Respiratory Muscle Pressure Estimation via Least Squares Optimization
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Solution Overview
Problem
Current methods for estimating respiratory muscle pressure, respiratory system resistance, and compliance are invasive, noisy, and based on unrealistic assumptions, making them unsuitable for real-time monitoring in mechanically ventilated patients.
Innovation Solution
A system that estimates these parameters on a per-breath basis using the Equation of Motion of the Lungs, leveraging physiological constraints and fitting airway pressure and flow data with single-breath parameterized profiles, optimizing parameters through least squares optimization to provide real-time respiratory muscle pressure and system resistance and compliance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If invasive measurement techniques (esophageal pressure catheter) are used to measure respiratory muscle pressure, then measurement precision is improved, but device complexity and patient stress increase
Solution Approach 1:
The patent uses airway pressure and flow measurements as intermediary variables to indirectly estimate respiratory muscle pressure. Instead of directly measuring esophageal pressure with a catheter, the system uses the relationship between airway pressure, flow, and respiratory mechanics to compute Pmus through mathematical modeling, thereby avoiding invasive procedures while maintaining measurement capability
Solution Approach 2:
The patent replaces the mechanical invasive measurement system (catheter-based direct pressure sensing) with a computational approach using standard ventilator sensors. The system substitutes physical intrusion with mathematical estimation based on the equation of motion and optimization algorithms, eliminating the need for invasive devices
2Measurement precision
If flow-interrupter technique (End Inspiratory Pause) is used to estimate respiratory system resistance and compliance, then measurement precision is improved, but productivity decreases due to interference with mechanical ventilation
Solution Approach 1:
The patent enables continuous estimation of respiratory mechanics parameters during normal mechanical ventilation without interrupting the breathing support. The system processes airway pressure and flow data in real-time as they occur during spontaneous breathing efforts, eliminating the need for pause interruptions and maintaining continuous ventilatory support
Solution Approach 2:
The patent performs parameter estimation during the natural breathing cycle by utilizing the spontaneous inspiratory effort phase. Instead of waiting for or creating an interrupt pause, the system extracts mechanical parameters during the ongoing inspiratory flow, making use of the naturally occurring breathing mechanics to obtain measurements
3Device complexity
If conventional estimation methods based on airway blockage assumptions are used, then device complexity is reduced, but measurement precision deteriorates due to unrealistic assumptions
Solution Approach 1:
The patent transforms the estimation problem by changing from assuming blocked airway conditions to using actual flowing airway conditions with spontaneous breathing. The system modifies the underlying assumptions about respiratory mechanics to reflect realistic patient-ventilator interaction during pressure support ventilation, thereby improving accuracy without adding complexity
Solution Approach 2:
The patent incorporates feedback from actual airway pressure and flow measurements to continuously refine the estimation of respiratory muscle pressure. The system uses the measured variables in the equation of motion to compute Pmus, creating a feedback loop that adapts to the patient's actual breathing mechanics rather than relying on fixed assumptions
Data Source
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AI summary
Respiratory variables are estimated on a per-breath basis from airway pressure and flow data acquired by airway pressure and flow sensors (20, 22). A breath detector (28) detects a breath interval. A per-breath respiratory variables estimator (30) fits the airway pressure and flow data over the detected breath interval to an equation of motion of the lungs relating airway pressure, airway flow, and a single-breath parameterized respiratory muscle pressure profile (40, 42) to generate optimized parameter values for the single-breath parameterized respiratory muscle pressure profile. Respiratory muscle pressure is estimated as a function of time over the detected breath interval as the single-breath parameterized respiratory muscle pressure profile with the optimized parameter values, and may for example be displayed as a trend line on a display device (26, 36) or integrated (32) to generate Work of Breathing (WoB) for use in adjusting settings of a ventilator (10).