By Andreas Miltiadous, Vasileios Aspiotis, Konstantinos Sakkas, Nikolaos Giannakeas, Euripidis Glavas, Alexandros T. Tzallas
Abstract
Stress is a subject always relevant to scientific research due to the numerous implications in human life. Typical biomarkers used in the physiological evaluation of stress include Electrocardiography, cortisol levels, galvanic skin response and other. Recently, one less widely used instrument for the assessment of stress that has been re-emerged due to advancements in computational power and machine learning techniques, is Electroencephalography. Moreover, as Virtual Reality HMDs are being rapidly adopted by the research community it becomes apparent that leveraging the offered advantages of VR for the exploration of stress can lead to novel controlable and reproducable experimental procedures. In this paper we combine EEG, ECG and the Perceived Stress Scale with a Virtual Reality phobia induction setting, to propose a protocol for assessing stress. The suggested protocol can be used for functional brain connectivity investigation and thus the evaluation of stress while it and can be expanded via the incorporation of machine learning algorithms for automatic stress level classification.
