Iterative Algorithm for Non-invasive Cardiac Output
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Solution Overview
Problem
Current methods for non-invasively measuring pulmonary blood flow are invasive, costly, and inaccurate, limiting their utility in clinical monitoring and physiological research due to fluctuations in alveolar ventilation and errors in calculating mixed-venous CO2 concentrations.
Innovation Solution
A novel iterative respiratory algorithm is developed to control a gas delivery apparatus, delivering a test gas to achieve a target concentration in the end tidal exhaled gas, allowing for iterative testing and refinement of pulmonary blood flow measurements using the Fick mass balance equation, enabling accurate and repeatable measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional rebreathing methods are used to measure pulmonary blood flow, then the measurement can be obtained, but the measurement precision is poor due to slow equilibration and recirculation errors
Solution Approach 1:
The system performs preliminary action by pre-delivering a calculated bolus of test gas (CO2) to the subject before the actual measurement. This preliminary bolus establishes a known initial concentration in the functional residual capacity, allowing the subsequent measurement phase to proceed with faster, more accurate equilibration without the slow exponential approach of traditional methods.
Solution Approach 2:
The system employs periodic action through iterative measurement cycles. After the initial bolus, the system delivers periodic test gas amounts and performs repeated measurements, using each cycle to refine the pulmonary blood flow calculation. This iterative approach allows the system to converge on an accurate measurement while maintaining rapid timing.
2Measurement precision
If iterative gas delivery is used to achieve target end-tidal concentration, then measurement precision improves, but device complexity increases
Solution Approach 1:
The system implements feedback control by continuously monitoring the subject's end-tidal test gas concentration and using this information to adjust subsequent gas delivery. The controller compares measured end-tidal concentrations with target values and modifies the amount of test gas delivered in the next cycle, creating a closed-loop system that achieves high precision without requiring overly complex hardware.
Solution Approach 2:
The system replaces complex mechanical gas delivery mechanisms with computational algorithms. Rather than using sophisticated hardware to precisely control gas flow, the invention uses software-based iterative calculation to determine the appropriate test gas amount to deliver, substituting mechanical complexity with computational simplicity.
3Productivity
If rapid measurement is implemented to reduce monitoring time, then productivity increases, but measurement precision may deteriorate due to insufficient equilibration
Solution Approach 1:
The system achieves rapid measurement while maintaining precision by performing preliminary action - delivering a calculated bolus of test gas that pre-establishes the conditions needed for quick equilibration. This preliminary step eliminates the need for long waiting periods, allowing rapid subsequent measurements without sacrificing accuracy.
Solution Approach 2:
The system employs dynamics by adapting the measurement protocol to the subject's real-time physiological response. The controller dynamically adjusts the test gas delivery based on measured end-tidal concentrations, allowing the system to optimize equilibration speed for each individual subject while maintaining measurement precision.
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
The method provides reliable, rapid, and repeatable non-invasive pulmonary blood flow monitoring, overcoming the limitations of previous techniques by iteratively refining measurements to achieve precise calculations of pulmonary blood flow.
Implementation Method 1
the flux of CO2 between the pulmonary capillary blood and the alveolar space is equal to the minute volume of expired CO2
Implementation Method 2
The Fick mass balance relation is shown in equation 1: V̇CO2 = Q̇(CvCO2 - CaCO2)
Data Source
AI summary
A method of controlling a gas delivery apparatus including an apparatus controllable variable using an iterative algorithm to deliver a test gas (TG) for non-invasively determining a subject's pulmonary blood flow comprising iteratively generating and evaluating test values of a iterated variable based on an iterative algorithm in order output a test value of the iterated variable that meets a test criterion wherein iterative algorithm is characterized in that it defines a test mathematical relationship between the at least one apparatus controllable variable, the iterated variable and an end tidal concentration of test gas attained by setting the apparatus controllable variable, such that the iterative algorithm is determinative of whether iteration on the test value satisfies a test criterion or iteratively generates a progressively refined test value.