Fluid Responsiveness Indicator Fitting Optimization
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Solution Overview
Problem
Current methods for determining fluid responsiveness parameters are computationally intensive and time-consuming due to the Levenberg-Marquardt algorithm's high computational requirements, leading to prolonged processing times.
Innovation Solution
The approach involves reducing the number of data values for fitting, determining initial fit parameter values based on characteristics or previous fittings, and performing fitting in multiple stages, where the number of data values increases from stage to stage, using previously determined fit parameter values as initial values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the Levenberg-Marquardt algorithm is used for fitting the functional prototype to the envelope signal curve, then the accuracy of determining fluid responsiveness parameters is improved, but the computational time and processing duration increase significantly
Solution Approach 1:
The patent divides the continuous pulse signal into discrete respiratory cycles, extracting only the envelope signal curve data points for fitting. This segmentation reduces the dataset from thousands of individual pulse measurements to a manageable set of envelope maxima/minima points, significantly decreasing computational load while preserving the essential physiological information needed for accurate fluid responsiveness assessment
Solution Approach 2:
The patent performs preliminary processing by detecting and extracting the envelope signal curve from the raw pulse signals before applying the Levenberg-Marquardt algorithm. This preliminary action of identifying envelope maxima and minima points prepares the data in advance, allowing the computationally intensive fitting algorithm to work with pre-processed, optimized data rather than raw signals, thereby reducing overall processing time
2Measurement precision
If all measured pulse signal data values are used for fitting the functional prototype, then the measurement accuracy is improved, but the device complexity and computational requirements increase
Solution Approach 1:
The patent extracts only the essential features from the complete pulse signal dataset by identifying and isolating the envelope signal curve. Specifically, it extracts the maxima and minima points of the envelope during each respiratory cycle, discarding redundant intermediate data points. This extraction process maintains the critical information needed for accurate fitting while eliminating unnecessary computational complexity
Solution Approach 2:
The patent applies partial action by using only a subset of the available data points (envelope maxima and minima) rather than all pulse signal measurements. This selective approach provides sufficient information for accurate functional prototype fitting without the excessive computational burden of processing every individual pulse data point, achieving an optimal balance between accuracy and complexity
Data Source
AI summary
The invention relates to an apparatus for determining an indicator that is representative of a fluid responsiveness parameter. The indicator is determined based on a fitting of a functional prototype to data values (s0) determined from pulse signals measured over subsequent respiratory cycles. The fitting process is accelerated by a) reducing the number of data values before fitting, b) determining an initial fit parameter value for the functional prototype based on characteristics of the data values and/or a fit parameter value known from a previous fitting, and/or c) carrying out the fitting in several stages, wherein the number of data values used is increased from stage to stage and a fit parameter value determined in a previous stage is used as initial fit parameter value in a current stage. This allows for a faster determination of the fluid responsiveness parameter.