Enhanced Mask Sizing Tool Using Machine Learning and Augmented Reality

Publication ID: 24-11857726_0006_PTD
Published: October 28, 2025
Category:Direct Improvements & Enhancements

Legal Citation

pr1or.art Inc., “Enhanced Mask Sizing Tool Using Machine Learning and Augmented Reality,” Published Technical Disclosure No. 24-11857726_0006_PTD, Published October 28, 2025, available at https://archive.pr1or.art/24-11857726_0006_PTD
This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 11,857,726.

Summary of the Inventive Concept

A novel mask sizing tool that leverages machine learning, augmented reality, and cloud-based processing to improve the accuracy and efficiency of patient interface size selection, enhancing the treatment of respiratory-related disorders.

Background and Problem Solved

The original patent, 'Mask sizing tool using a mobile application,' has limitations in terms of accuracy and efficiency. The new inventive concept addresses these limitations by integrating advanced technologies to provide a more precise and streamlined patient interface size selection process.

Detailed Description of the Inventive Concept

The enhanced mask sizing tool consists of a mobile application that captures facial feature measurements, which are then processed using machine learning algorithms to predict optimal patient interface sizes. The tool also utilizes augmented reality to superimpose virtual patient interfaces onto a user's facial features, allowing for real-time size adjustments and improved fit. Additionally, the system includes a cloud-based server to process measurements and generate recommended patient interface sizes, as well as a notification system to alert healthcare professionals of the recommended sizes.

Novelty and Inventive Step

The new inventive concept introduces the use of machine learning, augmented reality, and cloud-based processing to improve the accuracy and efficiency of patient interface size selection, which is not present in the original patent. These advancements provide a non-obvious solution to the limitations of the original patent.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include using different machine learning algorithms, incorporating additional data sources such as medical imaging or anthropometric data, or integrating the system with electronic health records. Variations could also include adapting the tool for use in different medical specialties or for selecting sizes for other medical devices.

Potential Commercial Applications and Market

The enhanced mask sizing tool has significant commercial potential in the respiratory care industry, particularly in the treatment of sleep apnea and other respiratory-related disorders. The market for respiratory care devices is growing rapidly, and the inventive concept's ability to improve patient outcomes and reduce healthcare costs makes it an attractive solution for healthcare providers and manufacturers.

CPC Classifications

SectionClassGroup
A A61 A61M16/06
A A61 A61B5/097
A A61 A61B5/1077
A A61 A61B5/1079
A A61 A61M16/0051
A A61 A61M16/021
G G06 G06V10/7553
G G06 G06V40/171
G G16 G16H20/40
G G16 G16H30/40
G G16 G16H40/63
A A61 A61B5/7264
A A61 A61M2016/0661
A A61 A61M2205/3306
A A61 A61M2205/3553
A A61 A61M2205/3584
A A61 A61M2205/3592
A A61 A61M2205/50
A A61 A61M2205/505
A A61 A61M2205/52
A A61 A61M2205/6063
A A61 A61M2205/6072
A A61 A61M2230/00
G G16 G16H10/60

Field of Art

Medical device technology, specifically respiratory interface sizing systems, involving mobile computing, image processing, and machine learning for anthropometric measurement and medical device fitting

Person of Ordinary Skill (PHOSITA) Profile

A biomedical engineer or medical device designer with expertise in mobile application development, computer vision, machine learning, and medical device sizing techniques, holding advanced degrees in biomedical engineering or related fields

Obviousness Rationale

A person of ordinary skill would recognize that enhancing the source patent's mask sizing methodology with machine learning, augmented reality, and cloud processing represents predictable technological improvements using standard techniques in medical device design and mobile computing. The core problem of accurate patient interface sizing remains consistent, with the PTD offering incremental technological enhancements that leverage known computational approaches. These variations would be considered obvious extensions of the existing patent's foundational sizing methodology.

Obvious Combinations & Variations

Source Patent Element
Image pixel data processing for facial feature measurement
PTD Variation
Machine learning neural network to predict facial measurements and interface sizes
Obviousness Reasoning
Applying machine learning to existing image processing techniques is a predictable evolution in computer vision, representing a known technique for improving measurement accuracy
Source Patent Element
Mobile application for patient interface sizing
PTD Variation
Augmented reality visualization of virtual patient interfaces
Obviousness Reasoning
Integrating augmented reality into mobile medical device applications is a standard design choice for improving user interaction and visualization
Source Patent Element
Facial feature measurement for interface sizing
PTD Variation
Cloud-based server processing and healthcare professional notification system
Obviousness Reasoning
Extending local measurement processing to cloud infrastructure is a standard architectural approach for scalable medical technology solutions
Source Patent Element
Anthropometric correction factors for measurement
PTD Variation
Demographic data integration with machine learning prediction models
Obviousness Reasoning
Incorporating additional demographic data to refine measurement predictions represents an obvious statistical enhancement to existing sizing methodologies
35 U.S.C. § 103 Summary: Based on US Patent 11857726's foundational teachings of mobile application-based patient interface sizing, the present publication demonstrates that a person of ordinary skill would find the disclosed machine learning, augmented reality, and cloud processing variations to be obvious technological extensions, thereby rendering potential derivative claims obvious and anticipating future patent attempts to claim such incremental improvements.

Original Patent Information

Patent NumberUS 11,857,726
TitleMask sizing tool using a mobile application
Assignee(s)ResMed Pty Ltd