Scenario Adaptive Cuffless Blood Pressure Estimation by Integrating Cardiovascular Coupling Effects

Area of Science:

• Biomedical Engineering
• Cardiovascular Technology
• Wearable Health Devices

Background:

• Cuffless blood pressure (BP) monitoring in wearables is crucial for hypertension management.
• Existing pulse transit time (PTT)-based methods face accuracy degradation and procedural sensitivity.
• Novel methods are needed for reliable and adaptable cuffless BP measurement.

Purpose of the Study:

• To introduce a pattern-fusion (PF) method for accurate cuffless BP measurement.
• To incorporate cardiovascular coupling effects into a vascular model for enhanced BP prediction.
• To develop a robust method for wearable hypertension monitoring.

Main Methods:

• Proposed a three-module pattern-fusion (PF) method: cardiac parameter extraction, cardiac parameter-to-BP mapping, and BP regulation.
• Cardiac parameter extraction module models cardiovascular system modulations using feedforward, feedback, and propagation modes from ECG and PPG signals.
• BP regulation module refines systolic BP (SBP) and diastolic BP (DBP) from mean BP (MBP).

Main Results:

• The PF method demonstrated consistent BP prediction accuracy across various scenarios.
• Achieved SBP/DBP mean absolute error (MAE) of 3.65/4.56 mmHg for short-term (<10 min) measurements.
• Reported SBP/DBP MAE of 6.84/3.81 mmHg for medium-term (>20 hours) and 6.24/3.65 mmHg for long-term (>1 month) measurements.

Conclusions:

• The pattern-fusion method offers a significant advancement in cuffless BP monitoring accuracy and reliability.
• The integrated approach effectively addresses limitations of traditional PTT-based methods.
• This technology holds promise for improved hypertension management through wearable devices.