Modular Breathing System with Information Tags
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Solution Overview
Problem
Clinicians face challenges in accurately configuring mechanical breathing systems due to the need for manual identification and recalibration of modular components, which can lead to therapeutic errors and inefficiencies, especially during patient transport where data may be lost or duplicated.
Innovation Solution
The implementation of information tags with sensors on modular components that transmit data to the system controller, including physical characteristics, function, and patient information, to automatically configure and optimize the mechanical breathing system, reducing human error and streamlining data transfer between systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual identification and configuration of modular components is used, then system flexibility and adaptability are maintained, but therapeutic errors increase and configuration accuracy decreases
Solution Approach 1:
The modular components perform self-identification through embedded tags (RFID, barcode, or data storage elements) that automatically provide component information to the system controller, eliminating the need for manual identification and configuration by clinicians
Solution Approach 2:
Manual mechanical configuration processes are replaced with automated electronic data transfer systems where information tags and sensors automatically communicate component characteristics to the controller, substituting human操作 with electronic automation
2Productivity
If manual reconfiguration of modular components is performed, then system adaptability to different patient needs is achieved, but time consumption and inefficiency increase
Solution Approach 1:
Component information is pre-stored in tags attached to each modular component before use, including all necessary identification and configuration data, so that when components are assembled, the system controller can immediately retrieve and process this information without requiring time-consuming manual entry or calibration procedures
Solution Approach 2:
The system controller receives automatic feedback from information tags on each modular component, continuously monitoring and updating system configuration data as components are added or removed, enabling real-time adaptation without manual intervention
3Measurement precision
If system checkout procedures are run to determine system characteristics, then measurement accuracy of system parameters is improved, but time loss and reduced productivity occur
Solution Approach 1:
Instead of performing physical checkout procedures to measure system characteristics, the system uses digital copies of component data stored in information tags, which contain pre-measured and verified parameters that are automatically transferred to the controller, replacing time-consuming physical testing with instant data retrieval
4Loss of information
If clinicians manually track and transfer patient data between systems, then data accuracy can be maintained, but time consumption and operational complexity increase
Solution Approach 1:
Patient data and system configuration information are merged into a unified digital record that travels with the patient through the mechanical breathing system, allowing automatic transfer between different ventilator systems without requiring separate manual tracking or entry processes
Data Source
AI summary
An optimized system for providing medical support to a patient is disclosed. The system has a plurality of modular components that may be assembled to create a connection between a support machine and the patient wherein at least one of the modular components comprises an information tag for the storage of data and at least one of the modular components comprises an information sensor for the reading and transmission of the data. Once read and transmitted by the sensor, the data may be used to optimize the operation of the support machine.


