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Proceedings Paper

Remotely detected differential pulse transit time as a stress indicator
Author(s): Balvinder Kaur; Elizabeth Tarbox; Marty Cissel; Sophia Moses; Megha Luthra; Misha Vaidya; Nhien Tran; Vasiliki N. Ikonomidou
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Paper Abstract

The human cardiovascular system, controlled by the autonomic nervous system (ANS), is one of the first sites where one can see the “fight-or-flight” response due to the presence of external stressors. In this paper, we investigate the possibility of detecting mental stress using a novel measure that can be measured in a contactless manner: Pulse transit time (dPTT), which refers to the time that is required for the blood wave (BW) to cover the distance from the heart to a defined remote location in the body. Loosely related to blood pressure, PTT is a measure of blood velocity, and is also implicated in the “fight-or-flight” response. We define the differential PTT (dPTT) as the difference in PTT between two remote areas of the body, such as the forehead and the palm. Expanding our previous work on remote BW detection from visible spectrum videos, we built a system that remotely measures dPTT. Human subject data were collected under an IRB approved protocol from 15 subjects both under normal and stress states and are used to initially establish the potential use of remote dPPT detection as a stress indicator.

Paper Details

Date Published: 2 June 2015
PDF: 8 pages
Proc. SPIE 9496, Independent Component Analyses, Compressive Sampling, Large Data Analyses (LDA), Neural Networks, Biosystems, and Nanoengineering XIII, 949604 (2 June 2015); doi: 10.1117/12.2177886
Show Author Affiliations
Balvinder Kaur, George Mason Univ. (United States)
Elizabeth Tarbox, George Mason Univ. (United States)
Marty Cissel, George Mason Univ. (United States)
Sophia Moses, George Mason Univ. (United States)
Megha Luthra, George Mason Univ. (United States)
Misha Vaidya, George Mason Univ. (United States)
Nhien Tran, George Mason Univ. (United States)
Vasiliki N. Ikonomidou, George Mason Univ. (United States)


Published in SPIE Proceedings Vol. 9496:
Independent Component Analyses, Compressive Sampling, Large Data Analyses (LDA), Neural Networks, Biosystems, and Nanoengineering XIII
Harold H. Szu; Liyi Dai; Yufeng Zheng, Editor(s)

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