Assessment of Mental Stress Using EEG and fNIRS Features

Abstract

Stress is a major contributing factor to chronical disorders and productivity loss. Students spend most of their time studying, often burdened with high workloads and time pressure, a factors that contribute to increase the level of stress and decrease their academic performance. Stress activates the hypothalamus-pituitary-adrenocortical axis and the sympathetic nervous system leading to the release of stress hormone (cortisol) in the adrenal cortex. The continuous release of cortisol leads to several chronical diseases including anxiety, depression, stroke and even addiction. Therefore, an accurate stress detection method at its early stage is very important to clinical intervention, diseases prevention as well as for academic performance. While different neuroimaging modalities have been proposed to detect mental stress, each modality experiences certain limitations. Neuroimaging tools such as functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) have good spatial resolution, yet are limited in terms of temporal resolution and susceptibility to motion artifacts. They also require the test subjects to remain at fixed position during scanning. Electroencephalography (EEG) constitutes a possible alternative neuroimaging technique that does not possess the same limitations. The EEG has temporal resolution in the order of a few milliseconds, which makes it suitable for measuring cortical changes during workplace activities. However, the EEG is generally considered as having poor spatial resolution (compare to excellent fMRI modality) and being highly prone to motion artifacts. Functional near-infrared spectroscopy (fNIRS) has allowed human cortical activity to be measured during unconstrained movements, the temporal resolution is sub-second, and the spatial resolution is on order of 1 cm2 at best. In order to overcome these constraints, it is advisable to combine the EEG with fNIRS modality to provide a complementary nature and improve the detection rate of mental stress.