Adaptive Predictive Model for Blood Pressure Estimation
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Solution Overview
Problem
Current noninvasive continuous blood pressure monitoring methods, such as the volume clamp method, face limitations including the need for a mechanical finger cuff, unpredictable calibration due to physiological variations, sensitivity to motion artifacts, limited battery life, and insufficient accuracy during rapid blood pressure changes, making them unsuitable for ambulatory use and wearable applications.
Innovation Solution
A blood pressure monitoring system utilizing an adaptive predictive model that generates blood pressure estimates via real-time arterial pulse wave data from a PPG sensor, updating model parameters continuously to improve accuracy, and includes an inflatable cuff and processor for wearable devices to provide accurate and reliable blood pressure monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the volume clamp method is used for noninvasive continuous blood pressure monitoring, then blood pressure can be continuously estimated without invasive arterial line insertion, but the method requires a mechanical finger cuff making it unsuitable for ambulatory use
Solution Approach 1:
The patent replaces the mechanical finger cuff system with an optical PPG sensor-based system. Instead of using mechanical clamping force to control blood flow, the invention uses photoplethysmography to detect pulse wave characteristics and an adaptive predictive model to estimate blood pressure, thereby enabling ambulatory use without mechanical constraints.
Solution Approach 2:
The patent introduces an adaptive predictive model as an intermediary between the PPG sensor measurements and blood pressure estimation. This model processes the optical sensor data and translates it into accurate blood pressure readings, serving as a computational mediator that bridges the gap between simple optical detection and complex physiological parameter estimation.
2Productivity
If the volume clamp method is used, then continuous blood pressure monitoring is achieved, but the transfer function between finger blood flow, clamp pressure, and brachial artery pressure changes over time leading to calibration drift
Solution Approach 1:
The patent employs an adaptive predictive model that dynamically adjusts to changing physiological conditions. Instead of relying on a static transfer function, the system continuously adapts its parameters based on real-time PPG waveform characteristics, thereby maintaining measurement precision despite temporal variations in the subject's physiological state.
Solution Approach 2:
The system implements feedback mechanisms where the adaptive predictive model continuously refines its estimates based on ongoing PPG measurements. The model learns from the relationship between pulse wave features and actual blood pressure readings, adjusting its internal parameters to compensate for drift and maintain accuracy over time.
3Reliability
If the volume clamp method is used, then noninvasive blood pressure monitoring is achieved, but physiological extrema such as fat fingers or hardened arteries limit accurate calibration
Solution Approach 1:
The patent replaces the mechanical measurement approach that directly contacts and clamps the finger with an optical sensing system. The PPG sensor measures blood volume changes through light absorption without mechanical contact, thereby eliminating the limitations imposed by finger morphology such as fat fingers or hardened arteries that interfere with mechanical clamping.
4Productivity
If the volume clamp method is used, then continuous blood pressure monitoring is achieved, but the system is highly sensitive to motion artifacts reducing utility to stationary use cases only
Solution Approach 1:
The patent replaces the mechanical sensor system vulnerable to motion-induced artifacts with an optical PPG sensing system. Optical sensors are inherently more tolerant of motion because they detect physiological optical properties rather than relying on stable mechanical contact, thereby reducing sensitivity to motion artifacts during ambulatory use.
5Reliability
If the volume clamp method is used, then noninvasive blood pressure monitoring is achieved, but continuously active mechanical parts are required making the solution unsuitable for wearable applications with limited battery life
Solution Approach 1:
The patent replaces the continuously active mechanical pump and cuff system with a passive optical sensing system. The PPG sensor requires minimal power to emit light and detect optical changes, eliminating the need for continuously running mechanical components and significantly reducing energy consumption for wearable applications.
6Reliability
If the volume clamp method is used, then noninvasive blood pressure monitoring is achieved, but BP estimations are insufficiently accurate during rapid blood pressure increases or decreases
Solution Approach 1:
The patent employs an adaptive predictive model that dynamically responds to rapid physiological changes. The model continuously updates its parameters based on real-time PPG waveform characteristics, allowing it to track and accurately estimate blood pressure even during rapid increases or decreases, unlike static mechanical systems that lag behind fast-changing conditions.
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 achieves improved accuracy and reliability in blood pressure estimation, reducing the need for mechanical cuffs and enhancing usability for ambulatory and wearable applications by leveraging real-time data updates and adaptive predictive modeling.
Implementation Method 1
an arterial pulse wave sensor configured to obtain arterial pulse wave data from the subject... In some embodiments, the arterial pulse wave sensor is a PPG sensor
Data Source
AI summary
A blood pressure monitoring system includes a blood pressure monitoring device configured to obtain a blood pressure measurement from a subject, a PPG sensor configured to obtain PPG data from the subject, and at least one processor configured to generate a blood pressure estimation for the subject via an adaptive predictive model using real-time PPG data from the PPG sensor, determine whether the generated blood pressure estimation is above or below a threshold, and send an alert to a remote device in response to determining that the generated blood pressure estimation is above or below the threshold. The at least one processor may also be configured to request a blood pressure measurement from the blood pressure monitoring device in response to determining that the generated blood pressure estimation is above or below the threshold, and update the one or more parameters of the adaptive predictive model in real-time.