Patient-Specific Digital Lung Model for Ventilator Optimization
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Solution Overview
Problem
Current ventilation methods for patients with lung diseases, such as acute respiratory failure or COVID-19, often require complex and iterative adjustments of ventilation parameters, leading to respiration-induced lung damage and high mortality rates due to the lack of precise, patient-specific assessment of ventilation harmfulness.
Innovation Solution
A computer-implemented method using a patient-specific digital lung model to iteratively determine optimal ventilation parameters by simulating mechanical ventilation, evaluating lung reactions, and adjusting parameters based on Bayesian optimization techniques to minimize mechanical load and ensure efficient gas exchange.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complex and iterative adjustments of ventilation parameters are performed manually, then ventilation can be adapted to patient needs, but respiration-induced lung damage occurs due to imprecise and delayed parameter optimization
Solution Approach 1:
The system performs self-optimization of ventilation parameters by automatically evaluating lung reactions and adjusting parameters without requiring continuous manual intervention. The computer program executes iterative optimization algorithms that autonomously determine optimal ventilation settings based on measured lung responses, reducing human error and improving ventilation safety.
Solution Approach 2:
The system implements closed-loop feedback by measuring actual lung reactions to ventilation, comparing these measurements with predicted reactions from the lung model, and using this feedback to iteratively optimize ventilation parameters. This feedback mechanism ensures parameters are precisely adjusted based on real patient responses, preventing lung damage while maintaining effective ventilation.
2Measurement precision
If statistical ventilation values and reference variables are used for ventilation assessment, then ventilation can be standardized, but precise patient-specific assessment of ventilation harmfulness is not achieved
Solution Approach 1:
The system transitions from using fixed statistical ventilation values to dynamically optimizing patient-specific ventilation parameters. By changing from standardized reference values to individually tailored parameters determined through iterative optimization based on patient-specific lung model predictions and actual measurements, the system achieves precise assessment of ventilation harmfulness for each patient.
Solution Approach 2:
The system performs preliminary assessment and optimization of ventilation parameters before actual ventilation is applied. The lung model predicts lung reactions to proposed ventilation settings, allowing the system to evaluate potential harmfulness in advance and adjust parameters preemptively, rather than relying on retrospective statistical analysis.
3Productivity
If ventilation parameters are adjusted frequently to adapt to patient needs, then ventilation effectiveness can be maintained, but the time required for parameter optimization increases
Solution Approach 1:
The system performs preliminary optimization calculations using the lung model to predict optimal ventilation parameters before applying them to the patient. This advance planning reduces the need for frequent iterative adjustments, as parameters are pre-optimized based on patient-specific characteristics and lung model predictions, thereby reducing the time lost to repeated parameter changes.
Solution Approach 2:
The system replaces manual parameter adjustment with automated computer-based optimization. The computer program executes optimization algorithms that rapidly evaluate multiple parameter combinations and determine optimal settings, significantly reducing the time required compared to manual trial-and-adjustment methods while maintaining or improving ventilation effectiveness.
Data Source
AI summary
The invention relates to a computer-implemented method, a computer program, a system, and a ventilation machine for determining patient-specific ventilation parameters for setting a ventilation machine by means of which the patient is to be ventilated.