Hemodynamic Parameter Determination Using Standard Deviation Interpolation
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Solution Overview
Problem
Current methods for calculating hemodynamic parameters like stroke volume variation (SVV), pulse pressure variation (PPV), and plethysmographic variability index (PVI) from blood pressure waveforms lack accuracy in distinguishing variations induced by mechanical ventilation from other causes, leading to suboptimal prediction of fluid responsiveness.
Innovation Solution
A method involving data processing to calculate standard deviations and interpolate variations, using polynomial functions or Fourier transforms to remove non-respiration-induced effects, thereby improving the sensitivity and specificity of parameter determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If standard blood pressure waveform analysis is used to calculate hemodynamic parameters, then the measurement process is simple and continuous, but the accuracy in distinguishing respiration-induced variations from other causes is insufficient
Solution Approach 1:
The patent segments the blood pressure waveform data into individual heart beats and further into specific phases (e.g., systolic, diastolic portions). By dividing the continuous waveform into discrete segments, the method can analyze variations within each segment and distinguish respiration-induced changes from other sources more accurately.
Solution Approach 2:
The patent utilizes the periodic nature of heartbeats and respiratory cycles by analyzing multiple consecutive heart beats and identifying patterns that repeat with respiratory frequency. This periodic analysis allows differentiation between respiration-induced variations and other non-periodic or differently-periodic variations in the waveform.
2Measurement precision
If polynomial interpolation is applied to calculate standard deviations for all data portions, then measurement accuracy improves, but computational time and processing complexity increase
Solution Approach 1:
The patent applies polynomial interpolation selectively to portions of the data where it provides the most benefit, rather than to all data points uniformly. By focusing the complex interpolation process on critical segments of the waveform, the method achieves improved accuracy while limiting the computational burden to only where necessary.
Solution Approach 2:
The patent performs preliminary processing of the blood pressure waveform data, such as identifying heart beat boundaries and filtering obvious artifacts, before applying the more computationally intensive polynomial interpolation. This preliminary preparation reduces the complexity of the subsequent interpolation process and improves overall processing efficiency.
Data Source
AI summary
Embodiments of the disclosure are directed to methods, apparatuses, and computer program products for determining a hemodynamic parameter. An exemplary method comprises: receiving data associated with at least one heart beat; calculating a first standard deviation for at least a portion of the data; interpolating a second standard deviation for at least a second portion of the data; and determining the hemodynamic parameter based on the first standard deviation and the second standard deviation.