Automated Patient Interface Selection System
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Solution Overview
Problem
Conventional methods for selecting patient interface devices are inefficient, often resulting in discomfort, product wastage, and reliance on guesswork, as they require physical try-ons or reliance on caregiver judgment, leading to suboptimal fits and increased cleaning or disposal costs.
Innovation Solution
An automated system that uses a database to match patient-specific data, including anatomical and lifestyle characteristics, with corresponding patient interface device data to determine the most suitable device or component, minimizing waste and improving fit accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional physical try-on methods are used to select patient interface devices, then patient comfort and fit quality can be improved, but time consumption and product wastage increase
Solution Approach 1:
The system performs preliminary measurements of patient facial anatomical features before device selection, storing these measurements in a database. This preliminary data collection enables automated matching without requiring physical try-on sessions, thus improving fit quality while reducing time consumption.
Solution Approach 2:
The system creates a digital copy or model of the patient's facial features based on measured data, and uses this digital model to virtually match with patient interface device geometries. This eliminates the need for physical try-on of multiple devices while maintaining accurate fit assessment.
2Measurement precision
If conventional physical try-on methods are used to select patient interface devices, then fit accuracy can be improved, but product wastage and cleaning costs increase
Solution Approach 1:
The system uses digital copying of patient facial measurements and virtual matching with device models, eliminating the need to physically handle and return multiple devices. This prevents contamination and wastage associated with physical try-on processes.
Solution Approach 2:
The system replaces the mechanical physical try-on process with an automated computational matching system that compares digital facial measurement data with device geometric specifications, achieving accurate fit selection without physical contact between patient and multiple devices.
3Productivity
If caregiver judgment is used to select patient interface devices, then selection speed can be improved, but fit accuracy and reliability decrease
Solution Approach 1:
The system enables automated self-service device selection by objectively comparing patient facial measurement data with device specifications through computational algorithms, eliminating reliance on caregiver subjectivity while maintaining high selection speed.
Solution Approach 2:
The system incorporates feedback loops where measurement data is continuously compared against device performance outcomes, refining the matching algorithms to improve fit accuracy while maintaining automated rapid selection capability.
Data Source
AI summary
A patient interface device selection system that includes a database storing a plurality of sets of data. Each set of data in the plurality of sets of data is associated with a unique patient interface device or a component thereof. A patient data collection system, such as a measuring device, acquires a set of patient data that correspond to at least one characteristic of a patient. A processing system compares the acquired patient data with the plurality of sets of data, and determines the patient interface device or the component thereof that is suitable for use by such a patient based on a result of the comparison.