Capnograph Respiratory Index Computation Without Breath Segmentation
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Solution Overview
Problem
Capnography devices struggle to accurately assess patient respiratory health due to complex waveform analyses that are prone to errors and information loss, particularly in segmenting breath cycles and normalizing amplitudes, which are challenging for medical personnel with limited expertise.
Innovation Solution
A capnograph device computes parameter quality indices and a respiratory well-being index using a capnogram histogram, eliminating the need for breath detection and segmentation, thereby providing reliable RR and etCO2 metrics for improved respiratory system status assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex waveform analyses are performed to capture rich informational content, then measurement precision is improved, but device complexity increases and reliability decreases due to numerous error mechanisms
Solution Approach 1:
The patent extracts only the essential features needed for assessment (etCO2, RR, and their quality indices) from the complex capnogram waveform, avoiding the need for comprehensive waveform segmentation and analysis. This extraction approach maintains measurement precision for critical parameters while eliminating the reliability issues associated with complex processing.
Solution Approach 2:
Instead of segmenting the waveform and then extracting parameters, the patent inverts the approach by computing quality indices directly from the raw capnogram data without segmentation. This eliminates the error propagation that occurs during segmentation and normalization operations.
2Ease of operation
If automated waveform analyses are performed to assist medical personnel, then ease of operation is improved, but loss of information increases due to normalization operations
Solution Approach 1:
The patent performs only the minimal necessary analysis to extract etCO2 and RR parameters with their quality indices, avoiding excessive waveform processing. This partial action approach maintains ease of operation while preserving waveform information by not applying aggressive normalization or segmentation that would lose data.
3Measurement precision
If breath detection and segmentation are performed to compute standard parameters, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent extracts parameters (etCO2, RR, PQI, RWI) directly from the capnogram waveform using simplified computation methods that do not require breath detection or segmentation. This extraction approach maintains measurement precision for critical clinical parameters while significantly reducing device complexity.
Solution Approach 2:
The patent replaces the mechanical segmentation process (dividing the waveform into breath cycles and phases) with a direct computational approach that calculates parameters from the continuous waveform using quality index metrics, thereby reducing complexity while maintaining accuracy.
Data Source
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AI summary
A capnograph device (10) includes a carbon dioxide measurement component (20) and an electronic processor (30) programmed to generate a capnogram (40) comprising carbon dioxide level sample values measured as a function of time. End-tidal carbon dioxide (etC02) is determined from the capnogram, and an etC02 parameter quality index (etC02 PQI) (44) is computed using one or more quantitative capnogram waveform metrics computed from the capnogram. A respiration rate (RR) value is also determined from the capnogram, and a RR PQI (46) computed using the RR value and the etC02 PQI. A respiratory well-being index (RWI) (50) may be computed from the etC02 and RR values and the etC02 and RR PQI values. In some embodiments the one or more capnogram waveform metrics are computed from a capnogram histogram generated from the capnogram.