@article{2e985b810cc84c3480b5a8d0ef4f73e1,
title = "Dynamic Quantification of Migrainous Thermal Facial Patterns - A Pilot Study",
abstract = "This article documents thermophysiological patterns associated with migraine episodes, where the inner canthi and supraorbital temperatures drop significantly compared to normal conditions. These temperature drops are likely due to vasoconstriction of the ophthalmic arteries under the inner canthi and sympathetic activation of the eccrine glands in the supraorbital region, respectively. The thermal patterns were observed on eight migraine patients and meticulously quantified using advance computational methods, capable of delineating small anatomical structures in thermal imagery and tracking them automatically over time. These methods open the way for monitoring migraine episodes in nonclinical environments, where the patient maintains directional attention, such as his/her computer at home or at work. This development has the potential to significantly expand the operational envelope of migraine studies.",
keywords = "Migraine, face tracking, facial features, headache, maximum likelihood estimation, periorbital, supraorbital, thermal imaging",
author = "Ioannis Pavlidis and Ivan Garza and Panagiotis Tsiamyrtzis and Malcolm Dcosta and Swanson, {Jerry W.} and Thomas Krouskop and Levine, {James A.}",
note = "Funding Information: The authors would like to thank L. MacBride for her help in collecting data for this study. This material is based upon work supported by the National Science Foundation award IIS-0414754 entitled “Interacting with Human Physiology.” It was also supported in part by grants from the Texas Medical Center, the Methodist Hospital, and the Mayo Clinic Foundation for Research. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the funding agency. Funding Information: This work was supported in part by the National Science Foundation under Grant IIS-0414754, in part by the Texas Medical Center, in part by the Methodist Hospital, and in part by the Mayo Clinic Foundation for Research. Funding Information: Manuscript received January 31, 2018; revised June 3, 2018; accepted July 10, 2018. Date of publication July 12, 2018; date of current version May 6, 2019. This work was supported in part by the National Science Foundation under Grant IIS-0414754, in part by the Texas Medical Center, in part by the Methodist Hospital, and in part by the Mayo Clinic Foundation for Research. (Corresponding author: Ioannis Pavlidis.) I. Pavlidis is with the Computational Physiology Lab, University of Houston, Houston, TX 77204 USA (e-mail:,ipavlidis@uh.edu). Publisher Copyright: {\textcopyright} 2013 IEEE.",
year = "2019",
month = may,
doi = "10.1109/JBHI.2018.2855670",
language = "English (US)",
volume = "23",
pages = "1225--1233",
journal = "IEEE Journal of Biomedical and Health Informatics",
issn = "2168-2194",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "3",
}