ISPAAD: Integrated Stress, Physical Activity, and Amusement Dataset

Long-term stress exposure is a leading cause of sickness in adults and may even cause physiological issues such as heart diseases. Developing systems to detect and monitor stressful events based on physiological signals can help prevent stress-induced severe health implications. Research in this domain has shown that it is possible to reliably distinguish stress and its absence and differentiate between different types of stress. However, publicly available data in the stress detection domain is rare, which limits the research possibilities. Moreover, datasets are usually very heterogeneous owing to variations in experimental protocols and sensors used to record physiological signals, which limits the comparability. This work presents ISPAAD, an integrated stress, physical activity, and amusement dataset to overcome aforementioned limitations. The dataset is intended for stress detection, in-depth analysis of different stressors, and physical and affective states. The contributions of this paper are threefold: 1) the criteria to be considered for seamless data integration are outlined, 2) a vanilla data integration pipeline is introduced, and 3) a novel and multi-modal dataset is presented, bridging cognitive and socio-evaluative stress with physical activity as well as a positive affective state.