Therapeutic Gas Flow Backup Control During Sensor Disruptions
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Solution Overview
Problem
Existing therapeutic gas delivery systems face disruptions in breathing gas flow measurement, leading to potential interruptions in treatment, particularly when sensors become decoupled, provide inaccurate readings, or experience wear and tear, which can result in risks such as rebound pulmonary hypertension and incorrect dosing.
Innovation Solution
The system stores historical breathing gas flow rate data, including moving averages and waveforms, to compensate for disruptions by using this data to continue therapeutic gas delivery when current measurements are unavailable or unreliable, transitioning to a backup mode until the disruption is resolved.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time breathing gas flow measurement is used to control therapeutic gas delivery, then dosing accuracy is improved, but system reliability deteriorates due to sensor disruptions and measurement errors
Solution Approach 1:
The system pre-calculates and stores expected breathing gas flow values based on ventilator settings and patient parameters before actual measurement is needed. When sensor disruptions occur, these pre-calculated values serve as reliable fallback data to maintain continuous therapeutic gas delivery without interruption.
Solution Approach 2:
The patent introduces an intermediary computational model that translates ventilator control parameters into expected flow values. This intermediary layer acts as a mediator between the ventilator control system and the therapeutic gas delivery system, providing reliable flow data even when direct sensor measurements are disrupted.
2Reliability
If multiple sensors and complex measurement systems are used to improve measurement reliability, then dosing consistency is improved, but device complexity increases
Solution Approach 1:
Instead of using multiple physical sensors, the system creates a computational copy of the expected flow signal based on ventilator parameters. This virtual flow signal serves as a reliable alternative to physical sensor measurements, maintaining dosing consistency without adding sensor complexity.
Solution Approach 2:
The system transitions from relying on physical sensor parameters to using computational parameters derived from ventilator settings. By changing from measurement-based parameters to calculation-based parameters, the system maintains reliability while reducing device complexity.
Data Source
AI summary
The present disclosure generally relates to systems and methods for delivery of therapeutic gas to patients, using techniques to compensate for disruptions in breathing gas flow measurement, such as when breathing gas flow measurement is unavailable or unreliable. Such techniques include using historical breathing gas flow rate data, such as moving average flow rates, moving median flow rates and/or flow waveforms. At least some of these techniques can be used to ensure that interruption in therapeutic gas delivery is minimized or eliminated.