Characterization of Arterial Stiffness and High Blood Viscosity Using PPG Signals

This study uses PPG signals to determine arterial stiffness by analyzing blood flow characteristics to allow patients to better understand their health and take early preventive measures against cardiovascular diseases. The study uses the sine wave ratio (SIN ratio) as an indicator of arterial stiffness. A normal PPG waveform features a percussion wave and a diastolic wave, but some signals lack the diastolic wave if there is arterial stiffness, so a sine wave results. This study identifies a sine wave using the first derivative and an auxiliary line method and calculates the SIN ratio. Sine waves are classified as two types: the first whereby arterial stiffness causes rapid blood flow rebound, so there is an overlap in the reflected wave and the primary peak, and the other whereby high blood viscosity slows blood flow, which decreases the amplitude of the reflected wave. To increase the accuracy with which arterial stiffness is determined, an algorithm to filter these waveform types is proposed. The study uses data from 142 participants.

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Publication Details

Published
2024-12-11
DOI
https://doi.org/10.1109/iecbes61011.2024.10990920
Citations
1
Primary Topic
Non-Invasive Vital Sign Monitoring
Type
article
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0.18
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Characterization of Arterial Stiffness and High Blood Viscosity Using PPG Signals

Michael Hsiao, Rui Wu, Lei Wang, Zijun Chen
1 citations
Non-Invasive Vital Sign Monitoring
0.18
article

Characterization of Arterial Stiffness and High Blood Viscosity Using PPG Signals

Michael Hsiao, Rui Wu, Lei Wang, Zijun Chen
article en
1 citations

Abstract

This study uses PPG signals to determine arterial stiffness by analyzing blood flow characteristics to allow patients to better understand their health and take early preventive measures against cardiovascular diseases. The study uses the sine wave ratio (SIN ratio) as an indicator of arterial stiffness. A normal PPG waveform features a percussion wave and a diastolic wave, but some signals lack the diastolic wave if there is arterial stiffness, so a sine wave results. This study identifies a sine wave using the first derivative and an auxiliary line method and calculates the SIN ratio. Sine waves are classified as two types: the first whereby arterial stiffness causes rapid blood flow rebound, so there is an overlap in the reflected wave and the primary peak, and the other whereby high blood viscosity slows blood flow, which decreases the amplitude of the reflected wave. To increase the accuracy with which arterial stiffness is determined, an algorithm to filter these waveform types is proposed. The study uses data from 142 participants.

Feng Chia University (TW)
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Non-Invasive Vital Sign Monitoring
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