Sequential Gas Delivery for Targeted End-Tidal Gas Pressures
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Solution Overview
Problem
Conventional methods for controlling end-tidal gas partial pressures are inadequate in achieving rapid and precise targeting due to the complex dynamics of gas exchange at the lungs and throughout the body, leading to unpredictable and unstable ventilatory responses.
Innovation Solution
A system and method that utilize a mass balance equation to prospectively determine the amount of gas needed in each breath to achieve targeted end-tidal partial pressures, considering factors like mixed venous blood concentration and alveolar gas exchange, using a gas delivery device and signal processor to control the inspired gas composition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If fixed changes to the composition of the inspired gas are used to manipulate end-tidal partial pressures, then the system is simple to operate, but the end-tidal partial pressures vary slowly and irregularly due to complex gas exchange dynamics
Solution Approach 1:
The system performs preliminary calculations of the required gas composition changes before each breath based on predicted gas exchange dynamics. The controller computes the necessary inspired gas composition in advance, allowing for rapid and predictable achievement of targeted end-tidal partial pressures without trial-and-error adjustments.
Solution Approach 2:
The system transitions from static fixed gas composition changes to dynamic, breath-by-breath adjusted gas delivery. The controller continuously adapts the inspired gas composition based on real-time measurements and predicted gas exchange, enabling rapid and precise control of end-tidal partial pressures despite complex physiological dynamics.
2Measurement precision
If negative feedback control is used to continuously vary the composition of the inspired gas, then the end-tidal partial pressures can be controlled more precisely, but the system suffers from inherent trade-off between response time and stability
Solution Approach 1:
The system calculates and prepares the required gas composition changes in advance before each breath occurs. By predicting the gas exchange dynamics and computing the necessary inspired gas composition beforehand, the system eliminates delays associated with real-time feedback adjustments, achieving both precision and rapid response.
Solution Approach 2:
The system incorporates real-time feedback from end-tidal partial pressure measurements to continuously refine and adjust the predicted gas exchange dynamics. This feedback mechanism ensures precision in control while the prospective calculation approach maintains rapid response by preparing adjustments before needed.
3Ease of operation
If conventional methods such as breath holding and hyperventilation are used to manipulate arterial carbon dioxide levels, then the approach is simple, but the ability to rapidly and accurately attain targeted arterial carbon dioxide partial pressures is deficient
Solution Approach 1:
The system uses real-time feedback from end-tidal partial pressure measurements to continuously adjust and refine the gas delivery composition. This closed-loop control enables accurate achievement of targeted carbon dioxide partial pressures by adapting to actual physiological response, overcoming the limitations of simple open-loop methods like breath holding and hyperventilation.
Solution Approach 2:
The system dynamically changes the composition parameters of the inspired gas breath-by-breath based on predicted gas exchange dynamics. By adjusting the inspired gas composition rather than relying on simple respiratory maneuvers, the system achieves rapid and accurate control of arterial carbon dioxide partial pressures with improved precision over conventional methods.
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
Enables precise and rapid control of end-tidal gas partial pressures, allowing for accurate measurement of vascular reactivity and diagnosis of conditions such as cerebrovascular disease, stroke, and liver fibrosis.
Implementation Method 1
A prospective computation is made, using a mass balance equation, of how much (if any) of the gas in question needs to be delivered by the device in a respective breath [i] to target a logistically attainable target end tidal concentration for the respective breath [i]
Implementation Method 2
The end-tidal partial pressures of gases are determined by the gases inspired into the lungs, the mixed venous partial pressures of gases in the pulmonary circulation, and the exchange of gases between the alveolar space and the blood in transit through the pulmonary capillaries
Data Source
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AI summary
A method of controlling an amount of gas X in a subject's lung using a sequential gas delivery circuit to attain a targeted end tidal partial pressure of gas X, the method comprising: obtaining input of a concentration of gas X in the mixed venous blood entering the subject's pulmonary circulation for gas exchange in one or more respective breaths [i] (CMVX[i]); obtaining input of a logistically attainable end tidal partial pressure of gas X (PetX[i]T) for a respective breath [i]; obtaining input of a prospective computation of an amount of gas X required to be inspired by the subject in an inspired gas to target the PetX[i]T for a respective breath [i] using inputs required to compute a mass balance equation including CMVX[i] and values to compute the contribution of one or more discrete volumetric components of breath [i] to the concentration of gas X in the subject's alveoli, wherein one or more values required to control the amount of gas X in a volume of gas delivered to the subject is output from the mass balance equation; and optionally controlling the amount gas X in a volume of gas delivered to the subject by the sequential gas delivery circuit in a respective breath [i] to target the respective PetX[i] based on the prospective computation.