Continuous Detection of Physiological Stress with Commodity Hardware

A new publication from the Amulet group:

Varun Mishra, Gunnar Pope, Sarah Lord, Stephanie Lewia, Byron Lowens, Kelly Caine, Sougata Sen, Ryan Halter, and David Kotz. “Continuous Detection of Physiological Stress with Commodity Hardware.” ACM Transactions on Computing for Healthcare (HEALTH), volume 1, number 2, article 8, 30 pages. ACM Press, April 2020. doi:10.1145/3361562. ©Copyright the authors.

Abstract: Timely detection of an individual’s stress level has the potential to improve stress management, thereby reducing the risk of adverse health consequences that may arise due to 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 to measure physiological signals; they are often bulky, custom made, and expensive, hence limiting their adoption by researchers and the general public. In this article, we explore the viability of commercially available off-the-shelf sensors for stress monitoring. The idea is to be able to use cheap, nonclinical sensors to capture physiological signals and make inferences about the wearer’s stress level based on that data. We describe a system involving a popular off-the-shelf heart rate monitor, the Polar H7; we evaluated our system with 26 participants in both a controlled lab setting with three well-validated stress-inducing stimuli and in free-living field conditions. Our analysis shows that using the off-the-shelf sensor alone, we were able to detect stressful events with an F1-score of up to 0.87 in the lab and 0.66 in the field, on par with clinical-grade sensors.

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About David Kotz

David Kotz is the Pat and John Rosenwald Professor in the Department of Computer Science at Dartmouth College. He previously served as Interim Provost, as Associate Dean of the Faculty for the Sciences, as the Executive Director of the Institute for Security Technology Studies, and on the US Healthcare IT Policy Committee. His research interests include security and privacy, pervasive computing for healthcare, and wireless networks. He has published over 230 refereed papers, obtained over $80m in grant funding, and mentored nearly 100 research students. He is a Fellow of the IEEE, a Distinguished Member of the ACM, a 2008 Fulbright Fellow to India, a 2019 Visiting Professor at ETH Zurich, 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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