Physiological Characterization of Stress

This study analyses and characterizes changes in features extracted from physiological signals in the presence of affective states, namely, neutral, stress, and amusement. With a focus on the stress condition, for this purpose a statistical analysis was performed on various features extracted from ECG (electrocardiogram), EMG (electromyography), EDA (electrodermal activity), and RESP (respiration) signals from the WESAD dataset. This dataset provides data from 15 healthy participants regarding three affective conditions. Concerning the ECG features, from the statistical analysis, it was possible to observe a significant decrease in the interval between consecutive R peaks, meaning that there was an increase in heart rate. The EMG signal showed a significant increase in muscle activation. Regarding the EDA, it was noticed that during the stress condition, the production of sweat increased, leading to greater skin conductivity. Lastly with respect to the RESP signal, although no significant difference was observed in regards to changes in the inspiration and expiration durations, the increase in the standard deviation leads inferring an increase in the irregularity of the breathing pattern of the participants during the stress condition.