BibTeX for papers by David Kotz; for complete/updated list see
https://www.cs.dartmouth.edu/~kotz/research/papers.html

@InProceedings{mishra:commodity,
  author =        {Varun Mishra and Gunnar Pope and Sarah Lord and Stephanie Lewia and Byron Lowens and Kelly Caine and Sougata Sen and Ryan Halter and David Kotz},
  title =         {{The Case for a Commodity Hardware Solution for Stress Detection}},
  booktitle =     {{Proceedings of the Workshop on Mental Health: Sensing \& Intervention}},
  year =          2018,
  month =         {October},
  pages =         {1717--1728},
  publisher =     {ACM},
  copyright =     {ACM},
  DOI =           {10.1145/3267305.3267538},
  URL =           {https://www.cs.dartmouth.edu/~kotz/research/mishra-commodity/index.html},
  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.},
}