Breath Selection for Diagnostic Analysis
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Solution Overview
Problem
Current breath analysis methods face challenges in accurately correlating blood-to-breath analyte levels due to variations in breathing patterns, particularly in non-resting tidal volumes or abnormal breathing, leading to potential false diagnostic results, especially in cases where patients cannot follow instructions or breathe abnormally.
Innovation Solution
The development of systems and methods that measure and target physiologically appropriate breaths for diagnostic tests by defining and capturing breaths that meet specific threshold criteria, such as complete tidal volume breaths, and applying correction factors for non-representative breaths, using sensors, breath sampling systems, and processors to ensure accurate sample collection and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If breath samples are taken without considering breathing pattern, then the testing process is simple and fast, but the diagnostic accuracy deteriorates due to false results from abnormal breathing
Solution Approach 1:
The system performs preliminary monitoring of breathing patterns before conducting the actual analyte measurement. The processor monitors breathing parameters (flow rate, tidal volume, respiratory rate) during a pre-measurement period to determine if the patient's breathing is appropriate for accurate testing. Only when breathing criteria are met does the system proceed to collect the breath sample for analysis, ensuring diagnostic accuracy without requiring complex real-time intervention during sampling.
Solution Approach 2:
The system continuously monitors breathing parameters and provides feedback to determine whether collected breath samples are suitable for analysis. The processor compares real-time breathing data against predetermined criteria (such as tidal volume thresholds and respiratory rate ranges) to validate sample quality. This feedback mechanism allows the system to reject inadequate samples and request additional breaths, maintaining high diagnostic accuracy while using relatively simple hardware components.
2Measurement precision
If the system waits for a specific type of breath to occur, then the accuracy of sample collection improves, but the testing time increases
Solution Approach 1:
The system performs preliminary monitoring of breathing patterns before conducting the actual analyte measurement. The processor monitors breathing parameters (flow rate, tidal volume, respiratory rate) during a pre-measurement period to determine if the patient's breathing is appropriate for accurate testing. Only when breathing criteria are met does the system proceed to collect the breath sample for analysis, ensuring diagnostic accuracy without requiring complex real-time intervention during sampling.
Solution Approach 2:
The system monitors multiple breathing parameters simultaneously (flow rate, tidal volume, respiratory rate, inspiratory/expiratory time) rather than relying on a single criterion. This partial monitoring of excessive parameters allows the system to efficiently identify suitable breath opportunities by checking multiple conditions in parallel, reducing the time to validate a sample while maintaining high accuracy standards.
3Reliability
If correction factors are applied for non-representative breaths, then the diagnostic reliability improves, but the complexity of data processing increases
Solution Approach 1:
The system changes the parameters used for analysis by applying correction factors that adjust the relationship between breath analyte levels and blood analyte levels based on the detected breathing pattern. When abnormal breathing is detected (such as hyperventilation or shallow breathing), the processor applies predetermined correction factors to the measured breath concentrations to compensate for the deviation from normal breathing conditions. This approach maintains diagnostic reliability by accounting for breathing variations without requiring complex real-time physiological modeling.
4Ease of operation
If the system automatically identifies and targets appropriate breaths, then the ease of operation improves for non-cooperative patients, but the device complexity increases
Solution Approach 1:
The system performs self-service by automatically monitoring breathing patterns, identifying suitable breaths, and triggering sample collection without requiring patient cooperation or manual intervention. The processor continuously analyzes breathing parameters and autonomously determines when breath samples meet the predetermined criteria for accurate analysis. This self-service capability allows the system to handle non-cooperative patients (such as infants or unconscious individuals) effectively, as the device independently manages the entire sample selection process without needing the patient to follow instructions.
Data Source
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AI summary
Methods and systems are described to obtain and analyze a gas sample from a desired section of the breath of a person, while accounting for erratic, episodic or otherwise challenging breathing patterns that may otherwise make the capturing of a gas sample from the desired section of breath difficult. These techniques may provide more reliable, accurate and adequate samples of gas such as end-tidal gas, and ultimately an accurate analysis of the sample captured.