Physiological datasets in stress and anxiety research: A systematic review

Stress and anxiety have seen a marked increase in reported cases. Traditional research relies on self-reported assessments, often limited by subjectivity and the variability of individual perceptions. To overcome these limitations, there is a growing focus on the use of physiological signals to detect stress and anxiety more objectively. In this context, collecting and analyzing physiological data in studies on stress and anxiety facilitates scientific understanding and provides a robust foundation for testing and validating new detection technologies and methodologies. This systematic review examines 58 state-of-the-art datasets, highlighting key characteristics such as the physiological signals captured, their attributes, population diversity, data acquisition devices, and regulatory compliance. It also highlights significant limitations in the existing datasets, addressing a critical gap in the literature on physiological signal processing. By providing this analysis, the review aims to guide future research efforts toward creating more robust and diverse datasets.