Pressure–Flow Correlation for Mechanical Ventilation Breathing Recognition
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Solution Overview
Problem
Existing breathing recognition methods for mechanically ventilated patients are prone to inaccuracies due to environmental and apparatus interference, leading to misrecognition.
Innovation Solution
A method and device that utilize correlation data derived from airway pressure and gas flow rate during mechanical ventilation to recognize breathing states, employing correlation calculation and threshold analysis to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If breathing recognition is performed based on diaphragmatic electromyogram or abdominal sensor, then breathing state can be detected, but recognition accuracy deteriorates due to environmental interference and apparatus interference
Solution Approach 1:
The patent introduces airway pressure and gas flow rate as intermediary parameters that indirectly reflect patient breathing states. Instead of directly measuring diaphragmatic electrical activity or abdominal movement (which are susceptible to interference), the system uses airway pressure and gas flow rate signals that are less affected by environmental and apparatus interference, thereby improving breathing recognition accuracy
Solution Approach 2:
The patent replaces the mechanical/sensor-based detection methods (abdominal sensors detecting physical movement) with a computational approach using correlation analysis of airway pressure and gas flow rate signals. This substitution transforms the measurement from direct physical sensing to indirect signal processing, reducing the impact of environmental and apparatus interference
2Adaptability or versatility
If multiple breathing recognition methods are used, then recognition coverage is improved, but system complexity increases and may lead to conflicting results
Solution Approach 1:
The patent merges airway pressure and gas flow rate measurements into a unified breathing recognition system. By calculating the correlation coefficient between these two signals, the system integrates multiple data sources into a single comprehensive indicator, avoiding the complexity and potential conflicts of multiple independent recognition methods while maintaining broad adaptability
Solution Approach 2:
The correlation-based breathing recognition method serves multiple functions: it can detect spontaneous breathing, distinguish between inhalation and exhalation phases, and adapt to different ventilation modes. This single universal approach replaces the need for multiple specialized sensors and algorithms, reducing system complexity while maintaining versatility
Data Source
AI summary
This disclosure provides a breathing recognition method applicable in a ventilation apparatus. In the breathing recognition method, an airway pressure and a gas flow rate can be acquired during mechanical ventilation; correlation data corresponding to the airway pressure and the gas flow rate can be determined according to the airway pressure and the gas flow rate; and a breathing state of a patient can be recognized according to a change in the correlation data.