Stress assessment based on EEG univariate features and functional connectivity measures

J. F. Alonso, S. Romero, M. R. Ballester, R. M. Antonijoan, M. A. Mañanas

Research output: Contribution to journalArticleResearchpeer-review

48 Citations (Scopus)

Abstract

© 2015 Institute of Physics and Engineering in Medicine. The biological response to stress originates in the brain but involves different biochemical and physiological effects. Many common clinical methods to assess stress are based on the presence of specific hormones and on features extracted from different signals, including electrocardiogram, blood pressure, skin temperature, or galvanic skin response. The aim of this paper was to assess stress using EEG-based variables obtained from univariate analysis and functional connectivity evaluation. Two different stressors, the Stroop test and sleep deprivation, were applied to 30 volunteers to find common EEG patterns related to stress effects. Results showed a decrease of the high alpha power (11 to 12 Hz), an increase in the high beta band (23 to 36 Hz, considered a busy brain indicator), and a decrease in the approximate entropy. Moreover, connectivity showed that the high beta coherence and the interhemispheric nonlinear couplings, measured by the cross mutual information function, increased significantly for both stressors, suggesting that useful stress indexes may be obtained from EEG-based features.
Original languageEnglish
Article number1351
JournalPhysiological Measurement
Volume36
Issue number7
DOIs
Publication statusPublished - 1 Jul 2015

Fingerprint Dive into the research topics of 'Stress assessment based on EEG univariate features and functional connectivity measures'. Together they form a unique fingerprint.

Cite this