CAN-STEESS

CAN-STRESS is a multimodal dataset designed to facilitate research on the physiological and behavioral effects of cannabis use, particularly in relation to stress. The dataset was collected using Empatica E4 wristbands worn by 82 participants (39 cannabis users and 43 non-users) as they engaged in their daily activities. It includes high-resolution physiological signals, such as Electrodermal Activity (EDA), Heart Rate (HR), Blood Volume Pulse (BVP), Interbeat Interval (IBI), accelerometer data, and body temperature, providing objective measures of autonomic nervous system activity. Additionally, participants provided self-reported stress ratings on a scale of 0–9 at various moments throughout the day, along with timestamps for key activities such as sleep, exercise, and cannabis consumption. By integrating wearable sensor data with subjective stress assessments, CAN-STRESS enables researchers to explore the relationship between physiological stress markers and cannabis use in real-world settings. This dataset is particularly valuable for studies in stress detection, behavioral health, cannabis research, and machine learning applications related to physiological signal processing.