An Artificial Intelligence-Based Continuous Positive Airway Pressure Nasal Mask Fitting Assistance System

This paper proposes an AI-based continuous positive airway pressure (CPAP) nasal mask fitting assistance system. The system consists of a camera module, an Edge-AI computing module, and a display module. It captures and analyzes the user's facial features using AI technology to generate a facial mesh, accurately measuring the nasal wing width and nasal bridge height. Based on these measurements, the system recommends an appropriately sized CPAP nasal mask for the user, with facial features and measurement details augmented on the display module. Experimental results indicate that the system achieves a relative measurement error of less than 5%, effectively providing precise nasal mask size recommendations while enhancing user comfort and therapeutic efficacy.

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Publication Details

Published
2025-03-29
DOI
https://doi.org/10.1109/icct-pacific63901.2025.11012781
Primary Topic
Airway Management and Intubation Techniques
Type
article
Field-Weighted Citation Impact
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article

An Artificial Intelligence-Based Continuous Positive Airway Pressure Nasal Mask Fitting Assistance System

Ming-Che Chen, Cheng-Yu Lin, Yen‐Chin Chen, Chien-Yan Chien
Airway Management and Intubation Techniques
article

An Artificial Intelligence-Based Continuous Positive Airway Pressure Nasal Mask Fitting Assistance System

Ming-Che Chen, Cheng-Yu Lin, Yen‐Chin Chen, Chien-Yan Chien
article en

Abstract

This paper proposes an AI-based continuous positive airway pressure (CPAP) nasal mask fitting assistance system. The system consists of a camera module, an Edge-AI computing module, and a display module. It captures and analyzes the user's facial features using AI technology to generate a facial mesh, accurately measuring the nasal wing width and nasal bridge height. Based on these measurements, the system recommends an appropriately sized CPAP nasal mask for the user, with facial features and measurement details augmented on the display module. Experimental results indicate that the system achieves a relative measurement error of less than 5%, effectively providing precise nasal mask size recommendations while enhancing user comfort and therapeutic efficacy.

National Sun Yat-sen University (TW), National Cheng Kung University Hospital (TW), Southern Taiwan University of Science and Technology (TW)
Openalex Percentile: Top 79%
Airway Management and Intubation Techniques
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