Therapeutic Gas Delivery Run-Time Prediction from Pressure and Flow
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Solution Overview
Problem
Existing therapeutic gas delivery systems lack the ability to determine the amount of treatment time left before the gas source falls below a predetermined minimum or becomes empty, and do not provide fail-safe mechanisms to ensure continuous gas delivery.
Innovation Solution
The system includes a gas pressure sensor, flow regulators, and a controller that calculate the run-time-to-empty based on gas pressure and consumption rate, with redundant subsystems for fail-safe operation and automatic backup, and a method to verify gas source identity and concentration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a computerized system tracks patient information and communicates with gas delivery components, then gas delivery control is improved, but the ability to determine remaining treatment time is lost
Solution Approach 1:
The system performs preliminary actions by calculating the run-time-to-empty value in advance based on gas source volume, pressure, and consumption rate. This allows the system to proactively determine remaining treatment time before the gas source is depleted, enabling timely alerts and preventing sudden termination of therapy.
Solution Approach 2:
The system establishes a feedback loop where the controller continuously monitors gas pressure via the pressure sensor, updates the run-time-to-empty calculation based on actual consumption rates, and provides real-time information to the display. This closed-loop feedback ensures accurate and dynamic tracking of remaining treatment time.
2Measurement precision
If the system calculates run-time-to-empty based on pressure and consumption rate, then treatment time prediction is improved, but system complexity increases
Solution Approach 1:
The system performs self-service by automatically calculating the run-time-to-empty value using internally available data (pressure sensor readings and consumption rate) without requiring external intervention or complex additional instrumentation. The controller utilizes existing system resources to generate the prediction.
Solution Approach 2:
The system monitors changes in key parameters (gas pressure and consumption rate) to dynamically update the run-time-to-empty calculation. By tracking parameter variations over time, the system adapts to changing consumption patterns and maintains accurate predictions without requiring complex algorithms.
3Reliability
If redundant subsystems are added for fail-safe operation, then system reliability is improved, but device complexity increases
Solution Approach 1:
The system implements beforehand cushioning by providing advance warning through the run-time-to-empty calculation and display. This allows operators to prepare for potential gas depletion by arranging backup gas sources or adjusting treatment plans before actual depletion occurs, cushioning against the harmful effect of sudden therapy termination.
Solution Approach 2:
The system takes preliminary action by alerting operators to low gas levels before depletion occurs. This early warning enables proactive replacement of gas sources or adjustment of treatment parameters, preventing the adverse event of sudden gas termination and ensuring continuous patient care.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Ensures accurate determination of gas remaining time, prevents sudden gas termination, and provides seamless backup operation, enhancing safety and reliability in therapeutic gas delivery.
Implementation Method 1
a gas pressure sensor adjacent to and in fluid communication with the gas source valve, wherein the gas source valve provides a gas flow path from the gas source coupling to the gas pressure sensor, and the gas pressure sensor is configured to measure a gas pressure at the gas source coupling
Data Source
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AI summary
Therapy gas delivery systems (100) that provide run-time-to-empty information to a user of the system and methods for administering therapeutic gas to a patient. The therapeutic gas delivery system (100) may include a gas pressure sensor (120) attachable to a therapeutic gas source (116) that communicates therapeutic gas pressure data to a therapeutic gas delivery system controller (129,144,164), a gas temperature (130) sensor positioned to measure gas temperature in the therapeutic gas source (116) that communicates therapeutic gas temperature data to the therapeutic gas delivery system controller (129,144,164), at least one flow controller (144,164) that communicates therapeutic gas flow rate data to the therapeutic gas delivery system controller (129,144,164), at least one flow sensor (146,148) that communicates flow rate data to the therapeutic gas delivery system controller (129,144,164), and at least one display (112) that communicates run-time-to-empty to a user of the therapeutic gas delivery system (100). The therapeutic gas delivery system controller (129,144,164) of the system (100) includes a processor that executes an algorithm to calculate the run-time-to-empty from the data received from the gas pressure sensor (120), temperature sensor (130), flow controller (144,164) and flow sensor (146,148), and directs the result to the display (112).