  Stress detection and classification from wearable sensor data is an emerging
area of research with significant implications for individuals' physical and
mental health. In this work, we introduce a new dataset, ADARP, which contains
physiological data and self-report outcomes collected in real-world ambulatory
settings involving individuals diagnosed with alcohol use disorders. We
describe the user study, present details of the dataset, establish the
significant correlation between physiological data and self-reported outcomes,
demonstrate stress classification, and make our dataset public to facilitate
research.
