Fluid Responsiveness Monitoring via Pulse Arrival Time
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Solution Overview
Problem
Current methods for determining fluid responsiveness, such as pulse pressure variation (PPV), are invasive and prone to noise in photoplethysmograph (PPG) signals, leading to inaccurate assessments of fluid responsiveness changes.
Innovation Solution
A physiological monitoring system using a light detecting sensor and processor to detect light absorption through tissue, generating a physiological signal and determining fluid responsiveness based on instantaneous and previous values, with an update characteristic selected based on whether fluid responsiveness is increasing or decreasing, to mitigate noise effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pulse pressure variation (PPV) is used to determine fluid responsiveness, then fluid responsiveness can be assessed, but the method is invasive and prone to noise in photoplethysmograph (PPG) signals leading to inaccurate assessments
Solution Approach 1:
The patent uses pulse arrival time (PAT) as an intermediary parameter to indirectly assess fluid responsiveness. Instead of directly measuring pulse pressure variation which is noisy, the system measures the time delay between the R-wave on ECG and the corresponding pulse wave detected by PPG sensor. This intermediary measurement approach avoids direct reliance on noisy PPG amplitude signals while still capturing hemodynamic changes related to fluid responsiveness.
Solution Approach 2:
The patent replaces the mechanical/invasive arterial line measurement system with an optical PPG-based system combined with ECG. By substituting the invasive mechanical pressure measurement with non-invasive optical detection of pulse wave timing, the system achieves similar physiological information without the harms of invasiveness and signal noise associated with traditional PPV methods.
2Adaptability or versatility
If traditional fluid responsiveness monitoring is used, then fluid status can be monitored, but the response time is fixed and does not adapt to changing conditions
Solution Approach 1:
The patent implements dynamic adaptability in the monitoring system by allowing the update characteristics to change based on the detected trend of fluid responsiveness. When the system detects that fluid responsiveness is increasing, it uses faster update characteristics to quickly capture the changing state. When fluid responsiveness is stable or decreasing, it uses slower update characteristics to filter noise. This dynamic adjustment optimizes both responsiveness and noise rejection in real-time.
Solution Approach 2:
The system continuously monitors the instantaneous fluid responsiveness values and uses this feedback to adjust the update characteristics. The feedback loop compares current measurements with previous values, determines the trend (increasing, decreasing, or stable), and automatically selects appropriate filtering and update parameters. This closed-loop feedback mechanism enables the system to adapt its behavior to changing physiological conditions without manual intervention.
3Measurement precision
If noise filtering is applied to PPG signals to improve accuracy, then measurement precision increases, but the response time increases and the system becomes less responsive to rapid changes
Solution Approach 1:
The patent dynamically adjusts the filtering strength based on the detected trend of fluid responsiveness. When the system identifies that fluid responsiveness is increasing (indicating a rapid physiological change), it applies lighter filtering to maintain fast response. When fluid responsiveness is stable or decreasing, it applies stronger filtering to improve precision. This dynamic filtering approach resolves the trade-off between speed and precision by adapting the filtering characteristics to the current physiological state.
Solution Approach 2:
The system changes the parameters of the filtering operation based on the detected trend. Specifically, it modifies the update characteristic parameter that controls how quickly the system responds to new measurements. By changing this parameter dynamically based on whether fluid responsiveness is increasing or decreasing, the system optimizes the balance between response speed and measurement precision for each physiological condition.
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
The system provides a non-invasive, accurate determination of fluid responsiveness with a response time adapted to changes, reducing the impact of noise and improving the reliability of fluid management decisions.
Implementation Method 1
a light detecting sensor configured to detect light absorbed through tissue of a subject, and generate a physiological signal based on the detected light
Data Source
AI summary
Methods and systems are provided for determining fluid responsiveness in the presence of noise. The system may determine an instantaneous value indicative of fluid responsiveness. In some embodiments, the system may determine a difference between an instantaneous value indicative of fluid responsiveness and a previous value indicative of fluid responsiveness, and select an update characteristic based on whether the difference indicates that the fluid responsiveness is increasing or decreasing. In some embodiments, the system may determine a parameter indicative of fluid responsiveness based on the update characteristic and a previously reported value indicative of fluid responsiveness.