TY - JOUR
T1 - A Pilot Human Study on Dual Photoplethysmography for Continuously Monitoring Pulse Wave Velocity and Blood Pressure
AU - Nguyen, Tien
AU - Kolla, Sai Satvik
AU - Wang, Henry
AU - Weisbecker, Hannah
AU - Messersmith, Braden
AU - Leal, Daniela Beatriz Martinez
AU - Kuntamukkala, Roshan
AU - Liu, Yihan
AU - Hanson, Erik D.
AU - Paterson, Craig
AU - Chauntry, Aiden J.
AU - Bai, Wubin
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2025/11/1
Y1 - 2025/11/1
N2 - Hypertension is a leading contributor to cardiovascular disease, stroke, and chronic kidney disease worldwide. However, current blood pressure (BP) monitoring techniques, whether auscultatory, oscillometric, or invasive, are constrained by episodic measurement, user variability, and limited feasibility for real-world, continuous monitoring. These limitations hinder early detection of abnormal BP patterns and long-term cardiovascular risk assessment. This paper presents a non-invasive device based on photoplethysmography (PPG) signals, with calculated Pulse Wave Velocity (PWV), that combines off-the-shelf sensors with an infrared-based dual PPG sensor. The device combines PPG signals and physiological measurements to predict blood pressure comprehensively using machine learning, with initial trials on 25 participants demonstrating promising accuracy with mean differences of 1.1 mmHg for Systolic Blood Pressure (SBP), -0.9 mmHg for Diastolic Blood Pressure (DBP), and -0.2 mmHg for Mean Arterial Pressure (MAP) compared to standard measurements with the Vicorder device. While primarily tested on a young population, the device shows potential for continuous, real-world BP and PWV monitoring, offering greater usability and accessibility than traditional tonometry- and oscillometry-based devices.
AB - Hypertension is a leading contributor to cardiovascular disease, stroke, and chronic kidney disease worldwide. However, current blood pressure (BP) monitoring techniques, whether auscultatory, oscillometric, or invasive, are constrained by episodic measurement, user variability, and limited feasibility for real-world, continuous monitoring. These limitations hinder early detection of abnormal BP patterns and long-term cardiovascular risk assessment. This paper presents a non-invasive device based on photoplethysmography (PPG) signals, with calculated Pulse Wave Velocity (PWV), that combines off-the-shelf sensors with an infrared-based dual PPG sensor. The device combines PPG signals and physiological measurements to predict blood pressure comprehensively using machine learning, with initial trials on 25 participants demonstrating promising accuracy with mean differences of 1.1 mmHg for Systolic Blood Pressure (SBP), -0.9 mmHg for Diastolic Blood Pressure (DBP), and -0.2 mmHg for Mean Arterial Pressure (MAP) compared to standard measurements with the Vicorder device. While primarily tested on a young population, the device shows potential for continuous, real-world BP and PWV monitoring, offering greater usability and accessibility than traditional tonometry- and oscillometry-based devices.
U2 - 10.1109/jflex.2025.3614515
DO - 10.1109/jflex.2025.3614515
M3 - Article (Academic Journal)
SN - 2768-167X
VL - 4
SP - 422
EP - 428
JO - IEEE Journal on Flexible Electronics
JF - IEEE Journal on Flexible Electronics
IS - 11
ER -