A Pilot Human Study on Dual Photoplethysmography for Continuously Monitoring Pulse Wave Velocity and Blood Pressure

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 noninvasive 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.

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Publication Details

Journal
IEEE Journal on Flexible Electronics
Published
2025-09-25
DOI
https://doi.org/10.1109/jflex.2025.3614515
Primary Topic
Innovations in Aquaponics and Hydroponics Systems
Type
article
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article

A Pilot Human Study on Dual Photoplethysmography for Continuously Monitoring Pulse Wave Velocity and Blood Pressure

IEEE Journal on Flexible Electronics
Innovations in Aquaponics and Hydroponics Systems
article

A Pilot Human Study on Dual Photoplethysmography for Continuously Monitoring Pulse Wave Velocity and Blood Pressure

article en

Abstract

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 noninvasive 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.

IEEE Journal on Flexible ElectronicsVol. 4(11)
University of North Carolina at Chapel Hill (US)
Good health and well-being
Openalex Percentile: Top 44%
Innovations in Aquaponics and Hydroponics Systems
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