The study presents the setup for automatic pain assessment, which aims to find discrepancies between physiological responses to electrical and mechanical pain stimulation. Since other works obtained satisfactory results on stimulus type classification, we developed a system for a comprehensive analysis of electrodermal activity (EDA) and photoplethysmography (PPG) signals’ patterns to find exact differences. The setup consists of two modules: (1) the data acquisition system and (2) data analysis software. Since the system automatically supervises the data-collecting stage, obtained recordings are precisely described and segmented. The data analysis software allows for a broad feature extraction. With the developed setup, we carried out a pilot study. The push-pull force gauge was employed as a mechanical stimulus, and the electro-stimulator acted as an electrical one. Then, a comparative analysis between pain and no-pain observations was performed. We observed more pronounced reactions in the EDA signal for electrical modality. The PPG amplitude drop was observed for mechanical stimuli during pain stimulation compared to the no-pain stage. Since state-of-the-art works mainly use electrical and heat stimulation, our work may extend the research gap with the pain response to mechanical stimuli.