AI Hemodynamic Prediction from Noninvasive Biosignals
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Solution Overview
Problem
Current hemodynamic monitoring relies heavily on invasive methods for accurate measurements of parameters like pulmonary arterial pressure, central venous pressure, and arterial blood pressure, which can be cumbersome and less accessible for continuous, non-invasive monitoring.
Innovation Solution
An apparatus and method utilizing non-invasive biosignals and AI models to predict hemodynamic parameters, such as pulmonary arterial pressure, arterial blood pressure, and central venous pressure, from input variables like ECG, ICG, PPG, and other general inputs, allowing for non-invasive estimation of these parameters using a processor and AI analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If invasive sensors or catheters are used to measure hemodynamic parameters, then measurement precision is improved, but device complexity and patient discomfort increase
Solution Approach 1:
The patent uses an AI model as an intermediary to translate easily obtainable noninvasive biosignals (ECG, PPG, ICG) into accurate predictions of hemodynamic parameters. This mediator enables the system to achieve clinical-grade measurement precision without requiring direct invasive contact with blood vessels or heart chambers.
Solution Approach 2:
The invention replaces the mechanical invasive catheter-based measurement system with a computational approach using AI models that process electrical and optical biosignals. This substitution eliminates the need for physical insertion of sensors into the cardiovascular system while maintaining measurement accuracy.
2Reliability
If invasive catheters are used for continuous hemodynamic monitoring, then measurement reliability is improved, but ease of operation deteriorates
Solution Approach 1:
The system utilizes biosignals that are naturally produced by the patient's own physiology (electrical signals from the heart, optical signals from blood flow) and processes them through AI algorithms. This self-service approach eliminates the need for external invasive instrumentation while maintaining continuous monitoring capability.
3Ease of operation
If noninvasive methods are used to estimate hemodynamic parameters, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent transforms the relationship between input biosignals and output hemodynamic parameters through AI model processing. By changing the analytical parameters and using sophisticated algorithms, the system achieves clinical-grade precision from noninvasive measurements, overcoming the traditional accuracy limitations of such methods.
Data Source
AI summary
The present disclosure relates to an apparatus for predicting a hemodynamics parameter being conventionally obtained from an implanted sensor or catheter (invasive sensor), e.g., pulmonary artery pressure, based on noninvasive biosignals, such as electrocardiographic (ECG), impedance cardio graphic (ICG), phonocardiogram (PCG), pulse oximetry plethysmograph (PPG). The present disclosure also relates to a method of feeding multiple noninvasive biosignals and/or general inputs into an AI model or AI models to predict a hemodynamics parameter, such as pulmonary artery pressure, which is conventionally obtained from an implanted sensor or catheter.