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Single-Trial Cognitive Stress Classification Using Portable Wireless Electroencephalography

Electrical and Computer Engineering Department, United States Naval Academy, Annapolis, MD 21402, USA
Department of Biomedical Engineering, Lund University, 221 00 Lund, Sweden
Author to whom correspondence should be addressed.
Sensors 2019, 19(3), 499;
Received: 29 November 2018 / Revised: 5 January 2019 / Accepted: 22 January 2019 / Published: 25 January 2019
(This article belongs to the Special Issue EEG Electrodes)
PDF [3327 KB, uploaded 25 January 2019]


This work used a low-cost wireless electroencephalography (EEG) headset to quantify the human response to different cognitive stress states on a single-trial basis. We used a Stroop-type color–word interference test to elicit mild stress responses in 18 subjects while recording scalp EEG. Signals recorded from thirteen scalp locations were analyzed using an algorithm that computes the root mean square voltages in the theta (4–8 Hz), alpha (8–13 Hz), and beta (13–30 Hz) bands immediately following the initiation of Stroop stimuli; the mean of the Teager energy in each of these three bands; and the wideband EEG signal line-length and number of peaks. These computational features were extracted from the EEG signals on thirteen electrodes during each stimulus presentation and used as inputs to logistic regression, quadratic discriminant analysis, and k-nearest neighbor classifiers. Two complementary analysis methodologies indicated classification accuracies over subjects of around 80% on a balanced dataset for the logistic regression classifier when information from all electrodes was taken into account simultaneously. Additionally, we found evidence that stress responses were preferentially time-locked to stimulus presentation, and that certain electrode–feature combinations worked broadly well across subjects to distinguish stress states. View Full-Text
Keywords: Electroencephalography; Cognitive stress; Biomedical signal processing; Brain–computer interface; Stroop test Electroencephalography; Cognitive stress; Biomedical signal processing; Brain–computer interface; Stroop test

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Blanco, J.A.; Vanleer, A.C.; Calibo, T.K.; Firebaugh, S.L. Single-Trial Cognitive Stress Classification Using Portable Wireless Electroencephalography. Sensors 2019, 19, 499.

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