Bio-Impedance Cardiac Output Estimation Using Time-Frequency Features
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Solution Overview
Problem
Existing methods for estimating stroke volume and cardiac output, such as thermodilution and bio-impedance, lack the precision and reliability needed for rapid and continuous monitoring, particularly in changing hemodynamic conditions.
Innovation Solution
A system and method utilizing bio-impedance measurements combined with electrocardiogram signals, processed through time-frequency distributions and non-linear models, to extract characteristic features for accurate estimation of stroke volume and cardiac output.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If bio-impedance measurements are used for non-invasive monitoring, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent applies parameter changes by transforming the bio-impedance signal from time domain to time-frequency domain using distributions such as Wigner-Ville, Short-Time Fourier Transform, and Wavelet Transform. This transformation extracts additional characteristic features (frequency components, energy distribution, temporal patterns) that enhance the precision of stroke volume estimation while maintaining the non-invasive nature of the measurement.
2Measurement precision
If advanced signal processing is applied, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the complex signal processing task into distinct stages: (1) computing different types of time-frequency distributions from the bio-impedance signal, (2) extracting specific characteristic features from each distribution type, (3) combining these features through a non-linear model to estimate stroke volume and cardiac output. This segmentation makes the complex processing more manageable and implementable.
Solution Approach 2:
The patent combines multiple signal processing approaches (different time-frequency distribution methods) and integrates them with a non-linear model to create a composite estimation system. By fusing information from multiple processing pathways, the system achieves higher precision than any single method alone would provide.
3Reliability
If frequent or continuous monitoring is implemented, then reliability of hemodynamic status assessment is improved, but use of energy increases
Solution Approach 1:
The patent enables continuous monitoring by implementing real-time computation of time-frequency distributions and continuous extraction of characteristic features from the ongoing bio-impedance signal. This continuous processing provides reliable, up-to-date hemodynamic status assessment without requiring invasive procedures, balancing energy consumption against monitoring reliability.
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
Provides a reliable and precise estimation of stroke volume and cardiac output, enabling rapid adjustments in therapy by leveraging advanced signal processing and non-linear models to enhance accuracy.
Implementation Method 1
two excitation electrodes (100E) for applying an excitation signal, in particular a current, and two sensing electrodes (100S) for sensing a measurement signal (VC), in particular a voltage signal
Data Source
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Figure 2A~2C
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AI summary
A system (1) for estimating the stroke volume and/or the cardiac output of a patient, comprises a processor device (12) constituted to receive a bio-impedance measurement signal (VC) relating to a bio-impedance measurement on the thorax (2) of a patient (2), process the bio-impedance measurement signal (VC) to extract a group of characteristic features from the bio-impedance measurement signal (DVC) and/or its derivative (DVC), and determine, using the group of extracted characteristic features, an output value indicative of the stroke volume and/or the cardiac output using at least one non-linear model (110, 111). The processor device (12) furthermore is constituted to process the bio-impedance measurement signal (VC) to compute at least one time-frequency distribution (TFD) based on the bio-impedance measurement signal (VC) and/or its derivative and to determine at least one characteristic feature of said group of characteristic features based on the at least one time-frequency distribution (TFD).