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Single-Trial Cognitive Stress Classification Using Portable Wireless Electroencephalography

Blanco, Justin A. LU ; Vanleer, Ann C. ; Calibo, Taylor K. and Firebaugh, Samara L. (2019) In Sensors (Basel, Switzerland) 19(3).
Abstract

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... (More)

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.

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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Biomedical signal processing, Brain–computer interface, Cognitive stress, Electroencephalography, Stroop test
in
Sensors (Basel, Switzerland)
volume
19
issue
3
article number
499
publisher
MDPI AG
external identifiers
  • pmid:30691041
  • scopus:85060647597
ISSN
1424-8220
DOI
10.3390/s19030499
language
English
LU publication?
yes
id
8fb84764-1748-42a7-b3df-1929eb8fa2a4
date added to LUP
2019-02-05 11:06:37
date last changed
2020-09-16 04:08:46
@article{8fb84764-1748-42a7-b3df-1929eb8fa2a4,
  abstract     = {<p>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.</p>},
  author       = {Blanco, Justin A. and Vanleer, Ann C. and Calibo, Taylor K. and Firebaugh, Samara L.},
  issn         = {1424-8220},
  language     = {eng},
  month        = {01},
  number       = {3},
  publisher    = {MDPI AG},
  series       = {Sensors (Basel, Switzerland)},
  title        = {Single-Trial Cognitive Stress Classification Using Portable Wireless Electroencephalography},
  url          = {http://dx.doi.org/10.3390/s19030499},
  doi          = {10.3390/s19030499},
  volume       = {19},
  year         = {2019},
}