EmpathicSchool: A multimodal dataset for real-time facial expressions and physiological data analysis under different stress conditions

EmpathicSchool is a novel dataset that captures facial expressions and the associated physiological signals, such as heart rate, electrodermal activity, and skin temperature, under different stress levels. The data was collected from 30 participants at different sessions for 42 hours. The data includes 7 different signal types, including both computer vision and physiological features that can be used to detect stress. In addition, various experiments were conducted to validate the signal quality.The data will be available upon signing the Data Usage Agreement.EmpathicSchool是一款新颖的数据集，可采集不同应激水平（stress levels）下的面部表情与关联生理信号，其中包括心率（heart rate）、皮肤电活动（electrodermal activity）、皮肤温度（skin temperature）等信号类型。该数据集的采集工作共覆盖30名参与者的多轮实验，总时长共计42小时。数据集共包含7类信号，涵盖计算机视觉特征（computer vision features）与生理特征两大类别，可用于应激检测任务。此外，研究团队开展了多组实验以验证该数据集的信号质量。签署数据使用协议（Data Usage Agreement）后，便可获取该数据集。