Model-Driven Exhalation Flow Estimation for Ventilator Sensor Failure
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Solution Overview
Problem
Medical ventilators face challenges with inaccurate exhalation flow measurements due to failures in flow sensors, such as damaged temperature or flow elements, which can lead to incorrect patient ventilation parameters.
Innovation Solution
A method and system for estimating a modeled exhalation flow using a pressure difference and a flow estimation model, allowing the ventilator to determine sensor failures and potentially replace or supplement faulty measurements, thereby ensuring accurate ventilation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a flow sensor is used to measure exhalation flow, then ventilation monitoring is enabled, but sensor failures lead to inaccurate measurements
Solution Approach 1:
The patent creates a virtual copy of the flow sensor by developing a mathematical model that replicates flow sensor functionality using pressure sensor data and valve parameters. This modeled flow estimate serves as a backup or supplement to the physical flow sensor, enabling continuous ventilation monitoring even when the physical sensor fails.
Solution Approach 2:
The patent replaces the mechanical/physical flow sensor measurement system with a computational model that uses pressure measurements and valve characteristics to calculate flow. This substitution eliminates the need for fragile flow sensor components while maintaining the ability to monitor exhalation flow.
2Ease of operation
If flow sensor components (temperature element, flow element) are used, then flow measurement is achieved, but these components are susceptible to damage and contamination
Solution Approach 1:
The patent creates a virtual replica of flow sensor functionality through mathematical modeling, eliminating the need for physical temperature and flow elements that are susceptible to contamination and damage. The modeled flow estimate reproduces the measurement capability without the vulnerable components.
Solution Approach 2:
The patent extracts and removes the vulnerable flow sensor components (temperature element, flow element) from the measurement system by replacing them with a computational approach that uses only the robust pressure sensor and existing valve parameters, thereby eliminating the source of contamination and damage issues.
3Productivity
If actual flow sensor measurements are used, then real-time flow data is obtained, but faulty measurements can occur due to sensor failures
Solution Approach 1:
The patent implements a feedback mechanism where the modeled flow estimate is continuously compared with actual flow sensor measurements when both are available. This feedback loop allows the system to validate the accuracy of the modeled flow and maintain measurement precision while preserving real-time data acquisition capability.
Solution Approach 2:
The patent prepares a modeled flow estimate in advance as a backup solution before flow sensor failures occur. This pre-established alternative measurement method cushions against the impact of sensor failures, ensuring continuous accurate flow data is available without interruption to real-time monitoring.
Data Source
AI summary
Systems and methods for model-driven system integration on a ventilator comprise a modeled exhalation flow. Ventilator flow sensors contain components that are easily damaged or impacted and have high rates of failure. Knowledge failure frequency and type may help determine when to replace, clean, or calibrate a flow sensor. A modeled exhalation flow may be trained for a ventilator. Additionally, the modeled exhalation flow may be compared to a flow sensor flow to determine a specific failure. Additionally or alternatively, the modeled exhalation flow may supplement, weight, or replace a faulty flow sensor measurement. These systems and methods may assist in identifying an inaccurate flow sensor measurement and/or providing a more accurate modeled flow estimate, thus increasing accuracy in patient-ventilator interactions.