Ventilation Airway Anomaly Detection for Water and Filter Blockage
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Solution Overview
Problem
Ventilation devices face issues such as water accumulation in circuits, airway secretions, and increased filter resistance due to moisture, leading to ventilation failures and reduced therapeutic effectiveness.
Innovation Solution
An airway anomaly recognition method that monitors ventilation parameters like airway pressure and flow, using spectral analysis and curve fitting to detect anomalies like water accumulation, sputum buildup, and filter resistance, and outputs prompts to address these issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a humidifier is used in the respiration circuit to improve respiratory function, then the therapeutic effect is improved, but water vapor condenses and accumulates in the pipeline causing ventilation obstruction
Solution Approach 1:
The patent applies preliminary action by performing spectral analysis and curve fitting on ventilation parameters before significant water accumulation occurs. The system continuously monitors airway pressure and flow parameters, detecting early signs of condensation through spectral characteristics, allowing preventive intervention before the humidifier's beneficial effects are compromised by water blockage
Solution Approach 2:
The patent implements feedback by continuously monitoring ventilation parameters (airway pressure, flow) and using spectral analysis to detect changes indicating water accumulation. The system compares real-time spectral characteristics against reference patterns, providing continuous feedback on the humidifier's operation status and enabling dynamic adjustment to maintain therapeutic effectiveness while preventing harmful condensation accumulation
2Reliability
If bacterial filters are installed at gas supply end and expiration end to prevent infection, then patient safety is improved, but filter resistance increases after long-term use hindering ventilation
Solution Approach 1:
The patent applies preliminary action by continuously monitoring ventilation parameters through spectral analysis to detect early increases in filter resistance before they significantly impede ventilation. The system analyzes spectral characteristics of airway pressure and flow parameters to identify trends indicating filter loading, enabling proactive filter replacement or cleaning before the protective function is compromised by excessive resistance
Solution Approach 2:
The patent implements feedback by establishing a continuous monitoring system that tracks ventilation parameters and uses spectral analysis to detect changes associated with filter resistance increases. The system provides real-time feedback on filter performance, allowing operators to balance infection prevention benefits against ventilation resistance by及时调整 or replacing filters based on actual performance degradation rather than fixed schedules
3Measurement precision
If spectral analysis and curve fitting are used to detect airway anomalies, then detection accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent applies partial action by implementing spectral analysis at selective frequencies and using curve fitting only when anomaly indicators are detected. The system performs continuous monitoring with full analytical capability but applies the computationally intensive spectral decomposition and curve fitting operations selectively based on preliminary parameter thresholds, achieving high detection accuracy while reducing unnecessary computational burden during normal operation
Solution Approach 2:
The patent applies segmentation by dividing the spectral analysis into discrete frequency bands and analyzing different ventilation parameters (pressure, flow) separately. The curve fitting process is also segmented into distinct phases: initial parameter estimation, spectral decomposition, and anomaly pattern matching. This segmented approach reduces computational complexity by processing smaller data subsets independently rather than performing comprehensive analysis on all data simultaneously
Data Source
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AI summary
An airway anomaly recognition method, comprising: acquiring a ventilation parameter, the ventilation parameter comprises at least one of an airway pressure and airway flow (S101); recognizing, according to a change of the ventilation parameter, whether an airway anomaly event occurs (S102); and when it is recognized that the airway anomaly event occurs, outputting an airway anomaly event prompt (S103).