Sensing stress with commodity sensors

The Amulet group has been developing sensors, apps, and algorithms for sensing stress, in the field.  In one of the first papers to come out of that effort, presented today in a UbiComp workshop, we explore the potential for detecting stress using a single commodity wearable sensor.

Varun Mishra, Gunnar Pope, Sarah Lord, Stephanie Lewia, Byron Lowens, Kelly Caine, Sougata Sen, Ryan Halter, and David Kotz. The Case for a Commodity Hardware Solution for Stress Detection. In Workshop on Mental Health: Sensing & Intervention, pages 1717-1728, October 2018. ACM. DOI 10.1145/3267305.3267538.

Abstract: Timely detection of an individual’s stress level has the potential to expedite and improve stress management, thereby reducing the risk of adverse health consequences that may arise due to unawareness or mismanagement of stress. Recent advances in wearable sensing have resulted in multiple approaches to detect and monitor stress with varying levels of accuracy. The most accurate methods, however, rely on clinical grade sensors strapped to the user. These sensors measure physiological signals of a person and are often bulky, custom-made, expensive, and/or in limited supply, hence limiting their large-scale adoption by researchers and the general public. In this paper, we explore the viability of commercially available off-the-shelf sensors for stress monitoring. The idea is to be able to use cheap, non-clinical sensors to capture physiological signals, and make inferences about the wearer’s stress level based on that data. In this paper, we describe a system involving a popular off-the-shelf heart-rate monitor, the Polar H7; we evaluated our system in a lab setting with three well-validated stress-inducing stimuli with 26 participants. Our analysis shows that using the off-the-shelf sensor alone, we were able to detect stressful events with an F1 score of 0.81, on par with clinical-grade sensors.

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About David Kotz

David Kotz is the Provost, the Pat and John Rosenwald Professor in the Department of Computer Science, and the Director of Emerging Technologies and Data Analytics in the Center for Technology and Behavioral Health, all at Dartmouth College. He previously served as Associate Dean of the Faculty for the Sciences and as the Executive Director of the Institute for Security Technology Studies. His research interests include security and privacy in smart homes, pervasive computing for healthcare, and wireless networks. He has published over 240 refereed papers, obtained $89m in grant funding, and mentored nearly 100 research students. He is an ACM Fellow, an IEEE Fellow, a 2008 Fulbright Fellow to India, a 2019 Visiting Professor at ETH Zürich, and an elected member of Phi Beta Kappa. He received his AB in Computer Science and Physics from Dartmouth in 1986, and his PhD in Computer Science from Duke University in 1991.

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