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Using Eulerian video magnification framework to measure pulse transit time

Authors: Xiaochuan He; Rafik A. Goubran; Xiaoping P. Liu;

Using Eulerian video magnification framework to measure pulse transit time

Abstract

Recent advances in sensor technology and mobile computing are now enabling practical non-intrusive approaches to measure vital signs and other biological signals. Furthermore, most smart phones are now equipped with high resolution cameras and powerful processors that can reliably measure these signals. One of the signals of interest is the pulse transit time that is often correlated with changes in the blood pressure and stress level. Conventional techniques for measuring pulse transit time are based on measuring the electrocardiogram (ECG) signal using leads attached to the chest and measuring the plethysmograph (PPG) signal from a finger. This paper proposes a novel approach to measure pulse transit time non-intrusively using the Eulerian video magnification framework, particularly Eulerian color magnification. The proposed approach uses a video camera to capture a standard video sequence of the subject. After applying spatial decomposition and temporal filtering to the frames, the filtered signal is then amplified to reveal the subtle changing, like the color changing on different spots caused by the blood pulse. Two spots, the wrist and the neck, were selected to measure the pulse transit time. To verify the performance and practicability of the proposed system, the measured pulse transit time were compared with the time difference detected using a conventional technique based on two Pulse Sensors and the Arduino board. Ten subjects were studied under three status, climbing stairs, five minutes rest after climbing stairs, and twenty minutes rest after climbing stairs. The experimental results show that the pulse transit time measured by the Eulerian video magnification framework is highly correlated with the pulse transit time detected by pulse sensors, demonstrating that the proposed approach has the potential to be used for health-care monitoring.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
23
Top 10%
Top 10%
Top 10%
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