Electrical and Computer Engineering Department, United States Naval Academy, Annapolis, MD 21402, USA.
Department of Biomedical Engineering, Lund University, 221 00 Lund, Sweden.
Sensors (Basel). 2019 Jan 25;19(3):499. doi: 10.3390/s19030499.
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.
本研究使用低成本无线脑电图（EEG）耳机，在单次试验的基础上量化人类对不同认知应激状态的反应。我们使用斯特鲁普式颜色-文字干扰测试在 18 名被试者中诱发轻度应激反应，同时记录头皮 EEG。从 13 个头皮位置记录的信号使用一种算法进行分析，该算法计算刺激启动后即刻的θ（4-8 Hz）、α（8-13 Hz）和β（13-30 Hz）频段的均方根电压；每个频段的 Teager 能量均值；以及宽带 EEG 信号线长和峰值数。在每个刺激呈现期间，从 13 个电极的 EEG 信号中提取这些计算特征，并将其用作逻辑回归、二次判别分析和 k-最近邻分类器的输入。两种互补的分析方法表明，在同时考虑所有电极信息的情况下，逻辑回归分类器对平衡数据集的受试者的分类准确率约为 80%。此外，我们发现应激反应优先与刺激呈现时间锁定，并且某些电极-特征组合在很大程度上可以在不同的受试者中区分应激状态。
