A systematic literature review aiming to identify the characteristics of physiological signals on two types of stress states - single moderate thermal stress state and moderate thermal stress combined with cognitive stress state – was conducted. Results of the review serve as a backdrop to envision different scenarios on the detection of these stress states in everyday situations, such as in schools, workplaces and residential settings, where the use of interactive technologies is commonplace. Stress detection is one of the most studied areas of affective computing. However, current models developed for stress detection only focus on recognizing whether a person is stressed, but not on identifying stress states. It is essential to differentiate them in order to implement strategies to minimize the source of stress by designing different interactive technologies. Wearables are commonly used to acquire physiological signals, such as heart rate and respiratory rate. Analysis results of these signals can support a user to make a decision for taking actions or to make an automatic system undertake certain strategies to counteract the sources of stress. These technologies can be designed for educational, work or medical environments. Our future work is to validate these use scenarios systematically to enhance the design of the technologies.