I+ Lab Emotion

Currently, existing public datasets based on peripheral physiological signals are limited, and there is a lack of emotion recognition (ER) datasets specifically customized for smart classroom scenarios. Therefore, we have collected and constructed the I+ Lab Emotion (ILEmo) dataset, which is specifically designed for the emotion monitoring of students in classroom. The raw data of the ILEmo dataset is collected by the I+ Lab at Shandong University, using custom multi-modal wristbands and computing suites. This dataset assesses the emotional states of students by recording various peripheral physiological signals from multiple students in classroom, along with different styles of instructional videos as stimuli. The dataset consists of data from 10 volunteers wearing wristbands on their left wrists. The wristband collects peripheral physiological data, acceleration, angular velocity, and environment data. Each wristband is equipped with a skin resistance sensor, a pulse wave sensor, and a skin temperature sensor to collect galvanic skin response (GSR), photoplethysmography (PPG), and skin temperature (TEMP), respectively. The collected peripheral physiological signals provide more comprehensive data for ER.