Understanding human emotions is always fascinating, emotions play a vital role in decision-making in our life. An automated way of recognizing human emotions with physiological signals can improve the system’s adaptation to emotive conditions of a person, with applications in working environments, like the optimization of employee well-being in settings based on the repetition of the same task all day. This study analyzes stress and arousal levels using a multimodal approach based on electrodermal activity (EDA), photoplethysmography (PPG) and electroencephalography (EEG) also evaluating the efficacy of two different normalization methods. In the first experiment two different VR environments were developed: one to elicit stress and one to give a less stressful experience.