Facial Recognition Patient Interface Identification System
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Solution Overview
Problem
Existing patient interface fitting systems are cumbersome and time-consuming, requiring manual measurement of facial dimensions, which is impractical for many situations and does not account for individual anatomical variations, leading to potential air leaks and discomfort.
Innovation Solution
A patient interface identification system using facial recognition technology to compare a test image with a database of reference images, analyzing image-based features to recommend the best-fitting interface type, size, and adjustment settings based on similarity scores, without the need for manual dimension measurement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual measurement of facial dimensions is used, then measurement precision can be achieved, but the process becomes time-consuming and cumbersome
Solution Approach 1:
The patent replaces manual mechanical measurement methods with an automated image processing system that captures facial images and extracts dimensional data through computer algorithms, eliminating the need for physical measuring tools and manual operations while maintaining measurement accuracy
Solution Approach 2:
The system creates a digital copy of the patient's facial features through imaging (photography or scanning) and performs measurements on this copy, allowing rapid repeated measurements without physical contact or time-consuming manual procedures on the actual patient
2Device complexity
If standardized patient interfaces are used, then device complexity is reduced, but individual anatomical variations cannot be accommodated
Solution Approach 1:
The system analyzes specific local features of the patient's face (nose shape, mouth contours, cheek structure) and uses these localized characteristics to determine the most suitable patient interface, rather than relying on overall face size alone, thereby accommodating individual anatomical variations
Solution Approach 2:
The system performs preliminary analysis of facial features and pre-determines the optimal patient interface type and size before the actual fitting process, allowing standard interfaces to be selected based on pre-acquired anatomical data, thus maintaining simplicity while achieving customization
3Manufacturing precision
If comprehensive facial measurements are taken, then fit accuracy is improved, but the measurement process becomes more complex
Solution Approach 1:
The patent replaces complex manual measurement procedures with automated image capture and processing systems that extract multiple facial dimensions simultaneously from images, achieving comprehensive measurements without proportionally increasing operational complexity
Solution Approach 2:
The system extracts and uses only the specific facial features and dimensions that are relevant for patient interface fitting from the captured images, rather than measuring every possible facial parameter, thereby achieving sufficient fit accuracy without unnecessary measurement complexity
Data Source
AI summary
The present invention relates to a patient interface identification system for identifying a patient interface that is suited for a face (16) of a user (18), comprising: a receiving unit (12) for receiving a test picture (14) including the face (16) of the user (18); a database (22) for storing reference picture including faces of other users, wherein each reference picture is referenced to a patient interface advice; a processing unit (24) for comparing the received test picture (14) with at least a subset of said reference pictures stored in the database (22), wherein comparing said test picture (14) with said subset of reference pictures includes a comparison of image based features of the user's face (16) and the other users' faces; and a user interface (26) for communicating a patient interface advice including information related to a patient interface that is suited for the face (16) of the user (18), which patient interface advice is based on the comparison of said test picture (14) with the subset of reference pictures stored in the database (22).