Electroencephalographic Insights into Mental Stress Induced by Arithmetic Challenges

Mental stress is a significant factor contributing to various health issues, including heart attacks and strokes. Accurately measuring stress is crucial for timely clinical interventions and preventing these diseases. This research explores the potential of using Electroencephalography (EEG) signals to distinguish between stressed and relaxed states during mental arithmetic tasks. Our research demonstrates distinct variations in EEG signals when comparing states of relaxation and stress across three tiers of arithmetic complexity, showing significant p-values of 0.03, 0.042, and 0.05. This study verifies the effectiveness of EEG in identifying levels of mental stress. Furthermore, by employing a support vector machine (SVM), we achieved stress detection accuracies of 94%, 85%, and 80% for the respective levels of arithmetic task difficulty.