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Stress assessment based on EEG univariate features and functional connectivity measures
Alonso López, Joan Francesc; Romero Lafuente, Sergio; Ballester Verneda, Maria Rosa; Antonijoan Arbós, Rosa Maria; Mañanas Villanueva, Miguel Ángel
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial; Universitat Politècnica de Catalunya. BIOART - Anàlisi de Biosenyals per a la Rehabilitació i la Teràpia
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.
Peer Reviewed
Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica
Stress
EEG
Stroop test
sleep deprivation
spectral analysis
mutual information function.
Estrès
Cervell -- Processament de dades
info:eu-repo/semantics/submittedVersion
Artículo
Institute of Physics (IOP)
         

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