution
A method and system that collect facial data to determine a personalized geometry for the face mask, using a point cloud of facial points to estimate face size and nasal profile, selecting parameters for the mask's profile geometry to improve the seal and comfort by matching the mask to the user's facial features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a one-size-fits-all face mask is used, then manufacturing simplicity and cost-effectiveness are improved, but seal effectiveness and protection reliability deteriorate due to inadequate fit to individual facial geometry
Solution Approach 1:
The patent applies parameter changes by offering multiple face mask sizes (small, medium, large) with different dimensional parameters to match different face sizes. The method involves measuring facial dimensions (nose bridge position, cheekbone width, chin position) and selecting the appropriate mask size based on these measurements, thereby optimizing the seal effectiveness for each user while maintaining standardized manufacturing processes for each size category.
Solution Approach 2:
The patent segments the face mask population into distinct size categories (small, medium, large) based on facial geometry measurements. This segmentation allows each mask size to be optimized for specific face types, improving seal effectiveness without requiring fully custom-made masks for every individual, thus balancing manufacturing simplicity with protection reliability.
2Reliability
If the seal between face mask and face is made tighter to improve protection, then seal effectiveness is improved, but skin comfort deteriorates due to abrasions and irritation
Solution Approach 1:
The patent optimizes the seal tightness parameter by matching mask size to individual facial geometry. Properly fitted masks achieve effective seals without excessive tightness, reducing skin abrasions and irritation while maintaining protection effectiveness. The method determines optimal mask size based on precise facial measurements, ensuring the seal is tight enough to prevent leakage but not so tight as to cause discomfort.
3Reliability
If multiple face mask sizes are provided to improve fit, then seal effectiveness is improved, but device complexity and inventory requirements increase
Solution Approach 1:
The patent manages device complexity by limiting the number of mask sizes to three distinct categories (small, medium, large) with clearly defined dimensional parameters. This approach provides sufficient variety to accommodate different face sizes and improve seal effectiveness while avoiding the complexity of offering numerous size variations or fully customizable masks.
4Measurement precision
If custom facial scanning and personalized mask design are implemented, then fit precision is improved, but measurement and manufacturing complexity increase
Solution Approach 1:
The patent achieves practical measurement precision by focusing on key facial geometry parameters (nose bridge position, cheekbone width, chin position) rather than attempting to capture the entire facial surface. This simplified measurement approach provides sufficient accuracy for mask size selection while avoiding the complexity of full 3D facial scanning and personalized manufacturing systems.
Data Source
AI summary
A method for determining geometry of a face mask comprising a main body and a seal configured to engage a nasal region, cheeks and a chin of a user. The method comprises collecting (402) facial data of the user comprising a point cloud comprising a plurality of points on a skin surface in a nasal region, eye region and chin region of the user; determining (406), based on the facial data, in at least one of the eye region and the chin region of the user, an estimated face size of the user; determining (408), based on the facial data comprising the plurality of points in the nasal region, a best-fit Gaussian curve to a profile of a nose of the user; and using the estimated face size of the user and the determined Gaussian curve to select (410) parameters for a profile geometry of the face mask.