  Advances in wearable technologies provide the opportunity to monitor many
physiological variables continuously. Stress detection has gained increased
attention in recent years, mainly because early stress detection can help
individuals better manage health to minimize the negative impacts of long-term
stress exposure. This paper provides a unique stress detection dataset created
in a natural working environment in a hospital. This dataset is a collection of
biometric data of nurses during the COVID-19 outbreak. Studying stress in a
work environment is complex due to many social, cultural, and psychological
factors in dealing with stressful conditions. Therefore, we captured both the
physiological data and associated context pertaining to the stress events. We
monitored specifc physiological variables such as electrodermal activity, Heart
Rate, and skin temperature of the nurse subjects. A periodic
smartphone-administered survey also captured the contributing factors for the
detected stress events. A database containing the signals, stress events, and
survey responses is publicly available on Dryad.
