Classification of Mental State from Sub-THz Reflections from the Skin

Anna Kochnev Goldstein, Yoav Goldstein, Paul Ben Ishai, Yuri Feldman

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

By applying machine learning techniques on sub-THz reflectance measurements from the palms of 21 subjects, this work presents preliminary evidence that the reflected electromagnetic (EM) signal is inherently different during stress and relaxation periods. Furthermore, the obtained results demonstrate that this difference can be determined from a 30second-long measurement with an accuracy of 92% for binary classification between relaxation and stress and an accuracy of 88% for multiclass classification between relaxation, mental stress, and physical stress.

Original languageEnglish
Title of host publicationIRMMW-THz 2022 - 47th International Conference on Infrared, Millimeter and Terahertz Waves
PublisherIEEE Computer Society
ISBN (Electronic)9781728194271
DOIs
StatePublished - 2022
Event47th International Conference on Infrared, Millimeter and Terahertz Waves, IRMMW-THz 2022 - Delft, Netherlands
Duration: 28 Aug 20222 Sep 2022

Publication series

NameInternational Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz
Volume2022-August
ISSN (Print)2162-2027
ISSN (Electronic)2162-2035

Conference

Conference47th International Conference on Infrared, Millimeter and Terahertz Waves, IRMMW-THz 2022
Country/TerritoryNetherlands
CityDelft
Period28/08/222/09/22

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