Respiratory Device Automatic Interface Identification via Airflow Analysis
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Solution Overview
Problem
Respiratory therapy devices face challenges in automatically identifying user interfaces and conduits, leading to potential errors in therapy delivery due to manual setup processes and changes in equipment over time, which can affect the accuracy and effectiveness of treatment.
Innovation Solution
A method that generates airflow through the user interface, measures airflow parameters such as flow rate and pressure, and uses machine learning models to identify user interface and conduit information, allowing for automatic detection and adjustment of settings to ensure proper therapy delivery without external sensors or user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual setup process is used to identify user interfaces and conduits, then device complexity is reduced, but measurement precision and reliability deteriorate due to potential errors in manual setup
Solution Approach 1:
The respiratory device automatically identifies user interfaces and conduits without requiring manual input or external sensors. The system uses its existing airflow sensors to characterize the acoustic signature of the user interface and conduit, enabling self-identification and eliminating manual setup errors.
Solution Approach 2:
The patent replaces manual mechanical identification processes with an automated acoustic measurement system. By using airflow sensors to detect acoustic signatures and machine learning algorithms to recognize patterns, the system substitutes manual setup procedures with automated electronic identification.
2Reliability
If manual setup process is used, then ease of operation is improved, but reliability deteriorates due to errors in manual configuration and equipment changes over time
Solution Approach 1:
The system continuously monitors airflow parameters and uses machine learning models to identify user interfaces and conduits in real-time. This feedback mechanism allows the device to automatically adapt to equipment changes and maintain accurate therapy delivery without requiring user intervention or manual reconfiguration.
Solution Approach 2:
The respiratory device performs self-identification of user interfaces and conduits autonomously, eliminating the need for manual configuration. The system uses its existing sensors to characterize acoustic signatures and automatically updates its identification based on real-time airflow data, ensuring reliable therapy delivery.
3Reliability
If automatic identification system is implemented, then measurement precision and reliability are improved, but device complexity increases due to additional sensors and processing requirements
Solution Approach 1:
The patent leverages the existing airflow sensor in the respiratory device to serve dual purposes: monitoring therapy delivery and identifying user interfaces and conduits through acoustic signature analysis. This multi-functionality approach eliminates the need for separate identification sensors, reducing overall system complexity.
Solution Approach 2:
The system replaces additional physical sensors with computational analysis of existing sensor data. By using machine learning models to process airflow signals and extract acoustic characteristics, the patent achieves reliable identification without adding significant hardware complexity.
4Productivity
If manual setup is used, then ease of manufacture is improved, but productivity deteriorates due to time-consuming setup processes and potential reconfiguration needs
Solution Approach 1:
The system performs preliminary identification of user interfaces and conduits automatically upon connection, eliminating the need for manual setup procedures. This preliminary automated characterization allows for immediate use without time-consuming configuration processes.
Solution Approach 2:
The respiratory device autonomously identifies and characterizes user interfaces and conduits without requiring manual intervention during setup. The system uses its existing airflow sensors to automatically detect acoustic signatures and update its identification, significantly reducing setup time and improving productivity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate and automatic identification of user interfaces and conduits, ensuring correct therapy pressure and reducing errors by dynamically adjusting settings based on real-time data, thereby improving the efficacy of respiratory therapy.
Implementation Method 1
generating airflow through a user interface... measuring one or more airflow parameters associated with the generated airflow, wherein the one or more airflow parameters include at least one of a flow signal of the generated airflow over time and a pressure signal of the generated airflow over time
Implementation Method 2
measuring one or more airflow parameters associated with the generated airflow... identifying user interface identification information based on the measured one or more airflow parameters
Data Source
AI summary
Airflow parameters (e.g., flow rate and airflow pressure) of airflow generated by a flow generator of a respiratory therapy system can be measured during use and processed to automatically identify user interface and/or conduit identification information. This user interface and/or conduit identification information can be used to adjust settings of the respiratory therapy device, generate notifications (e.g., notifications of a detected change in user interface without concomitant, expected adjustment of settings of the respiratory therapy device), or otherwise facilitate respiratory therapy of the user or of other users. User interface and/or conduit identification information can be indicative of specific characteristics of the user interface and/or conduit (e.g., resonant frequencies, impedance, and the like), a style of the user interface (e.g., a face mask, nasal mask, or nasal pillow) and/or style of conduit, a specific manufacturer, a specific model, or other such identifiable information.