ABSTRACT HCI researchers and practitioners are increasingly using physiological data to measure User eXperience (UX) parameters. The dynamic nature of physiological data offers a continuous window for an in-depth understanding of users’ interaction experience. However, in order to be truly informative, physiological signals need to be linked to users’ interaction experience aspects, such as their emotional states, in a systematic and efficient way. Studies have shown that skin conductance is a physiological signal highly associated with stress. The main purpose of this paper is to present the validation study of our proposed stress detection mechanism which is integrated into a software named PhysiOBS. PhysiOBS is an observation analysis tool that can be used in the post-study analysis phase. PhysiOBS uses nonspecific skin conductance responses (NS-SCRs) in order to auto-report time periods that are probably associated with a problematic interaction. PhysiOBS can also combine multiple data sources. Hence, UX evaluators are able to further investigate a recorded session in order to reveal additional interaction flaws. The integrated stress assessment mechanism, which uses four trained classifiers, can be applied in the reported periods (auto/expert-reported) in order to classify them as stress or non-stress. For the purpose of the validation study, 24 users were recruited in order to participate in a lab experiment. Results showed that our stress assessment mechanism supports UX evaluators by accurately identifying stressful regions within an interaction scenario.