Acoustic Interface Characterization for Respiratory Therapy Conduits
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Solution Overview
Problem
Existing respiratory therapy systems face challenges in accurately identifying the specific category and type of user interfaces, such as masks, due to user input errors, which can affect therapy delivery and parameter measurement.
Innovation Solution
The system analyzes acoustic reflections of acoustic signals to categorize and characterize user interfaces by identifying signatures through acoustic data, using windowing, deconvolution, and machine learning models to determine features like direct or indirect connections and specific models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a menu system is used to allow user input for user interface identification, then the system can obtain user interface information, but user input errors occur leading to incorrect or incomplete information
Solution Approach 1:
The system performs self-identification of the user interface by automatically analyzing acoustic reflections from the user interface and conduit, eliminating the need for manual user input. The processor autonomously determines the user interface type, model, and manufacturer based on acoustic signature matching, thereby removing the source of human error while maintaining ease of system configuration.
Solution Approach 2:
The patent replaces the mechanical/manual input method (menu system requiring user selection) with an acoustic sensing and analysis system. By substituting human interaction with automated acoustic measurement and pattern recognition, the system achieves both ease of operation (automatic detection) and high measurement precision (objective acoustic analysis).
2Measurement precision
If automated acoustic analysis is implemented to identify user interface features, then user interface identification accuracy is improved, but device complexity increases
Solution Approach 1:
The acoustic sensor and processor are designed to serve multiple functions: detecting acoustic reflections, analyzing acoustic signatures, identifying user interface type, determining conduit type, and characterizing connection features. By making the acoustic analysis system multi-functional, the patent achieves high identification accuracy without proportionally increasing device complexity, as a single integrated system performs what would otherwise require multiple separate components.
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
Accurately identifies user interface types and models, enhancing therapy control and measurement precision by reducing user input errors.
Implementation Method 1
generating acoustic data associated with an acoustic reflection of an acoustic signal... The acoustic reflection is indicative of, at least in part, one or more features of a user interface coupled to a respiratory therapy device via a conduit
Data Source
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AI summary
Systems and methods are disclosed for categorizing and/or characterizing a user interface. The systems and methods include generating acoustic data associated with an acoustic reflection of an acoustic signal, the acoustic reflection being indicative of, at least in part, one or more features of a user interface coupled to a respiratory therapy device via a conduit. The systems and methods further include analyzing the generated acoustic data which includes categorizing and/or characterizing the user interface based, at least in part, on the analyzed acoustic data.