The AffectiveRoad dataset used Empatica E4 and Zephyr Bioharness 3 to study the effect of driving conditions on stress of 10 drivers, for which each driver took a 1h26m driving test. Our work was inspired by previous work on wearables to monitor physiological signals related to stress. Signals, stress events, and survey responses is available upon request. A periodic smartphone-administered survey also captured theĬontributing factors for the detected stress events. Specific physiological variables that were monitored included electrodermalĪctivity, heart rate, skin temperature, and accelerometer data of the nurse Physiological data and associated context pertaining to the stress events. In order to address these concerns, we captured both the Many social, cultural and individuals experience in dealing with stressfulĬonditions. ![]() Stress "in the wild" in a work environment is complex due to the influence of This dataset is aĬollection of biometric data of nurses during the COVID-19 outbreak. This paper provides a unique stress detection dataset that wasĬreated in a natural working environment in a hospital. Individuals better manage health to minimize the negative impacts of long-term Stress detection has gained increasedĪttention in recent years, especially because early stress detection can help Advances in wearable technologies provide the opportunity to continuously
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